Proceedings of the International Field Exploration and Development Conference 2018 [1st ed. 2020] 978-981-13-7126-4, 978-981-13-7127-1

Table of contents :
Front Matter ....Pages i-xxi
The Nonlinear Flow Analytical Model and Its Field Use (Hongbing Jia, Baoquan Song, Wei Mao, Zhijing Bao, PengJu Du, Yaguang Li et al.)....Pages 1-10
Research on Low Damage Drilling Fluids and Application in Low Permeability Reservoirs of Shengli Oilfield (J. Y. Liu, E. D. Chen, X. L. Li)....Pages 11-23
Multistage Fractures Optimum of Different Cluster Wells in Tight Gas Reservoirs (Shihua Liu)....Pages 24-41
Deliverability Evaluation on Horizontal Well with DHC in Tight Sandstone Gas Reservoir (Yundong Xu, Zhen Sun, Liangrong You, Long Chen, Liu He, Shunzhi Yang et al.)....Pages 42-47
The Integration of Checking Seal and Testing Regulation of Bridge Concentric Layered Water Injection Technology Research and Application (Lingzhi Yang, Jiuzheng Yu, Bin Yao, Yanqing Liu, Changlong Yu, Fuwei Bi)....Pages 48-55
Permeability and Viscosity Index Range Estimation of Imbibition Agent Suitable for Low-Permeability Reservoir (Yi Zhang, Jianguo Li, Fangge Gong, Yun Sun, Haihui Chen, Hongyan Cai et al.)....Pages 56-73
Influence of Low-Frequency Vibration Acceleration on the Permeability of Low Permeable Porous Media During Water Flooding (Liming Zheng, Wenhao Cui, Jing Liu, Lei Zhang)....Pages 74-86
Long Horizontal Section Well Application in Developing Ultra-Low Permeability Layer (Baixue Chen)....Pages 87-94
Performance Evaluation and Optimization of Temporary Plugging Agent Used in Diverting Fracturing (Haiyang Ma, Qingzhi Wen, Mingliang Luo, Tingting Yu, Gang Lei, Xiaofei Duan et al.)....Pages 95-107
Investigation on Productivity and Affecting Factors of Low Permeability Reservoir Using Radial Water Jet Drilling (Xudong Shen, Xinwei Liao, Xiaoliang Zhao, Xiongtao Shang, Weiyun Luo)....Pages 108-118
Research and Application of Dual Packer Multistage Control Fracturing Technology in Horizontal Wells (Jinyou Wang)....Pages 119-128
Discussion on the Technical Countermeasures of Hechuan Xujiahe Gas Reservoir Development (Qinglong Xu, Yongzhuo Wang, Xuemin Zhou, Ping Shu)....Pages 129-139
Study on Areal Sweep Coefficient Under Water Flooding in Ultra-Low Permeability Reservoirs (He Congge, Xu Anzhu, Zhao Lun, Fan Zifei)....Pages 140-152
Dynamic Fracture and Matrix Heterogeneity and Remaining Oil Models of Ultra-Low Permeability Reservoir (Li Liu, Youjing Wang, Jiahong Li)....Pages 153-170
Production Analysis Method Based on Material Balance Pseudo-time for Water Production Gas Wells (Jianning Luo, Yanyan Sun, Bo Zhang, Jun Yue, Minghui Huo)....Pages 171-180
A Drilling Rate Model for Roller Cone Bit with Experimental Verification (Li Wei, Li Bing, Sun Wenfeng, Li Siqi, Zhao Huan)....Pages 181-190
Analysis of Inversion Structure and Trap Diversity in a Block of Western Qaidam Basin (Wang Guihong, Chen Zhiyong, Zhou Chuanmin, Lv Jietang, Zhang Ming, Wang Dianao)....Pages 191-202
Rock Fracture Analysis Method in Drilling Operation (Zhaomei Xue)....Pages 203-211
Analysis of the Influence Factors of Casing Damage Based on Data Mining (Shujuan Zhang, Xueqing Zhang, Wenchang Fu, Jin Zhang, Liqiu Zhang, Qinghong Liu et al.)....Pages 212-221
Application of Geostatistical Inversion to Thin Reservoir Prediction in the Indonesian Project (C. L. Li, D. M. Li, H. Q. Zhu)....Pages 222-235
The Research on Teeth Invade Bottom-Hole Rock Basing on Unified Strength Theory (Li Wei, Zhao Huan, Li Siqi, Ling Xin)....Pages 236-246
Carbon Dioxide Corrosion on Casing Under High-Temperature and High-Pressure Conditions in Deep Wells (Jingfu Zhang, Shuai Shao, Shuting Wang, Wenhui Xiao, Ziyang Lin)....Pages 247-260
Calculation Model of Rock Fracture Pressure Under Multifield Coupling Action (Zhao Xiaojiao, Qu Zhan, Xu Xiaofeng, Yu Xiaocong, Fan Heng)....Pages 261-273
Experimental Study on Pore Structure Damage of Bedding Shale Under Ultralow Temperature (Zhongying Han, Yuanfang Cheng, Huaidong Wang)....Pages 274-283
Simulation on Formation Mechanism of Qiongdongnan Basin (Liu Xinlu, Li Zian, Liang Yingjie, Ma Teng)....Pages 284-295
Prediction of Gas-Bearing Properties of Compact Sandstone Based on Avo-Analyzed Attribute Variance (Mingbo Bi, Yijun Zhou, Yadong Zhang, Yu Lei)....Pages 296-303
Study on Reservoir Properties’ Varying Laws and Production Features of CBM Wells (Qing Feng, Miao Tian, Zijun Huang, Ming Zeng, Tao Wang, Wanchun Zhang et al.)....Pages 304-315
The Mathematical Analysis of Temperature-Pressure-Adsorption Data of Deep Shale Gas (Hao Jingyuan, Li Dong, Zhang Xuemei, Ma Qinghua)....Pages 316-327
A New Method for Flooded Layer Evaluation by Logging with Strong Heterogeneous in Heavy Oil Reservoirs, K Field, Central Asia (Yaping Lin, Zhenhua Guo, Shanbo Sheng, Junzhang Zheng, Man Luo, Hongwei Liang)....Pages 328-339
Evaluation of Shale Gas Resource Potential in Devonian–Carboniferous of Yaziluo Region (Yazhao Liu, Haijun Zhang, Yuru Xiao, Hao Li)....Pages 340-348
Application and Characterization Technology of Cleat in Medium-Rank Coalbed Methane (Liangchao Qu, Zhaohui Xia, Lijiang Duan, Ming Zhang, Lingli Liu, Kening Zheng)....Pages 349-360
Characteristics and Classification Evaluation of Tight Sandstone Caprock: In Manjiaer-Yingjisu Sag as an Example (Wancang Tan, Yuanlin Meng, Qiang Li, Hongjun Shao, Liang Zhao, Lijuan Wang et al.)....Pages 361-371
Prediction of Hydrate Formation and Decomposition in the Production of Water-Bearing Gas Reservoir in Deep Water (Na Wei, Wantong Sun, Yingfeng Meng, Jinzhou Zhao, Liehui Zhang, Haitao Li et al.)....Pages 372-388
Horizontal Well Technology for Tight Reservoirs with Coal Seams in the Fangzheng Fault Depression (Jingfeng Wu)....Pages 389-396
Reservoir Characteristics of Epimetamorphic Rock Gas Reservoir in Pingxi Area, Qaidam Basin (Zhiyuan Xia, Senming Li, Zhanguo Liu, Bo Wang, Yanqing Wang, Mei Xie)....Pages 397-409
Developing Coalbed Methane in Broken-Soft Coal Seam by Virtual Reservoir Horizontal Wells: A Case Study of Luling Field in Huaibei Mining Area, East China (Yaobo Xu)....Pages 410-421
Sensitivity Analysis and Stochastic History Matching of Shale Gas Production Based on Embedded Discrete Fracture Model (Xue Liang, Yujuan Wu)....Pages 422-438
Prediction of the Planar Distribution of Liquid-Rich Hydrocarbons in Duvernay Shale in the West Canadian Sedimentary Basin (Houqin Zhu, Yinchao Huai, Xiangwen Kong, Yuzhong Xing)....Pages 439-455
Analysis of Reservoir Formation Conditions of Gravity Flow Fan in Tadong (Liu Yang)....Pages 456-463
Introduction and Application of the Key Technology of Subsalt Reservoir Prediction in Jingbian Area (Ke-han Cai, Li Ma, Na Zhang, Jun Zhu)....Pages 464-470
Experimental and Numerical Study on Drag Reduction Performance of Slickwater in Turbulent Pipeflow (Fan Fan, Fujian Zhou, Zhiyu Liu)....Pages 471-484
Seismic Application in Australia Bowen Basin CBM Well Drilling and Development Well Placement (Ming Li, Yuxia Ma, Xiangwen Kong, Zhaohui Xia, Houqin Zhu)....Pages 485-494
Reserves Evaluation, Reporting and Sensitivity Analysis of Tight Gas Project Under Royalty & Tax System in British Columbia, Canada (Guifang Fa, Zuoqian Wang, Qian Zou, Dechao Cai, Zhiyu Li)....Pages 495-506
A Case Study of Upscaling Extra-Fine Coalbed Methane Geological Model (Lijiang Duan, Zhaohui Xia, Liangchao Qu)....Pages 507-521
The Challenges and Key Technology of Drilling Safety in the Area of the Arctic (Yongqi Ma, Jin Yang, Pengtian Feng, Can Zhang)....Pages 522-532
Spectral Shaping Technology and its Application for Dense-Gas Dessert Prediction on Songliao Basin (Hong-wei Deng, Yi Bao, Jiang-yun Pei, Hui-tian Lan, Ji-feng Ding)....Pages 533-545
Study on the Optimization of Fractures Layout in Horizontal Wells of Tight Gas Reservoirs (Zhaozhong Yang, Qian Chen, Xiaogang Li)....Pages 546-559
Shale Gas Potential of Goldwyer Formation in Canning Basin, Australia (Wenguang Zhao, Yuxia Ma, Houqin Zhu)....Pages 560-572
Evaluation Method of Shale Oil Reservoirs Fracability—A Case from Seventh Member of Triassic Yanchang Formation in Ordos Basin 2018 IFEDC (L. B Dou, H. Gao, R. Wang, K. Zhao)....Pages 573-587
High-Precision Magnetic Anomaly and Geological Significance of Shale Gas in Upper Yangtze Region 2018 IFEDC (Wendao Qian, Taiju Yin, Xuesen Li, Jianping Qian, Guowei Hou, Miao He)....Pages 588-600
Research and Application of Unconventional Gas Wellsite Ground and Underground Integration System (Heng-bin Wang)....Pages 601-610
Sediments Evolution of Napo Formation in the Slope Belt of Oriente Basin—A Case Study of Block T (Chao-qian Zhang, Wen-song Huang, Shi-yao Lin, Ke-xin Zhang, He-ping Chen, Zheng Meng et al.)....Pages 611-623
Numerical Simulation of Deformed Medium on In Situ Upgrading of Oil Shale via Steam Injection (Yang Zheng, Guanglun Lei, Chuanjin Yao, Shufeng Pei, Long Wang, Xin Zhang)....Pages 624-631
The Oil and Water Separation from Surfactant Produced Water by Using a Flotation Column (Ku Esyra Hani Ku Ishak, Mohammed Abdalla Ayoub)....Pages 632-642
A Novel Method to Evaluate the Well Pattern Infilling Potential for Water-Flooding Reservoirs (Jinde Feng, Wei Tang, Ting Liu, Donghui Wang, Yajie Tian, Jianzi Shi et al.)....Pages 643-650
Innovative Application of Big Data Technology in Southwest Pipeline Information System (Heng-Bin Wang, Dong-Chao Liu, Yan Meng)....Pages 651-657
Optimizing the Development Strategy for the Block Faulted Oil field with Merak Capital Planning (Zuoqian Wang, Guifang Fa, Weina Jiang, Jun Lan, Bin Zhao)....Pages 658-668
The Study on Portfolio Optimization Methods for Overseas Petroleum Development Projects (Wei-na Jiang, Liang Wei, Qian Liu, Xi Chen, Zuo-qian Wang)....Pages 669-684
Smart Oilfield Technology (Dianfa Du, Xue Zhang, Qiaoqiao Guo, Bin Zhang, Genkai Zhang)....Pages 685-694
Driving Force Analysis of Sandstone Reservoirs with Strong Natural Aquifer (Zhanxiang Lei, Jian Liu, Jian Li, Likun Xu, Lihong Fan, Yunbo Li et al.)....Pages 695-704
CO2 Sequestration Electromagnetic Imaging Based on Nanoparticle Contrast Agent and Casing Excitation (Weiqin Li, Zaiping Nie, Wenhe Xia)....Pages 705-712
Experimental Study of Transient Electromagnetic Resistivity Logging Through Casing (Si-hui Liu, De-fu Zang, Fu-ming Zhang, Yu-ke Huang)....Pages 713-722
Study on Centrifugal Pump Rotor Fault Feature Extraction Based on Fractal Theory (Wencai Liu, Qiyong Peng)....Pages 723-735
Research and Development of B/S-Based Data Mining System for Petroleum Information (Qian Zhang, Shiyun Mi, Xinchao Liu)....Pages 736-744
Different Tapping Solutions for Remaining Oil in Sandstone Oil Field at Ultrahigh Water Cut Stage (Jian Liu, Zhan Xiang Lei, Li Kun Xu, Jian Li, Yun Bo Li, Zhao Peng Yang et al.)....Pages 745-756
New Dynamic Multi-factor Economic Limit Well Pattern Density Calculation Method Based on Single-Well Limit Control Reserves (Hongwei Wang, Haibo Liu, Xianbao Zheng, Zhiguo Miao, Jibin Wang, Wei Yan et al.)....Pages 757-769
A Numerical Well Test Model in Multi-media Carbonate Reservoirs and Its Application (Fangfang Chen, Zhiwen Ding, Meichun Yang, Jing Liang, Jian Zhang, Wen Cao)....Pages 770-781
Mechanism of Hydrocarbon Migration of Paleozoic Clastic Rocks in Western Section of the Tabei Uplift, Tarim Basin: YM34 Silurian Accumulations as a Case (Wensheng Guan, Ming Zha, Ting Li, Jiangxiu Qu, Fei Li, Liping Deng et al.)....Pages 782-797
Prediction on Basement Fracture in Jambi Depression, South Sumatra Basin, Indonesia (Guangcheng Hu, Xiangwen Kong, Yuxia Ma, Houqin Zhu, Ming Li, Guoliang Hong)....Pages 798-809
Diagenetic Simulation of Paleogene Clastic Reservoir Based on Diagenesis in Bozhong Depression, China (Wendao Qian, Taiju Yin, Changmin Zhang, Guowei Hou, Miao He, Min Xia)....Pages 810-821
Reserves Estimation of Two-Layer Commingled Gas Well by Material Balance Method (Sun Hedong, Cui Yongping, Cao Wen, Li Yanchun)....Pages 822-827
A New Identification Method and Its Application on Asphaltic Zones In Bioclastic Limestone Reservoir: A Case Study of Ru3 Reservoir of AA Field, Middle East (Zhong-yuan Tian, Rui Guo, Li-ping Yi)....Pages 828-840
Applied Research and Well Interference Test Model of Ultrahigh Pressure Gas Reservoir of Keshen Gas field (Hongfeng Wang, Yinglin Jia, Songbai Zhu, Xia Qiao, Shengjun Wang, Yanbo Nie)....Pages 841-850
A Case Study of Subsurface Uncertainty Analysis in Modelling Carbonate Reservoir (Yong Yang, Ming Zhang, Aifang Bie, Jietang Lv, Wenqi Zhang, Zehong Cui et al.)....Pages 851-864
Research and Application of the Evaluation System for a Complex Fault Block Sandstone Condensate Gas Reservoir (Xiaoling Zhang, Wei Ding, Yunpeng Hu, Xiaoyan Liu)....Pages 865-872
Transient Pressure Analysis in Partially Perforated Vertical Wells (Weiping Ouyang, Deyong Yang, Hedong Sun)....Pages 873-891
A Method of Favorable Source Rock Evaluation and Prediction: A Case Study From Zhahaquan Oil Field, Qaidam Basin (Nw China) (Mingzhi Tian, Zhanguo Liu, Zhiyuan Xia, Yanqing Wang, Senming Li, Guangyong Song et al.)....Pages 892-900
Characterization and Modeling of Fractures in the Bereketli-Pirgui Carbonate Reservoir, The Right Bank of the Amu Darya (Xing Yuzhong, Guo Chunqiu, Cheng Muwei, Shi Haidong, Zhu Houqin, Chen Pengyu)....Pages 901-915
Time Matching and Its Control Effect on Gas Migration and Accumulation Period of Caprock, Source Rock, and Fault in Ed Formation of X sag (Chen Haibin, Chen Xuehai, Song Jing, Yang Zhisheng, Cheng Zhiyong, Yang Jingfang et al.)....Pages 916-925
Logging Identification of Asphaltenes in Carbonate Reservoirs—Taking the Case of the Halahatang Oil Field as an Example (Chen Lixin, Yang Haijun, Cheng Hanlie, Yang Wenming, Gao Chunhai, Qi Dianqing et al.)....Pages 926-931
Effect of WaterFlooding Speed on Water–Oil Displacement Efficiency of Homogeneous Core (Xiangzhong Zhang, Lun Zhao, Jincai Wang, Li Chen, Xiangan Yue)....Pages 932-937
Fractal Distribution of Paleotrough and Exploration Potential in Ordos Basin (Xunxun Fu, Huitao Zhao, Daojun Huang, Yijun Fan, Yani Jia, Lei Sun et al.)....Pages 938-945
Predicting Recovery Factor and Waterflooding Performance by History Variables in Waterflooding Reservoirs (Libing Fu, Jun Ni, Zifei Fan, Xuanran Li, Lun Zhao)....Pages 946-958
Geological Characteristics and Production Performance of Ultra-Deep Naturally Fractured Tight Sandstone Gas Reservoirs (Ruilan Luo, Yongzhong Zhang)....Pages 959-972
Analysis of Pore Characteristics of Reservoir Rock Based on CT Scanning—Taking the Tazhong Block of Tarim Basin as an Example (Ying Guo, Yong Yang, Guangying Ren, Jinlong Ni, Hanlie Cheng)....Pages 973-984
Identification of Interwell Interference Based on Production Dynamics (Hailong Zuo)....Pages 985-991
Integration of Two-Dimensional Map into Three-Dimensional Model: A New Sand Body Modeling Approach for Delta Reservoir (Xintao Yuan, Cheng Lei, Qingyan Xu)....Pages 992-1003
Investigation on Characteristics and Affecting Factors of Water Cut in Planar Thief Zone (Xudong Shen, Xinwei Liao, Aixian Huang, Jufeng Xue, Xiongtao Shang)....Pages 1004-1017
High-Resolution Sequence Stratigraphy and Subtle Reservoir Characterization Analysis: A Case Study from the Qingshankou Formation in Southern Songliao Basin (Minghui Liu, Ziming Hou, Li Chen, Hongwen Deng)....Pages 1018-1031
Description Technology of Fractured-Vuggy Carbonate Reservoir in Halahatang Oil field, Tarim Basin—Take the Ha 7 Test Area as an Example (Lixin Chen, Zhenbiao Wang, Lijuan Zhang, Hanlie Cheng, Dianqing Qi)....Pages 1032-1042
A Systematic Workflow to Determine the Distribution of Original Oil and Gas and Residual Oil and Gas in N Gas Condensate Field (Ming Zhang, Hongjun Wang, Jietang Lv, Yong Yang, Yunpeng Hu, Zhaohui Xia et al.)....Pages 1043-1054
New Identification Method of Sedimentary Microfacies of Carbonate Rocks: A Case Study of Carboniferous KT-II Layer on West Slope, in the Central Block of Caspian Basin (Shuang Liang, Man Luo, Jiquan Yin, Yankun Wang, Shanbo Sheng, Shutang Jin)....Pages 1055-1065
Research on Reasonable Water Injection Parameters of Water Flowing Barrier to Delay Bottom Water Coning (Ying Fu, Zheng-jun Zhu, Chao Zhang, Tao Shi, Hui Ma, Kai Feng)....Pages 1066-1072
Reservoir Characterization of Qadirpur Gas Field, Central Indus Basin, Pakistan (Waqar Ahmad, Xianlin Ma, Fakhar ul Islam)....Pages 1073-1081
Reservoir Prediction of the Reef of the Cambrian Platform Margin Area in the Gucheng of Tarim Basin (Wei Xu)....Pages 1082-1088
Seismic Geomorphology of the LTAF Formation in JB Block, South Sumatra Basin (Houqin Zhu, Guoliang Hong, Yuxia Ma, Guangcheng Hu, Zhenhua Bai)....Pages 1089-1099
Seismic Motion Inversion Study on Prediction of Interbedded Thin Beds (Wei-wei Liu, Chun-lin Xie, Jiu-zhan Hu, Meng Tian, Chao Wang, Jing Sun)....Pages 1100-1108
Fan Delta Sedimentary Characteristics (Tianjian Sun, Fang Xu, Zheng Meng)....Pages 1109-1118
Uncertainty Analysis of Sedimentary Microfacies Modeling on Hancha Block in Chang Guanmiao Oilfield (S. W. Pan, Z. T. Xue, M. M. Zhang)....Pages 1119-1129
Fracture Prediction of Thin Carbonate Reservoir Based on Wide-Azimuth Seismic Data (Zhen Wang, Junzhang Zheng, Yankun Wang, Jiquan Yin, Man Luo, Shuang Liang)....Pages 1130-1136
Study on Coal Forming Process and Coal Seam Distribution Controlled by the 4th-Order Sequence—A Case Study of T Block, the South Turgay Basin, Kazakhstan (Wei Yin, Jiquan Yin, Mingjun Zhang, Man Luo, Xiaofeng Sheng, Jianjun Guo et al.)....Pages 1137-1147
A New Thought on Identification of Reef Shoal and Carbonate Sedimentary Environment Under Salt Gypsum Rocks—A Case Study in the Central Block of Amu Darya Right Bank (Liangjie Zhang, Xingyang Zhang, Hongjun Wang, Tongcui Guo, Xinglin Gong, Youheng Leng et al.)....Pages 1148-1160
Productivity Analysis of Commingling Production of a Multiple-Channel Reservoir with Closed Boundary by a Horizontal Well (Wen-qi Zhao, Lun Zhao, Shu-qin Wang, Meng Sun, Ming-xian Wang, Hao Su et al.)....Pages 1161-1170
Study on Comprehensive Modeling of Reservoir Based on Process Control (Da Cheng Wang, Zhi Wei Chen, Xiao Chen Liu, Yu Zhang, Xin Kai Cui, Jun Lin)....Pages 1171-1179
Stochastic Simulation of Lithology Distribution Constrained by Stratigraphic Forward Modeling and Seismic Inversion: A Case Study of A Oilfield in Ecuador (Kexin Zhang, Xuepeng Wan, Quan Hu, Heping Chen, Hong Huo, Shiyao Lin et al.)....Pages 1180-1192
Sedimentary Microfacies of M1 Sandstone Reservoir in the D-F Oil Field (Tianyu Zhang, Jinxiu Yang)....Pages 1193-1207
Effective Quantification and Applications of Seismic Attributes (Changjiang Fan, Tianwei Zhou, Tiezhuang Wu)....Pages 1208-1217
Fewer Well with Higher Production Pattern Development of Metamorphic Reservoirs (M. Q. Chen, J. He, L. Ren, W. B. Yang)....Pages 1218-1228
The Simulation Method Research of Hydraulic Fracture Initiation with Perforations (Haifeng Fu, Fengshou Zhang, Dingwei Weng, Yunzhi Liu, Yuzhong Yan, Tiancheng Liang et al.)....Pages 1229-1240
Research on Key Techniques of Offshore Heavy Oil Production Based on Distributed Electro-Acoustic Efficiency (Guowang Gao, Dan Wu, Dasen Hou, Dawei Yu)....Pages 1241-1250
Research and Application of Oil Recovery Recyclable Clean Fracturing Fluid (Zefeng Li, Mian Zhang, Yan Gao, Zuwen Wang, Jianping Lan, Xiaohong Bao)....Pages 1251-1263
Post-flooding with Associative Polymer/Alkali/Surfactant Ternary System After Polymer-Enhanced Oil Recovery (P. H. Han, R. B. Cao, H. S. Liu, W. Yan, L. Yang, F. Luo et al.)....Pages 1264-1274
Study on the Effect of Reservoir Heterogeneity on Air Foam Flooding (Hua Hua Li, Shu Man Li, Xiao Bing Lu, Jing Hua Wang, Wen Biao Duan)....Pages 1275-1289
Laboratory Study of the Petrophysical Effect of Natural Fractures on Gas Flow Through Naturally Fractured Tight Cores (Hong-yan Qu, Jia-wei Hu, Fu-jian Zhou, Yan Peng, Zhe-jun Pan)....Pages 1290-1297
Design and Field Application of a Composite Microbial Flooding Process for a High-Water-Content Oilfield (Long Ren, Mingqiang Chen, Baoge Cao, Bing Li, Xue Li, Nan Zhang et al.)....Pages 1298-1310
Water Cut Changing Rules After Liquid Rate Increasing in Strongly Heterogeneous Reservoirs (Renfeng Yang, Jinqing Zhang, Han Chen, Sheng Guo, Jiawei Tang, Jing Li)....Pages 1311-1329
Stress Analysis of Sand Particles in Separators in Downhole Oil/Water Separation and Reinjection System Based on Coupled CFD-DEM (Yan Zhang, Minghu Jiang, Yong Zhang, Lei Xing, Youbin Chen)....Pages 1330-1342
New Method for Analysis of Shearing Fracture in Unconventional Reservoirs (Zi-wei Zhang, Xiang-yi Yi, Xia Wu, Yuan-qin Wu, Qin Li)....Pages 1343-1352
Laboratory Evaluation on Air-Assisted Steam Stimulation in Common Heavy Oil Reservoir (Zhao Qinghui, Liu Qicheng, Leng Guangyao, Peng Xu)....Pages 1353-1362
Development of Remote Well Opening Equipment Based on Electric Needle Valve in Sulige Gas Field (Yong Chen, JiE Gui, Zhengyan Zhao, Shuangquan Liu)....Pages 1363-1369
Properties of Surfactant Solution for Foam-Flooding (H. S. Liu, G. Chen, R. B. Cao, P. H. Han, C. S. Lv, S. L. Guo et al.)....Pages 1370-1380
Experimental Study on CO2 Microcosmic Displacement of Core Flooding in Ultra-low Permeability Reservoirs, Ordos Basin (Yangnan Shangguan, Jiyong Zhao, Zhaoguo Li, Xinhui Lei, Weiliang Xiong, Shuman Li et al.)....Pages 1381-1388
Design of Oil and Gas Well Ground Manifold Connecting Aid (Yanchao Sun, Mingxue Chen, Shengming Huang, Yue Su, Qibing Wang, Yichang Zhang)....Pages 1389-1395
Optimization Design of Drilling Speed in Sulige Gas Field (Yanchao Sun, Yue Su, Shengming Huang, Yichang Zhang, Qibing Wang, Mingxue Chen)....Pages 1396-1405
Vertical Well and Wirtual Well Trajectory Control Colume Theoretical Research (Yanchao Sun, Chengcheng Niu, Zongxi Bai, Lizhi Su)....Pages 1406-1414
Reservoir Prediction and Its Applications in Identification of Stratigraphic Traps in Fula3D Area, Muglad Basin, Sudan (Quan Zou, Aixiang Liu, Fengyun Zheng, Yanli Shi, Weili Ke)....Pages 1415-1421
Effect of Packer on the Fracture Initiation in Open-Hole Horizontal Well (H. X. Xu, Z. W. Wang, M. Zhang)....Pages 1422-1433
An Integrated Petrophysics and Geomechanics Method for Fracability Evaluation in Tight Sandstone Reservoirs: A Case Study in the Yingcheng Formation, Jinshan Gas Field, Songliao Basin, China (Zhaozhong Yang, Rui He, Xiaogang Li, Ziyuan Liu, He Huang, Zhuang Deng)....Pages 1434-1452
Optimization Design and Application of Vortex Drainage Gas Recovery (M. Cai, W. H. Ma, P. G. Ma, J. Q. Wang, J. L. Li, N. Li et al.)....Pages 1453-1462
Design of a Magnetic Memory Detecting Sensor for Oil Well Casing Well Damage (Sun Bingcai, Chu Shengli)....Pages 1463-1471
Study on Tensile Test Elongation Variation Law for High-Strength Steel Material (X. F. Xu, X. J. Zhao, Y. F. Ai, M. H. Liang, H. J. Zhang)....Pages 1472-1478
Optimization Model of Horizontal Wells with ICD Water Control Completion in Bottom Water Reservoirs (Fachao Shan, Shijun Huang, Congge He, Lun Zhao, Anzhu Xu)....Pages 1479-1487
A New Temporary Blocking Fracturing Design for Efficiently Activating Natural Fractures of HPHT Fractured Thick Sand Reservoir (Xiu-ling Han, Ying Gao, Juan Jin, Kan Sun, Yang Shi, Xue-fang Yuan et al.)....Pages 1488-1498
Deep Penetrating Horizontal Drilling Techniques Status Quo Analysis (Yu Han, Shao-gong Zhu, Feng-shan Wang, Fu-min Liang, Hai-cheng Li, Qing-zhong Li et al.)....Pages 1499-1507
Research and Application of Intelligent Separate Layer Production Technology for Producers (Shujin Zhang, Lin Li, Jing Chen, Li Ban, Jiali Chen, Hongyan Zhang et al.)....Pages 1508-1517
Study on Sensitivities of Numerical Simulation Parameters in SP Flooding (Shuman Li, Huahua Li, Yangnan Shangguan, Lei Fang, Wei Fan, Jinlong Yang et al.)....Pages 1518-1526
Water-Out Characteristics and Remaining Oil Distribution of Delta Front Reservoir—Take J-2C Reservoir of Kalamkas Oilfield in Kazakhstan as an Example (Xuanran Li, Rongrong Jin, Libing Fu, Bifeng Xu, Zihan Zhang)....Pages 1527-1535
Development of a New Type Two-Stage Cutting Composite Bit (Yanchao Sun, Yichang Zhang, Qibing Wang, Yue Su, Shengming Huang, Mingxue Chen)....Pages 1536-1546
A Parameter Design Method of Gas Lift Technology for Production Recovery and Application to a Water-flooded Gas Well (H. T. Zhang, Y. P. Zhang, Z. S. Yang, M. Cai, P. G. Ma, N. Li et al.)....Pages 1547-1556
Research and Application of Borehole Stability Mechanism in the Deep Sand-mudstone Formation (Dongjie Li, Yuhao Wei, Changzhu Liu, Hongyan Ma, Jinsheng Yang, Zhaohai Yin)....Pages 1557-1572
Numerical Simulation of Lateral Drilling Horizontal Well Flow Lines in High-Hydrocarbon Reservoirs (Du Dianfa, Guo Qiaoqiao, Zhang Xue, Zhang Bin)....Pages 1573-1581
Study and Application of Temporary Plugging and Acidization in Water Injection Well (Fei Chen, Xin Rong Zhong, Long Chai)....Pages 1582-1590
Influence of Well Pattern on in situ Stress Filed of Shale Reservoir (Li Shuai, Chen Junbin, Li Yu, Liu Jing)....Pages 1591-1603
A Review of Techniques for Enhancing Oil Recovery by EM and US Wave (Muhammad Ismail, Guowang Gao, Iqbal Sajid, Yongchao Wang)....Pages 1604-1615
A Study on Reasonable Injection-Production Network in Tahe Oil field Fractured Reservoir (Jie He, Long Ren, Mingqiang Chen)....Pages 1616-1624
Visualized Experiment on Critical Cutting Transport Behavior of Annular in Horizontal Well Section (Wei Song, Yan Zhou, Kuanliang Zhu, Zhongzhi Hu, Ji Xu)....Pages 1625-1635
The Stability Experimental Method and Friction Reduction Method Discussion of Emulsified Acid (Liwei Wang, Xiaohui Qiu, Yuting Liu, Minjie Xu)....Pages 1636-1644
Evaluation of β-Cyclodextrin Dimers/Amphiphilic Polymer Inclusion Complexation in Enhanced Oil Recovery (Yanfeng Ji, Xulong Cao, Lanlei Guo, Yangwen Zhu, Hui Xu)....Pages 1645-1652
Distribution of Microscopic Remaining Oil After ASP Flooding in Saertu Oilfield in Daqing (Y. J. Liang, Z. A. Li, J. Li, X. D. Sun)....Pages 1653-1662
Studies on EOR of Sandstone Oilfield with Low Viscosity and High Salinity During High Water Cut Stage—A Case Of Kumkol Oilfield in Kazakhstan (Li Chen, Lun Zhao, Haili Cao, Jincai Wang, Wenqi Zhao, Libing Fu et al.)....Pages 1663-1683
Electromagnetic Response Characteristics of Local Conductors with Pseudo-random Coded Waveforms (Xijin Song, Xuelong Wang, Peng Li)....Pages 1684-1705
Multi-Stage Intelligent Throughput Test of Horizontal Wells in Jiyu Oilfield (Wei Wang, Xiang-jun Wei, Jian-zhong Zhang, Xiao-e Wang)....Pages 1706-1715
Design of De-oiling Separator Based on Oil Droplets Migration Trajectory (Lei Xing, Minghu Jiang, Yong Zhang)....Pages 1716-1727
Development Strategy for Gas Cap Reservoirs with Edge Water and Complicated Faults in Niger (Qingyan Xu, Cheng Lei, Xintao Yuan, Xuanyu Yang)....Pages 1728-1733
A Novel Separate Layer Injection Technique for Polymer Flooding in Daqing Oil Field (Shao-gong Zhu, Wang-fu Zhou, Chong-jiang Liu, Xing-liang Song, Hai-cheng Li, Guang-lei Gao et al.)....Pages 1734-1743
Self-excited Rotating Magnetization Field Ranging for SAGD Dual Horizontal Well (P. Wu, Z. Y. Guo, W. Xu, Y. X. Zhou, Z. X. Liu)....Pages 1744-1752
Application of Electro Thermal Technology in Heavy Oil Production Testing (Zeng Qinghui)....Pages 1753-1758
Intelligent Judgment of Risks While Gas Drilling (Haitao Li, Na Wei, Anqi Liu, Wantong Sun, Lin Jiang, Yang Liu et al.)....Pages 1759-1777
A Design of Magnetic Memory Sensor of Oil Well Casing Damage Detection (Bingcai Sun, Shengli Chu, Jianchu Fan, Fangfang Ding)....Pages 1778-1787
Application of Conformal Coring Tool in Complex Formation of Block Structure (Jing Liu, Junbin Chen, Yu Li, Shuai Li, Nannan Ren)....Pages 1788-1795
A Transient Well Test Method for Wellhead Pressure Fall-Off Test After Acid Fracturing (Hanlie Cheng, Lianshan Wang)....Pages 1796-1806
Development and Application of Visual Logging Equipment (Zhengguo Yan, Qingping Luo, Xiangxiu Zheng, Jiatian Zhang)....Pages 1807-1815
Development Strategy Study Based on Improved Analytic Hierarchy Process for Complex Fault Block Oil Reservoirs (Cheng Lei, Qingyan Xu, Xintao Yuan, Chujuan Kang, Xuanyu Yang, Jiaofen She)....Pages 1816-1830
Experiment for Acquiring the Secondary Field About Formation Information in a Cased Well Model (Shouwei Zhang, Defu Zang, Shuqin Liu, Hongna Jiang)....Pages 1831-1840
Influence of Swirl Vane on the Low-Pressure Gas Flow in Supersonic Separators (Jiang Bian, Xuewen Cao, Yang Liu, Yuan Sun, Qi Chu)....Pages 1841-1849
An Unconventional Method to Separate Carbon Dioxide from Wellhead Natural Gas (Jiang Bian, Xuewen Cao, Yuan Sun, Wenming Jiang, Qi Chu)....Pages 1850-1859
Study on Wellbore Relative Humidity of Gas Drilling in Condition of Formation Water (Haitao Li, Na Wei, Anqi Liu, Wantong Sun, Lin Jiang, Hanming Xu et al.)....Pages 1860-1873
Detection Optimization of Single-Axis Magnetic Anomaly Sensor for Pig Clog Locating (W. Xu, Z. Y. Guo, P. Wu, Z. X. Liu)....Pages 1874-1884
Wellbore Temperature Field Prediction in Marine Drilling (Na Wei, Wantong Sun, Yingfeng Meng, Jinzhou Zhao, Liehui Zhang, Haitao Li et al.)....Pages 1885-1900
System Reliability Evaluation for Complex Deep Well Casing Based on Structural Reliability (H. Fan, P. Wang, X. J. Zhao, M. Liu, X. Zh. Yan, Y. R. Feng)....Pages 1901-1913
Research and Application of Electronic Control Intelligent Oil Recovery Technology in Horizontal Well (Long Wang, Dekui Xu, Nan Li, Xiaoyu Xu, Renyong Liu, Jiyang Zhang et al.)....Pages 1914-1919
Aerated Drilling Fluids Used for Geothermal Wells (Esaie Kuadjovi, Michelle Djuidje, Irene Kongwa, Janet Timana, Vito Mitoukou)....Pages 1920-1933
Experimental Confirmation of the Existence of the Lag in the Hydraulic Fracture (M. A. Trimonova, E. V. Zenchenko, P. E. Zenchenko, S. B. Turuntaev, N. A. Baryshnikov)....Pages 1934-1942
Advanced Technologies Used in Sand Control Completion (Ismael W. Friki, Ndakolo J. Haiduwa, Andrew J. Magoti, Gervas Dotto, Jackeline P. Kimune, Albert K. Kissima)....Pages 1943-1964
Distributed Vibration and Temperature Measurement for Oil Well Based on Continuous Fiber Bragg Grating Array (Zhihui Mei, Jianguan Tang, Chengli Li, Kun Yang, Minghong Yang)....Pages 1965-1973
Application of Discrete Fracture Network Model in the Simulation of Massive Fracking in Tight Oil Reservoir (Shuai Li, Xin Wang, Bo Cai, Chunming He)....Pages 1974-1983
Experimental Study on Fracture Propagation of Liquid CO2 Fracturing in High-Rank Coal Rock (Yuanzhao Jia, Xi Yu, Donghe Yu, Guohua Liu, Mengmeng Ning, Hang Che)....Pages 1984-1993
Sedimentary Microfacies Analysis and Reservoir Characterization of the Middle Jurassic Carbonates: A Case Study from Lower Indus Basin, Pakistan (Bilal Wadood, Sajjad Ahmad, Suleman Khan)....Pages 1994-2000
Study on the Current Situation and Influencing Factors of Casing Damage in S Oilfield (Yimin Pan)....Pages 2001-2006
Research on Identification Method of Dominant Seepage Flow Channel of Fractured Horizontal Wells in Tight Oil Reservoir Based on Fuzzy Synthetic Evaluation Model (Wenhao Cui, Wendong Yang, Cheng Jing, Yihua Wang)....Pages 2007-2024
Experimental Research on Corrosion Resistant Rubber Based on Supercritical CO2 Injection Process (Zhongchao Lin, Jiang Sun, Lichuan Zhao, Qing He, Hao Xu)....Pages 2025-2033
Back Matter ....Pages 2034-2041

Citation preview

Springer Series in Geomechanics and Geoengineering

Jia’en Lin Editor

Proceedings of the International Field Exploration and Development Conference 2018

Springer Series in Geomechanics and Geoengineering Series Editor Wei Wu, Universität für Bodenkultur, Vienna, Austria e-mail: [email protected]

Geomechanics deals with the application of the principle of mechanics to geomaterials including experimental, analytical and numerical investigations into the mechanical, physical, hydraulic and thermal properties of geomaterials as multiphase media. Geoengineering covers a wide range of engineering disciplines related to geomaterials from traditional to emerging areas. The objective of the book series is to publish monographs, handbooks, workshop proceedings and textbooks. The book series is intended to cover both the state-ofthe-art and the recent developments in geomechanics and geoengineering. Besides researchers, the series provides valuable references for engineering practitioners and graduate students. ** Now indexed by SCOPUS, EI and Springerlink**

More information about this series at http://www.springer.com/series/8069

Jia’en Lin Editor

Proceedings of the International Field Exploration and Development Conference 2018

123

Editor Jia’en Lin College of Petroleum Engineering Xi’an Shiyou University Xi’an, Shaanxi, China

ISSN 1866-8755 ISSN 1866-8763 (electronic) Springer Series in Geomechanics and Geoengineering ISBN 978-981-13-7126-4 ISBN 978-981-13-7127-1 (eBook) https://doi.org/10.1007/978-981-13-7127-1 © Springer Nature Singapore Pte Ltd. 2020 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore

Contents

The Nonlinear Flow Analytical Model and Its Field Use . . . . . . . . . . . Hongbing Jia, Baoquan Song, Wei Mao, Zhijing Bao, PengJu Du, Yaguang Li, Lijun Yang, and Yingmei Shao

1

Research on Low Damage Drilling Fluids and Application in Low Permeability Reservoirs of Shengli Oilfield . . . . . . . . . . . . . . . . . . . . . . J. Y. Liu, E. D. Chen, and X. L. Li

11

Multistage Fractures Optimum of Different Cluster Wells in Tight Gas Reservoirs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Shihua Liu

24

Deliverability Evaluation on Horizontal Well with DHC in Tight Sandstone Gas Reservoir . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Yundong Xu, Zhen Sun, Liangrong You, Long Chen, Liu He, Shunzhi Yang, and Yilin He The Integration of Checking Seal and Testing Regulation of Bridge Concentric Layered Water Injection Technology Research and Application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Lingzhi Yang, Jiuzheng Yu, Bin Yao, Yanqing Liu, Changlong Yu, and Fuwei Bi Permeability and Viscosity Index Range Estimation of Imbibition Agent Suitable for Low-Permeability Reservoir . . . . . . . . . . . . . . . . . . Yi Zhang, Jianguo Li, Fangge Gong, Yun Sun, Haihui Chen, Hongyan Cai, and Hongfu Fan Influence of Low-Frequency Vibration Acceleration on the Permeability of Low Permeable Porous Media During Water Flooding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Liming Zheng, Wenhao Cui, Jing Liu, and Lei Zhang

42

48

56

74

v

vi

Contents

Long Horizontal Section Well Application in Developing Ultra-Low Permeability Layer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Baixue Chen Performance Evaluation and Optimization of Temporary Plugging Agent Used in Diverting Fracturing . . . . . . . . . . . . . . . . . . . . . . . . . . . Haiyang Ma, Qingzhi Wen, Mingliang Luo, Tingting Yu, Gang Lei, Xiaofei Duan, and Liu Yang Investigation on Productivity and Affecting Factors of Low Permeability Reservoir Using Radial Water Jet Drilling . . . . . . . . . . . Xudong Shen, Xinwei Liao, Xiaoliang Zhao, Xiongtao Shang, and Weiyun Luo

87

95

108

Research and Application of Dual Packer Multistage Control Fracturing Technology in Horizontal Wells . . . . . . . . . . . . . . . . . . . . . Jinyou Wang

119

Discussion on the Technical Countermeasures of Hechuan Xujiahe Gas Reservoir Development . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Qinglong Xu, Yongzhuo Wang, Xuemin Zhou, and Ping Shu

129

Study on Areal Sweep Coefficient Under Water Flooding in Ultra-Low Permeability Reservoirs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . He Congge, Xu Anzhu, Zhao Lun, and Fan Zifei

140

Dynamic Fracture and Matrix Heterogeneity and Remaining Oil Models of Ultra-Low Permeability Reservoir . . . . . . . . . . . . . . . . . . . . Li Liu, Youjing Wang, and Jiahong Li

153

Production Analysis Method Based on Material Balance Pseudo-time for Water Production Gas Wells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Jianning Luo, Yanyan Sun, Bo Zhang, Jun Yue, and Minghui Huo

171

A Drilling Rate Model for Roller Cone Bit with Experimental Verification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Li Wei, Li Bing, Sun Wenfeng, Li Siqi, and Zhao Huan

181

Analysis of Inversion Structure and Trap Diversity in a Block of Western Qaidam Basin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Wang Guihong, Chen Zhiyong, Zhou Chuanmin, Lv Jietang, Zhang Ming, and Wang Dianao Rock Fracture Analysis Method in Drilling Operation . . . . . . . . . . . . . Zhaomei Xue Analysis of the Influence Factors of Casing Damage Based on Data Mining . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Shujuan Zhang, Xueqing Zhang, Wenchang Fu, Jin Zhang, Liqiu Zhang, Qinghong Liu, and Lihong Zhu

191

203

212

Contents

vii

Application of Geostatistical Inversion to Thin Reservoir Prediction in the Indonesian Project . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C. L. Li, D. M. Li, and H. Q. Zhu

222

The Research on Teeth Invade Bottom-Hole Rock Basing on Unified Strength Theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Li Wei, Zhao Huan, Li Siqi, and Ling Xin

236

Carbon Dioxide Corrosion on Casing Under High-Temperature and High-Pressure Conditions in Deep Wells . . . . . . . . . . . . . . . . . . . . Jingfu Zhang, Shuai Shao, Shuting Wang, Wenhui Xiao, and Ziyang Lin

247

Calculation Model of Rock Fracture Pressure Under Multifield Coupling Action . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Zhao Xiaojiao, Qu Zhan, Xu Xiaofeng, Yu Xiaocong, and Fan Heng

261

Experimental Study on Pore Structure Damage of Bedding Shale Under Ultralow Temperature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Zhongying Han, Yuanfang Cheng, and Huaidong Wang

274

Simulation on Formation Mechanism of Qiongdongnan Basin . . . . . . . Liu Xinlu, Li Zian, Liang Yingjie, and Ma Teng Prediction of Gas-Bearing Properties of Compact Sandstone Based on Avo-Analyzed Attribute Variance . . . . . . . . . . . . . . . . . . . . . Mingbo Bi, Yijun Zhou, Yadong Zhang, and Yu Lei Study on Reservoir Properties’ Varying Laws and Production Features of CBM Wells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Qing Feng, Miao Tian, Zijun Huang, Ming Zeng, Tao Wang, Wanchun Zhang, Xuxing Wang, and Juan Wang The Mathematical Analysis of Temperature-Pressure-Adsorption Data of Deep Shale Gas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Hao Jingyuan, Li Dong, Zhang Xuemei, and Ma Qinghua A New Method for Flooded Layer Evaluation by Logging with Strong Heterogeneous in Heavy Oil Reservoirs, K Field, Central Asia . . . . . . Yaping Lin, Zhenhua Guo, Shanbo Sheng, Junzhang Zheng, Man Luo, and Hongwei Liang Evaluation of Shale Gas Resource Potential in Devonian–Carboniferous of Yaziluo Region . . . . . . . . . . . . . . . . . . . Yazhao Liu, Haijun Zhang, Yuru Xiao, and Hao Li Application and Characterization Technology of Cleat in Medium-Rank Coalbed Methane . . . . . . . . . . . . . . . . . . . . . . . . . . . Liangchao Qu, Zhaohui Xia, Lijiang Duan, Ming Zhang, Lingli Liu, and Kening Zheng

284

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Contents

Characteristics and Classification Evaluation of Tight Sandstone Caprock: In Manjiaer-Yingjisu Sag as an Example . . . . . . . . . . . . . . . Wancang Tan, Yuanlin Meng, Qiang Li, Hongjun Shao, Liang Zhao, Lijuan Wang, Na Jiang, and Yaguang Li Prediction of Hydrate Formation and Decomposition in the Production of Water-Bearing Gas Reservoir in Deep Water . . . . . . . . Na Wei, Wantong Sun, Yingfeng Meng, Jinzhou Zhao, Liehui Zhang, Haitao Li, Qingping Li, and Anqi Liu Horizontal Well Technology for Tight Reservoirs with Coal Seams in the Fangzheng Fault Depression . . . . . . . . . . . . . . . . . . . . . . . . . . . . Jingfeng Wu Reservoir Characteristics of Epimetamorphic Rock Gas Reservoir in Pingxi Area, Qaidam Basin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Zhiyuan Xia, Senming Li, Zhanguo Liu, Bo Wang, Yanqing Wang, and Mei Xie Developing Coalbed Methane in Broken-Soft Coal Seam by Virtual Reservoir Horizontal Wells: A Case Study of Luling Field in Huaibei Mining Area, East China . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Yaobo Xu

361

372

389

397

410

Sensitivity Analysis and Stochastic History Matching of Shale Gas Production Based on Embedded Discrete Fracture Model . . . . . . . . . . Xue Liang and Yujuan Wu

422

Prediction of the Planar Distribution of Liquid-Rich Hydrocarbons in Duvernay Shale in the West Canadian Sedimentary Basin . . . . . . . Houqin Zhu, Yinchao Huai, Xiangwen Kong, and Yuzhong Xing

439

Analysis of Reservoir Formation Conditions of Gravity Flow Fan in Tadong . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Liu Yang

456

Introduction and Application of the Key Technology of Subsalt Reservoir Prediction in Jingbian Area . . . . . . . . . . . . . . . . . . . . . . . . . Ke-han Cai, Li Ma, Na Zhang, and Jun Zhu

464

Experimental and Numerical Study on Drag Reduction Performance of Slickwater in Turbulent Pipeflow . . . . . . . . . . . . . . . . . . . . . . . . . . . Fan Fan, Fujian Zhou, and Zhiyu Liu

471

Seismic Application in Australia Bowen Basin CBM Well Drilling and Development Well Placement . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ming Li, Yuxia Ma, Xiangwen Kong, Zhaohui Xia, and Houqin Zhu

485

Contents

Reserves Evaluation, Reporting and Sensitivity Analysis of Tight Gas Project Under Royalty & Tax System in British Columbia, Canada . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Guifang Fa, Zuoqian Wang, Qian Zou, Dechao Cai, and Zhiyu Li

ix

495

A Case Study of Upscaling Extra-Fine Coalbed Methane Geological Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Lijiang Duan, Zhaohui Xia, and Liangchao Qu

507

The Challenges and Key Technology of Drilling Safety in the Area of the Arctic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Yongqi Ma, Jin Yang, Pengtian Feng, and Can Zhang

522

Spectral Shaping Technology and its Application for Dense-Gas Dessert Prediction on Songliao Basin . . . . . . . . . . . . . . . . . . . . . . . . . . Hong-wei Deng, Yi Bao, Jiang-yun Pei, Hui-tian Lan, and Ji-feng Ding

533

Study on the Optimization of Fractures Layout in Horizontal Wells of Tight Gas Reservoirs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Zhaozhong Yang, Qian Chen, and Xiaogang Li

546

Shale Gas Potential of Goldwyer Formation in Canning Basin, Australia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Wenguang Zhao, Yuxia Ma, and Houqin Zhu

560

Evaluation Method of Shale Oil Reservoirs Fracability—A Case from Seventh Member of Triassic Yanchang Formation in Ordos Basin 2018 IFEDC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . L. B Dou, H. Gao, R. Wang, and K. Zhao High-Precision Magnetic Anomaly and Geological Significance of Shale Gas in Upper Yangtze Region 2018 IFEDC . . . . . . . . . . . . . . Wendao Qian, Taiju Yin, Xuesen Li, Jianping Qian, Guowei Hou, and Miao He Research and Application of Unconventional Gas Wellsite Ground and Underground Integration System . . . . . . . . . . . . . . . . . . . . . . . . . Heng-bin Wang Sediments Evolution of Napo Formation in the Slope Belt of Oriente Basin—A Case Study of Block T . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Chao-qian Zhang, Wen-song Huang, Shi-yao Lin, Ke-xin Zhang, He-ping Chen, Zheng Meng, Yu-sheng Wang, and Fang Xu Numerical Simulation of Deformed Medium on In Situ Upgrading of Oil Shale via Steam Injection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Yang Zheng, Guanglun Lei, Chuanjin Yao, Shufeng Pei, Long Wang, and Xin Zhang

573

588

601

611

624

x

Contents

The Oil and Water Separation from Surfactant Produced Water by Using a Flotation Column . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ku Esyra Hani Ku Ishak, and Mohammed Abdalla Ayoub A Novel Method to Evaluate the Well Pattern Infilling Potential for Water-Flooding Reservoirs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Jinde Feng, Wei Tang, Ting Liu, Donghui Wang, Yajie Tian, Jianzi Shi, and Meng Zhao

632

643

Innovative Application of Big Data Technology in Southwest Pipeline Information System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Heng-Bin Wang, Dong-Chao Liu, and Yan Meng

651

Optimizing the Development Strategy for the Block Faulted Oil field with Merak Capital Planning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Zuoqian Wang, Guifang Fa, Weina Jiang, Jun Lan, and Bin Zhao

658

The Study on Portfolio Optimization Methods for Overseas Petroleum Development Projects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Wei-na Jiang, Liang Wei, Qian Liu, Xi Chen, and Zuo-qian Wang

669

Smart Oilfield Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Dianfa Du, Xue Zhang, Qiaoqiao Guo, Bin Zhang, and Genkai Zhang Driving Force Analysis of Sandstone Reservoirs with Strong Natural Aquifer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Zhanxiang Lei, Jian Liu, Jian Li, Likun Xu, Lihong Fan, Yunbo Li, and Zhaopeng Yang

685

695

CO2 Sequestration Electromagnetic Imaging Based on Nanoparticle Contrast Agent and Casing Excitation . . . . . . . . . . . . . . . . . . . . . . . . . Weiqin Li, Zaiping Nie, and Wenhe Xia

705

Experimental Study of Transient Electromagnetic Resistivity Logging Through Casing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Si-hui Liu, De-fu Zang, Fu-ming Zhang, and Yu-ke Huang

713

Study on Centrifugal Pump Rotor Fault Feature Extraction Based on Fractal Theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Wencai Liu and Qiyong Peng

723

Research and Development of B/S-Based Data Mining System for Petroleum Information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Qian Zhang, Shiyun Mi, and Xinchao Liu

736

Different Tapping Solutions for Remaining Oil in Sandstone Oil Field at Ultrahigh Water Cut Stage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Jian Liu, Zhan Xiang Lei, Li Kun Xu, Jian Li, Yun Bo Li, Zhao Peng Yang, and Wen Chen

745

Contents

New Dynamic Multi-factor Economic Limit Well Pattern Density Calculation Method Based on Single-Well Limit Control Reserves . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Hongwei Wang, Haibo Liu, Xianbao Zheng, Zhiguo Miao, Jibin Wang, Wei Yan, and Wenlin Chen A Numerical Well Test Model in Multi-media Carbonate Reservoirs and Its Application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Fangfang Chen, Zhiwen Ding, Meichun Yang, Jing Liang, Jian Zhang, and Wen Cao Mechanism of Hydrocarbon Migration of Paleozoic Clastic Rocks in Western Section of the Tabei Uplift, Tarim Basin: YM34 Silurian Accumulations as a Case . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Wensheng Guan, Ming Zha, Ting Li, Jiangxiu Qu, Fei Li, Liping Deng, Yang Tan, and Chi Zhang Prediction on Basement Fracture in Jambi Depression, South Sumatra Basin, Indonesia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Guangcheng Hu, Xiangwen Kong, Yuxia Ma, Houqin Zhu, Ming Li, and Guoliang Hong Diagenetic Simulation of Paleogene Clastic Reservoir Based on Diagenesis in Bozhong Depression, China . . . . . . . . . . . . . . . Wendao Qian, Taiju Yin, Changmin Zhang, Guowei Hou, Miao He, and Min Xia Reserves Estimation of Two-Layer Commingled Gas Well by Material Balance Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sun Hedong, Cui Yongping, Cao Wen, and Li Yanchun A New Identification Method and Its Application on Asphaltic Zones In Bioclastic Limestone Reservoir: A Case Study of Ru3 Reservoir of AA Field, Middle East . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Zhong-yuan Tian, Rui Guo, and Li-ping Yi Applied Research and Well Interference Test Model of Ultrahigh Pressure Gas Reservoir of Keshen Gas field . . . . . . . . . . . . . . . . . . . . . Hongfeng Wang, Yinglin Jia, Songbai Zhu, Xia Qiao, Shengjun Wang, and Yanbo Nie A Case Study of Subsurface Uncertainty Analysis in Modelling Carbonate Reservoir . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Yong Yang, Ming Zhang, Aifang Bie, Jietang Lv, Wenqi Zhang, Zehong Cui, and Zhaohui Xia Research and Application of the Evaluation System for a Complex Fault Block Sandstone Condensate Gas Reservoir . . . . . . . . . . . . . . . . Xiaoling Zhang, Wei Ding, Yunpeng Hu, and Xiaoyan Liu

xi

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770

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822

828

841

851

865

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Transient Pressure Analysis in Partially Perforated Vertical Wells . . . Weiping Ouyang, Deyong Yang, and Hedong Sun A Method of Favorable Source Rock Evaluation and Prediction: A Case Study From Zhahaquan Oil Field, Qaidam Basin (Nw China) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mingzhi Tian, Zhanguo Liu, Zhiyuan Xia, Yanqing Wang, Senming Li, Guangyong Song, and Yafeng Li Characterization and Modeling of Fractures in the Bereketli-Pirgui Carbonate Reservoir, The Right Bank of the Amu Darya . . . . . . . . . . Xing Yuzhong, Guo Chunqiu, Cheng Muwei, Shi Haidong, Zhu Houqin, and Chen Pengyu

873

892

901

Time Matching and Its Control Effect on Gas Migration and Accumulation Period of Caprock, Source Rock, and Fault in Ed Formation of X sag . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Chen Haibin, Chen Xuehai, Song Jing, Yang Zhisheng, Cheng Zhiyong, Yang Jingfang, Wang Chunguang, Liu Li, and Yang Qin

916

Logging Identification of Asphaltenes in Carbonate Reservoirs—Taking the Case of the Halahatang Oil Field as an Example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Chen Lixin, Yang Haijun, Cheng Hanlie, Yang Wenming, Gao Chunhai, Qi Dianqing, and Liu Xiao

926

Effect of WaterFlooding Speed on Water–Oil Displacement Efficiency of Homogeneous Core . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Xiangzhong Zhang, Lun Zhao, Jincai Wang, Li Chen, and Xiangan Yue

932

Fractal Distribution of Paleotrough and Exploration Potential in Ordos Basin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Xunxun Fu, Huitao Zhao, Daojun Huang, Yijun Fan, Yani Jia, Lei Sun, and Yuan Wei

938

Predicting Recovery Factor and Waterflooding Performance by History Variables in Waterflooding Reservoirs . . . . . . . . . . . . . . . . Libing Fu, Jun Ni, Zifei Fan, Xuanran Li, and Lun Zhao

946

Geological Characteristics and Production Performance of Ultra-Deep Naturally Fractured Tight Sandstone Gas Reservoirs . . . . . . . . . . . . . Ruilan Luo and Yongzhong Zhang

959

Analysis of Pore Characteristics of Reservoir Rock Based on CT Scanning—Taking the Tazhong Block of Tarim Basin as an Example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ying Guo, Yong Yang, Guangying Ren, Jinlong Ni, and Hanlie Cheng

973

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Identification of Interwell Interference Based on Production Dynamics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Hailong Zuo

985

Integration of Two-Dimensional Map into Three-Dimensional Model: A New Sand Body Modeling Approach for Delta Reservoir . . . . . . . . . Xintao Yuan, Cheng Lei, and Qingyan Xu

992

Investigation on Characteristics and Affecting Factors of Water Cut in Planar Thief Zone . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1004 Xudong Shen, Xinwei Liao, Aixian Huang, Jufeng Xue, and Xiongtao Shang High-Resolution Sequence Stratigraphy and Subtle Reservoir Characterization Analysis: A Case Study from the Qingshankou Formation in Southern Songliao Basin . . . . . . . . . . . . . . . . . . . . . . . . . 1018 Minghui Liu, Ziming Hou, Li Chen, and Hongwen Deng Description Technology of Fractured-Vuggy Carbonate Reservoir in Halahatang Oil field, Tarim Basin—Take the Ha 7 Test Area as an Example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1032 Lixin Chen, Zhenbiao Wang, Lijuan Zhang, Hanlie Cheng, and Dianqing Qi A Systematic Workflow to Determine the Distribution of Original Oil and Gas and Residual Oil and Gas in N Gas Condensate Field . . . . . . 1043 Ming Zhang, Hongjun Wang, Jietang Lv, Yong Yang, Yunpeng Hu, Zhaohui Xia, Ming Li, Guihong Wang, Fengyun Zheng, Fangwen Dai, and Xiaowei Yu New Identification Method of Sedimentary Microfacies of Carbonate Rocks: A Case Study of Carboniferous KT-II Layer on West Slope, in the Central Block of Caspian Basin . . . . . . . . . . . . . . . . . . . . . . . . . 1055 Shuang Liang, Man Luo, Jiquan Yin, Yankun Wang, Shanbo Sheng, and Shutang Jin Research on Reasonable Water Injection Parameters of Water Flowing Barrier to Delay Bottom Water Coning . . . . . . . . . . . . . . . . . 1066 Ying Fu, Zheng-jun Zhu, Chao Zhang, Tao Shi, Hui Ma, and Kai Feng Reservoir Characterization of Qadirpur Gas Field, Central Indus Basin, Pakistan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1073 Waqar Ahmad, Xianlin Ma, and Fakhar ul Islam Reservoir Prediction of the Reef of the Cambrian Platform Margin Area in the Gucheng of Tarim Basin . . . . . . . . . . . . . . . . . . . . . . . . . . 1082 Wei Xu

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Seismic Geomorphology of the LTAF Formation in JB Block, South Sumatra Basin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1089 Houqin Zhu, Guoliang Hong, Yuxia Ma, Guangcheng Hu, and Zhenhua Bai Seismic Motion Inversion Study on Prediction of Interbedded Thin Beds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1100 Wei-wei Liu, Chun-lin Xie, Jiu-zhan Hu, Meng Tian, Chao Wang, and Jing Sun Fan Delta Sedimentary Characteristics . . . . . . . . . . . . . . . . . . . . . . . . . 1109 Tianjian Sun, Fang Xu, and Zheng Meng Uncertainty Analysis of Sedimentary Microfacies Modeling on Hancha Block in Chang Guanmiao Oilfield . . . . . . . . . . . . . . . . . . . 1119 S. W. Pan, Z. T. Xue, and M. M. Zhang Fracture Prediction of Thin Carbonate Reservoir Based on Wide-Azimuth Seismic Data . . . . . . . . . . . . . . . . . . . . . . . . . 1130 Zhen Wang, Junzhang Zheng, Yankun Wang, Jiquan Yin, Man Luo, and Shuang Liang Study on Coal Forming Process and Coal Seam Distribution Controlled by the 4th-Order Sequence—A Case Study of T Block, the South Turgay Basin, Kazakhstan . . . . . . . . . . . . . . . . . . . . . . . . . . 1137 Wei Yin, Jiquan Yin, Mingjun Zhang, Man Luo, Xiaofeng Sheng, Jianjun Guo, and Rui Cai A New Thought on Identification of Reef Shoal and Carbonate Sedimentary Environment Under Salt Gypsum Rocks—A Case Study in the Central Block of Amu Darya Right Bank . . . . . . . . . . . . . . . . . 1148 Liangjie Zhang, Xingyang Zhang, Hongjun Wang, Tongcui Guo, Xinglin Gong, Youheng Leng, and Hongwei Zhang Productivity Analysis of Commingling Production of a Multiple-Channel Reservoir with Closed Boundary by a Horizontal Well . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1161 Wen-qi Zhao, Lun Zhao, Shu-qin Wang, Meng Sun, Ming-xian Wang, Hao Su, and Li Chen Study on Comprehensive Modeling of Reservoir Based on Process Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1171 Da Cheng Wang, Zhi Wei Chen, Xiao Chen Liu, Yu Zhang, Xin Kai Cui, and Jun Lin

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Stochastic Simulation of Lithology Distribution Constrained by Stratigraphic Forward Modeling and Seismic Inversion: A Case Study of A Oilfield in Ecuador . . . . . . . . . . . . . . . . . . . . . . . . . 1180 Kexin Zhang, Xuepeng Wan, Quan Hu, Heping Chen, Hong Huo, Shiyao Lin, Chaoqian Zhang, Zheng Meng, Yusheng Wang, and Haikuan Zhang Sedimentary Microfacies of M1 Sandstone Reservoir in the D-F Oil Field . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1193 Tianyu Zhang and Jinxiu Yang Effective Quantification and Applications of Seismic Attributes . . . . . . 1208 Changjiang Fan, Tianwei Zhou, and Tiezhuang Wu Fewer Well with Higher Production Pattern Development of Metamorphic Reservoirs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1218 M. Q. Chen, J. He, L. Ren, and W. B. Yang The Simulation Method Research of Hydraulic Fracture Initiation with Perforations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1229 Haifeng Fu, Fengshou Zhang, Dingwei Weng, Yunzhi Liu, Yuzhong Yan, Tiancheng Liang, Baoshan Guan, Xin Wang, and Wei Zheng Research on Key Techniques of Offshore Heavy Oil Production Based on Distributed Electro-Acoustic Efficiency . . . . . . . . . . . . . . . . . 1241 Guowang Gao, Dan Wu, Dasen Hou, and Dawei Yu Research and Application of Oil Recovery Recyclable Clean Fracturing Fluid . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1251 Zefeng Li, Mian Zhang, Yan Gao, Zuwen Wang, Jianping Lan, and Xiaohong Bao Post-flooding with Associative Polymer/Alkali/Surfactant Ternary System After Polymer-Enhanced Oil Recovery . . . . . . . . . . . . . . . . . . . 1264 P. H. Han, R. B. Cao, H. S. Liu, W. Yan, L. Yang, F. Luo, and H. Zhou Study on the Effect of Reservoir Heterogeneity on Air Foam Flooding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1275 Hua Hua Li, Shu Man Li, Xiao Bing Lu, Jing Hua Wang, and Wen Biao Duan Laboratory Study of the Petrophysical Effect of Natural Fractures on Gas Flow Through Naturally Fractured Tight Cores . . . . . . . . . . . 1290 Hong-yan Qu, Jia-wei Hu, Fu-jian Zhou, Yan Peng, and Zhe-jun Pan Design and Field Application of a Composite Microbial Flooding Process for a High-Water-Content Oilfield . . . . . . . . . . . . . . . . . . . . . . 1298 Long Ren, Mingqiang Chen, Baoge Cao, Bing Li, Xue Li, Nan Zhang, and Jian Sun

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Water Cut Changing Rules After Liquid Rate Increasing in Strongly Heterogeneous Reservoirs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1311 Renfeng Yang, Jinqing Zhang, Han Chen, Sheng Guo, Jiawei Tang, and Jing Li Stress Analysis of Sand Particles in Separators in Downhole Oil/Water Separation and Reinjection System Based on Coupled CFD-DEM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1330 Yan Zhang, Minghu Jiang, Yong Zhang, Lei Xing, and Youbin Chen New Method for Analysis of Shearing Fracture in Unconventional Reservoirs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1343 Zi-wei Zhang, Xiang-yi Yi, Xia Wu, Yuan-qin Wu, and Qin Li Laboratory Evaluation on Air-Assisted Steam Stimulation in Common Heavy Oil Reservoir . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1353 Zhao Qinghui, Liu Qicheng, Leng Guangyao, and Peng Xu Development of Remote Well Opening Equipment Based on Electric Needle Valve in Sulige Gas Field . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1363 Yong Chen, JiE Gui, Zhengyan Zhao, and Shuangquan Liu Properties of Surfactant Solution for Foam-Flooding . . . . . . . . . . . . . . 1370 H. S. Liu, G. Chen, R. B. Cao, P. H. Han, C. S. Lv, S. L. Guo, and C. Y. Cui Experimental Study on CO2 Microcosmic Displacement of Core Flooding in Ultra-low Permeability Reservoirs, Ordos Basin . . . . . . . . 1381 Yangnan Shangguan, Jiyong Zhao, Zhaoguo Li, Xinhui Lei, Weiliang Xiong, Shuman Li, and Xingmei Kang Design of Oil and Gas Well Ground Manifold Connecting Aid . . . . . . 1389 Yanchao Sun, Mingxue Chen, Shengming Huang, Yue Su, Qibing Wang, and Yichang Zhang Optimization Design of Drilling Speed in Sulige Gas Field . . . . . . . . . . 1396 Yanchao Sun, Yue Su, Shengming Huang, Yichang Zhang, Qibing Wang, and Mingxue Chen Vertical Well and Wirtual Well Trajectory Control Colume Theoretical Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1406 Yanchao Sun, Chengcheng Niu, Zongxi Bai, and Lizhi Su Reservoir Prediction and Its Applications in Identification of Stratigraphic Traps in Fula3D Area, Muglad Basin, Sudan . . . . . . . 1415 Quan Zou, Aixiang Liu, Fengyun Zheng, Yanli Shi, and Weili Ke Effect of Packer on the Fracture Initiation in Open-Hole Horizontal Well . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1422 H. X. Xu, Z. W. Wang, and M. Zhang

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xvii

An Integrated Petrophysics and Geomechanics Method for Fracability Evaluation in Tight Sandstone Reservoirs: A Case Study in the Yingcheng Formation, Jinshan Gas Field, Songliao Basin, China . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1434 Zhaozhong Yang, Rui He, Xiaogang Li, Ziyuan Liu, He Huang, and Zhuang Deng Optimization Design and Application of Vortex Drainage Gas Recovery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1453 M. Cai, W. H. Ma, P. G. Ma, J. Q. Wang, J. L. Li, N. Li, and H. T. Zhang Design of a Magnetic Memory Detecting Sensor for Oil Well Casing Well Damage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1463 Sun Bingcai and Chu Shengli Study on Tensile Test Elongation Variation Law for High-Strength Steel Material . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1472 X. F. Xu, X. J. Zhao, Y. F. Ai, M. H. Liang, and H. J. Zhang Optimization Model of Horizontal Wells with ICD Water Control Completion in Bottom Water Reservoirs . . . . . . . . . . . . . . . . . . . . . . . 1479 Fachao Shan, Shijun Huang, Congge He, Lun Zhao, and Anzhu Xu A New Temporary Blocking Fracturing Design for Efficiently Activating Natural Fractures of HPHT Fractured Thick Sand Reservoir . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1488 Xiu-ling Han, Ying Gao, Juan Jin, Kan Sun, Yang Shi, Xue-fang Yuan, and Meng Wang Deep Penetrating Horizontal Drilling Techniques Status Quo Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1499 Yu Han, Shao-gong Zhu, Feng-shan Wang, Fu-min Liang, Hai-cheng Li, Qing-zhong Li, Kan Wu, and Ling Wang Research and Application of Intelligent Separate Layer Production Technology for Producers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1508 Shujin Zhang, Lin Li, Jing Chen, Li Ban, Jiali Chen, Hongyan Zhang, and Chunhui Zhang Study on Sensitivities of Numerical Simulation Parameters in SP Flooding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1518 Shuman Li, Huahua Li, Yangnan Shangguan, Lei Fang, Wei Fan, Jinlong Yang, and Lili Wang Water-Out Characteristics and Remaining Oil Distribution of Delta Front Reservoir—Take J-2C Reservoir of Kalamkas Oilfield in Kazakhstan as an Example . . . . . . . . . . . . . . . . . . . . . . . . . 1527 Xuanran Li, Rongrong Jin, Libing Fu, Bifeng Xu, and Zihan Zhang

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Development of a New Type Two-Stage Cutting Composite Bit . . . . . . 1536 Yanchao Sun, Yichang Zhang, Qibing Wang, Yue Su, Shengming Huang, and Mingxue Chen A Parameter Design Method of Gas Lift Technology for Production Recovery and Application to a Water-flooded Gas Well . . . . . . . . . . . 1547 H. T. Zhang, Y. P. Zhang, Z. S. Yang, M. Cai, P. G. Ma, N. Li, J. L. Li, and Q. Yang Research and Application of Borehole Stability Mechanism in the Deep Sand-mudstone Formation . . . . . . . . . . . . . . . . . . . . . . . . 1557 Dongjie Li, Yuhao Wei, Changzhu Liu, Hongyan Ma, Jinsheng Yang, and Zhaohai Yin Numerical Simulation of Lateral Drilling Horizontal Well Flow Lines in High-Hydrocarbon Reservoirs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1573 Du Dianfa, Guo Qiaoqiao, Zhang Xue, and Zhang Bin Study and Application of Temporary Plugging and Acidization in Water Injection Well . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1582 Fei Chen, Xin Rong Zhong, and Long Chai Influence of Well Pattern on in situ Stress Filed of Shale Reservoir . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1591 Li Shuai, Chen Junbin, Li Yu, and Liu Jing A Review of Techniques for Enhancing Oil Recovery by EM and US Wave . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1604 Muhammad Ismail, Guowang Gao, Iqbal Sajid, and Yongchao Wang A Study on Reasonable Injection-Production Network in Tahe Oil field Fractured Reservoir . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1616 Jie He, Long Ren, and Mingqiang Chen Visualized Experiment on Critical Cutting Transport Behavior of Annular in Horizontal Well Section . . . . . . . . . . . . . . . . . . . . . . . . . 1625 Wei Song, Yan Zhou, Kuanliang Zhu, Zhongzhi Hu, and Ji Xu The Stability Experimental Method and Friction Reduction Method Discussion of Emulsified Acid . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1636 Liwei Wang, Xiaohui Qiu, Yuting Liu, and Minjie Xu Evaluation of b-Cyclodextrin Dimers/Amphiphilic Polymer Inclusion Complexation in Enhanced Oil Recovery . . . . . . . . . . . . . . . . . . . . . . . 1645 Yanfeng Ji, Xulong Cao, Lanlei Guo, Yangwen Zhu, and Hui Xu Distribution of Microscopic Remaining Oil After ASP Flooding in Saertu Oilfield in Daqing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1653 Y. J. Liang, Z. A. Li, J. Li, and X. D. Sun

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xix

Studies on EOR of Sandstone Oilfield with Low Viscosity and High Salinity During High Water Cut Stage—A Case Of Kumkol Oilfield in Kazakhstan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1663 Li Chen, Lun Zhao, Haili Cao, Jincai Wang, Wenqi Zhao, Libing Fu, Erhui Luo, Fengjun Hao, and Xiangzhong Zhang Electromagnetic Response Characteristics of Local Conductors with Pseudo-random Coded Waveforms . . . . . . . . . . . . . . . . . . . . . . . . 1684 Xijin Song, Xuelong Wang, and Peng Li Multi-Stage Intelligent Throughput Test of Horizontal Wells in Jiyu Oilfield . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1706 Wei Wang, Xiang-jun Wei, Jian-zhong Zhang, and Xiao-e Wang Design of De-oiling Separator Based on Oil Droplets Migration Trajectory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1716 Lei Xing, Minghu Jiang, and Yong Zhang Development Strategy for Gas Cap Reservoirs with Edge Water and Complicated Faults in Niger . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1728 Qingyan Xu, Cheng Lei, Xintao Yuan, and Xuanyu Yang A Novel Separate Layer Injection Technique for Polymer Flooding in Daqing Oil Field . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1734 Shao-gong Zhu, Wang-fu Zhou, Chong-jiang Liu, Xing-liang Song, Hai-cheng Li, Guang-lei Gao, Jun-dong Tang, and Jing Wang Self-excited Rotating Magnetization Field Ranging for SAGD Dual Horizontal Well . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1744 P. Wu, Z. Y. Guo, W. Xu, Y. X. Zhou, and Z. X. Liu Application of Electro Thermal Technology in Heavy Oil Production Testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1753 Zeng Qinghui Intelligent Judgment of Risks While Gas Drilling . . . . . . . . . . . . . . . . 1759 Haitao Li, Na Wei, Anqi Liu, Wantong Sun, Lin Jiang, Yang Liu, Zhenjun Cui, and Hanming Xu A Design of Magnetic Memory Sensor of Oil Well Casing Damage Detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1778 Bingcai Sun, Shengli Chu, Jianchu Fan, and Fangfang Ding Application of Conformal Coring Tool in Complex Formation of Block Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1788 Jing Liu, Junbin Chen, Yu Li, Shuai Li, and Nannan Ren A Transient Well Test Method for Wellhead Pressure Fall-Off Test After Acid Fracturing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1796 Hanlie Cheng and Lianshan Wang

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Development and Application of Visual Logging Equipment . . . . . . . . 1807 Zhengguo Yan, Qingping Luo, Xiangxiu Zheng, and Jiatian Zhang Development Strategy Study Based on Improved Analytic Hierarchy Process for Complex Fault Block Oil Reservoirs . . . . . . . . . . . . . . . . . 1816 Cheng Lei, Qingyan Xu, Xintao Yuan, Chujuan Kang, Xuanyu Yang, and Jiaofen She Experiment for Acquiring the Secondary Field About Formation Information in a Cased Well Model . . . . . . . . . . . . . . . . . . . . . . . . . . . 1831 Shouwei Zhang, Defu Zang, Shuqin Liu, and Hongna Jiang Influence of Swirl Vane on the Low-Pressure Gas Flow in Supersonic Separators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1841 Jiang Bian, Xuewen Cao, Yang Liu, Yuan Sun, and Qi Chu An Unconventional Method to Separate Carbon Dioxide from Wellhead Natural Gas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1850 Jiang Bian, Xuewen Cao, Yuan Sun, Wenming Jiang, and Qi Chu Study on Wellbore Relative Humidity of Gas Drilling in Condition of Formation Water . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1860 Haitao Li, Na Wei, Anqi Liu, Wantong Sun, Lin Jiang, Hanming Xu, Yang Liu, and Zhenjun Cui Detection Optimization of Single-Axis Magnetic Anomaly Sensor for Pig Clog Locating . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1874 W. Xu, Z. Y. Guo, P. Wu, and Z. X. Liu Wellbore Temperature Field Prediction in Marine Drilling . . . . . . . . . 1885 Na Wei, Wantong Sun, Yingfeng Meng, Jinzhou Zhao, Liehui Zhang, Haitao Li, Qingping Li, and Anqi Liu System Reliability Evaluation for Complex Deep Well Casing Based on Structural Reliability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1901 H. Fan, P. Wang, X. J. Zhao, M. Liu, X. Zh. Yan, and Y. R. Feng Research and Application of Electronic Control Intelligent Oil Recovery Technology in Horizontal Well . . . . . . . . . . . . . . . . . . . . . . . 1914 Long Wang, Dekui Xu, Nan Li, Xiaoyu Xu, Renyong Liu, Jiyang Zhang, Zhongbo Zheng, Jiahui Zhu, and Haichen Ou Aerated Drilling Fluids Used for Geothermal Wells . . . . . . . . . . . . . . . 1920 Esaie Kuadjovi, Michelle Djuidje, Irene Kongwa, Janet Timana, and Vito Mitoukou Experimental Confirmation of the Existence of the Lag in the Hydraulic Fracture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1934 M. A. Trimonova, E. V. Zenchenko, P. E. Zenchenko, S. B. Turuntaev, and N. A. Baryshnikov

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Advanced Technologies Used in Sand Control Completion . . . . . . . . . 1943 Ismael W. Friki, Ndakolo J. Haiduwa, Andrew J. Magoti, Gervas Dotto, Jackeline P. Kimune, and Albert K. Kissima Distributed Vibration and Temperature Measurement for Oil Well Based on Continuous Fiber Bragg Grating Array . . . . . . . . . . . . . . . . 1965 Zhihui Mei, Jianguan Tang, Chengli Li, Kun Yang, and Minghong Yang Application of Discrete Fracture Network Model in the Simulation of Massive Fracking in Tight Oil Reservoir . . . . . . . . . . . . . . . . . . . . . 1974 Shuai Li, Xin Wang, Bo Cai, and Chunming He Experimental Study on Fracture Propagation of Liquid CO2 Fracturing in High-Rank Coal Rock . . . . . . . . . . . . . . . . . . . . . . . . . . 1984 Yuanzhao Jia, Xi Yu, Donghe Yu, Guohua Liu, Mengmeng Ning, and Hang Che Sedimentary Microfacies Analysis and Reservoir Characterization of the Middle Jurassic Carbonates: A Case Study from Lower Indus Basin, Pakistan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1994 Bilal Wadood, Sajjad Ahmad, and Suleman Khan Study on the Current Situation and Influencing Factors of Casing Damage in S Oilfield . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2001 Yimin Pan Research on Identification Method of Dominant Seepage Flow Channel of Fractured Horizontal Wells in Tight Oil Reservoir Based on Fuzzy Synthetic Evaluation Model . . . . . . . . . . . . . . . . . . . . 2007 Wenhao Cui, Wendong Yang, Cheng Jing, and Yihua Wang Experimental Research on Corrosion Resistant Rubber Based on Supercritical CO2 Injection Process . . . . . . . . . . . . . . . . . . . 2025 Zhongchao Lin, Jiang Sun, Lichuan Zhao, Qing He, and Hao Xu Author Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2034

The Nonlinear Flow Analytical Model and Its Field Use Hongbing Jia1(&), Baoquan Song1, Wei Mao1, Zhijing Bao1, PengJu Du1, Yaguang Li1, Lijun Yang2, and Yingmei Shao1 1

The E&D Research Institute of Daqing Oilfield Company Ltd, Daqing, China {jiahongbing,songbaoquan,maowei,baozhijing,dupengju, liyaguang,shaoyingmei}@petrochina.com.cn 2 The Natural Gas Company of Daqing Oilfield Company Ltd, Daqing, China [email protected]

Abstract. The nonlinear flow exists in ultra-low-permeability reservoir. It is important to establish an analytical model, which can be used in revealing nonlinear flow rule and improving producing status in field. According to the potential superposition principle, the mathematical model to predict the pressure gradient is established, and then, the nonlinear flow model is established by combining the pressure gradient boundary getting from the indoor nonlinear flow, and at last nonlinear flow area is determined in plane by increasing virtual production wells. It shows three features in the application of T14 block in Hailar oilfield. Firstly, the high value zone of cross-well pressure gradient is mainly concentrated in the area of 20–50 m near the oil–water well. Secondly, the pressure gradient is obviously affected by well spacing, and its lowest value is inclined to one side of the oil well. At last, the nonlinear flow zone is the main zone in ultra-low-permeability reservoir, and the area percentage is 60%, which is the main cause of the quickly production decline. The nonlinear flow area can be determined using the dynamic data. It can overcome two problems including parameter selection and extension in oilfield. Keywords: Ultra-low permeability Pressure gradient
Quasilinear flow




Nonlinear flow




Analytical model




Copyright 2018, Shaanxi Petroleum Society. This paper was prepared for presentation at the 2018 International Field Exploration & Development Conference in Xi’an, China, 18–20 September 2018. This paper was selected for presentation by the IFEDC&IPPTC Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the IFEDC&IPPTC Committee and are subject to correction by the author(s). The material does not necessarily reflect any position of the IFEDC&IPPTC Committee, its members. Papers presented at the Conference are subject to publication review by Professional Committee of Petroleum Engineering of Shaanxi Petroleum Society. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of Shaanxi Petroleum Society is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of IFEDC&IPPTC. Contact email: [email protected]. © Springer Nature Singapore Pte Ltd. 2020 J. Lin (ed.), Proceedings of the International Field Exploration and Development Conference 2018, Springer Series in Geomechanics and Geoengineering, https://doi.org/10.1007/978-981-13-7127-1_1

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1 Introduction The core displacement experiment in laboratory and the oilfield development practice show that nonlinear flow exists in ultra-low-permeability reservoirs [1–5]. Numerical reservoir simulation is the main method to study nonlinear flow at present. The numerical simulation software of three-phase nonlinear flow is developed [6–11]. It is considered that most of the flow regions in low-permeability reservoirs are in the nonlinear flow range. Quasilinear flow occurs only in a small area near the wellhole. However, many parameters required for modeling are often difficult to be determined accurately (especially when non-Darcy flow is considered in ultra-low-permeability reservoirs), coupled with the complexity of reservoir numerical simulation (currently mainstream commercial software does not take into account non-Darcy flow), so there are some difficulties in the field application for engineers and technicians. In addition, some scholars put forward some mathematical models to describe nonlinear flow based on laboratory experimental data [12–14]. However, how to obtain the analytical solution and how to apply it to the oil field to match the actual dynamic characteristics are not been reported in the reference. In this paper, the nonlinear flow model of injection-production well group is studied from the point of view of establishing equation based on the actual production dynamic data of oil field, and it is applied in typical blocks.

2 The Nonlinear Flow Analytical Model The key to the establishment of nonlinear flow model is the prediction of pressure gradient. An equation for calculating the displacement pressure gradient of water flooding at the midpoint of the mainstream line of one source (water injection well) one confluence (oil well) with constant output is proposed [15], but this method is only suitable for the case of two wells with the same injection rate and oil production rate. The distribution equation of the pressure gradient between injection and production wells with one source and one confluence is derived [16, 17], but in the course of oilfield development, the number of wells in an injection-production well group is rarely one, generally more than two. 2.1

Assumed Condition

To simplify the process and facilitate the establishment of mathematical models, set the following assumptions: ① The reservoir is stratified, and the longitudinal fluid movement and material exchange are ignored; ② the reservoir is homogeneous and equal in thickness, and the difference of fluid distribution on the plane is not considered; ③ no consideration of compressibility of porous media and liquids; ④ it is steady flow; ⑤ the flow process isothermal.

The Nonlinear Flow Analytical Model and Its Field Use

2.2

3

Potential of Plane Radial Flow

In reference [18], the concept of apparent permeability is introduced and the starting pressure gradient is considered, and when the pressure gradient is greater than the minimum starting pressure gradient, the equation of low velocity non-Darcy flow is: v ¼ 0:0864

k0 gradP l

ð1Þ

In the equation: v is flow velocity, m/d; k′ is apparent permeability, 10−3 lm2; l is underground fluid viscosity, mPa s; P is formation pressure at any point in an infinite formation, MPa; GradP is the pressure gradient here, MPa/m. 0 The following is based on the dynamic and static data of the field, and kl is obtained. According to the definition of potential: w¼

k0 P l

ð2Þ

In the equation: w is the potential, when the distance from it to the well is r, it has stress implication. The equation for calculating the potential of a point in infinite plane is: w¼

5:787q ln r þ C ph

ð3Þ

In the equation: C is constant, determined by boundary conditions. Suppose at a certain time T0, an injection-production well group is in production in the infinite layer (Fig. 1), the average reservoir thickness of each well in the well group is h, m; W1 is a water injection well, the well location coordinates are (x1, y1), the

Fig. 1. The well location figure of nonlinear flow model

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bottom hole pressure is P1, MPa, the injection rate is q1, t/d, W2W3,…Wn is oil production well, the well location coordinates are (x2, y2), (x3, y3), …, (xn, yn), the bottom hole pressure is P2, P3, …, Pn, MPa, the production is q2, q3, …, qn, t/d, and R12 is the interval between injection well W1 and production of well W2, m. On the main line of water injection well W1 and any oil production well (W2 well here), the distance between any point M and the water injection well W1 is rM, The coordinate of the point M is (x, y). According to Eq. (3) and the principle of superposition, the potential of M point is as follows: 2 3 q lnrM þ q2 lnðR12  rM Þ  q ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 5:787 4 1P n 5þC wM ¼ þ qi ln ðx  xi Þ2 þ ðy  yi Þ2 ph

ð4Þ

i¼3

If the well coordinates, fluid production, and water injection are known, according to Eq. (2), based on the wellbore potential of water injection well W1 and any oil 0 production well (W2 well here), the equation to calculate kl is as follows: " # n k0 5:787 R21 X Ri1 ¼  ðq1 þ q2 Þ ln þ qi ln l p hðPinf  Pwf Þ rw Ri2 i¼3

ð5Þ

In the equation: Pinf is the bottom hole pressure of water injection well, MPa; rW is well radius, m; Pwf is bottom well flow pressure, MPa; Ri1 is the well spacing between W1 well and Wi well, m; Ri2 is the well spacing between W2 well and Wi well, m. 0 Therefore, at a certain time, kl of whole reservoir can be calculated and fixed, its value is related to the time and the dynamic and static parameters of water injection. The distribution of the pressure gradient along the main stream is derived below. The coordinates of any point M on the main stream are unknown. It is necessary to found the function of well point coordinate and distance from injection well; the relationship of rM and coordinates is obtained by coordinate transformation: 1 x ¼ x1  pffiffiffiffiffiffiffiffiffiffiffiffiffi rM 1 þ a2   1 y ¼ a x1  pffiffiffiffiffiffiffiffiffiffiffiffiffi rM þ b 1 þ a2

ð6Þ ð7Þ

2 In the equation: a is a straight line slope, a ¼ yx11 y x2 ; b is a straight line intercept, y1 y2 b ¼ y1  x1 x2 x1 . In the Eqs. (6) and (7), if x1 > x2, that is, when the water injection well is located on the right side of the production well, it is negative, conversely, it is positive. Equations (2), (6), and (7) are substituted into Eq. (4); the pressure gradient of any point M on the mainstream line between injection and production wells is gained by derivation as follows:

The Nonlinear Flow Analytical Model and Its Field Use

5

 5:787l q1 q2  jgradPj ¼ phk 0 rM ðR12  rM Þ 9     > 2     > 1 a 2 = n qi x1  pffiffiffiffiffiffiffiffiffi r  xi  þ a x1  pffiffiffiffiffiffiffiffiffi r þ ab  ayi  X 1 þ a2 M 1 þ a2 M

       2 2 > pffiffiffiffiffiffiffiffiffiffiffiffiffi > 1 1 i¼3 ; 1 þ a2 x1  pffiffiffiffiffiffiffiffiffi r  xi þ a x1  pffiffiffiffiffiffiffiffiffi r þ b  yi 1 þ a2 M 1 þ a2 M ð8Þ The pressure gradient distribution on the main stream of water injection well and production well can be calculated according to Eq. (8). Equation (5) is substituted into Eq. (8); the pressure gradient at any point on the mainstream line can be obtained. Combined with nonlinear flow definition, the model of nonlinear flow can be obtained: ðPinf  Pwf Þ n P ðq1 þ q2 Þ ln Rrw21 þ qi ln RRi1i2 i¼3 9 8     > >    2  > > 1 a2 p ffiffiffiffiffiffiffiffiffi p ffiffiffiffiffiffiffiffiffi n =

> r ðR12  rM Þ i¼3 pffiffiffiffiffiffiffiffiffiffiffiffi2ffi > > 1 1 ; :M 1þa r  xi þ a x1  pffiffiffiffiffiffiffiffiffi r þ b  yi x1  pffiffiffiffiffiffiffiffiffi 1 þ a2 M 1 þ a2 M

kmin \

ð9Þ In the equation: kmin is maximum starting pressure gradient, MPa/m. kmax is maximum starting pressure gradient, MPa/. 2.3

Determination Process of Nonlinear Flow Zone

The process of determining the nonlinear flow zone can be divided into three steps: The first is to determine the pressure gradient between injection and production wells according to the analytical model of nonlinear flow; the second is to determine the maximum and minimum starting pressure gradient in the laboratory, or to determine it based on the regression between permeability and experimental data. The third is the deployment of virtual production wells with a production rate of 0 in fault boundaries or areas with low well control, the calculation of the cross-well pressure gradient is calculated, the main aim is to increase data point, and the determination of nonlinear flow region in plane can be coupled at last.

3 Oil Field Application 3.1

Overview of the Block

T14 block is located in the east of A oil field in Hai Ta Basin. A semi-enclosed fault block reservoir with east, north, and west sides blocked by faults and open to the south side. The fault is a reverse normal fault, and the reservoir is mainly developed in

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T formation. The fault block is 0.82 km in length and 0.75 km in width. The formation dip angle is 11.0°, the reservoir permeability is 8.5  10−3 lm2, and the formation crude oil viscosity is 2.7 mPa s. Block T14 has two well groups A56-54 and T236-216, which are separated by D4 fault and are in low water cut stage (Table 1). 3.2

Variation Characteristics of Pressure Gradient in Mainstream Line

Firstly, the maximum starting pressure gradient of T14 block is 0.06 MPa/m, the minimum starting pressure gradient of T14 block is 0.003 MPa/m, which are measured by laboratory experiments, so the pressure gradient range of nonlinear flow zone is 0.003–0.06 MPa/m. Furthermore, according to the method in Sect. 2.2, the pressure gradient distribution between wells in block T14 is determined (Fig. 2). The pressure gradient distribution in the mainstream line between injection and production wells has the following two aspects: Firstly, the high value of pressure gradient between wells is mainly concentrated in a very small area near oil and water wells. The maximum pressure gradient is mainly within 50 m of injection wells, and the average value is 0.337 MPa/m; the next is within 20 m near the oil well, and the average value is 0.230 MPa/m. The pressure gradient in the rest region of the wells is small, and the average value is 0.034 MPa/m (Table 2). Secondly, the pressure gradient is obviously affected by well spacing, and the minimum pressure gradient is biased toward the oil production well side. The greater the well spacing becomes, the lower the pressure gradient becomes, and it has more difficulty to put the reservoir into production. For example, the injection well spacing of A56-50 well is maximum and reaches 288 m, which leads to the lowest pressure gradient at the same relative position between oil and water wells. The minimum pressure gradient between the wells is reached at 190 m from the injection well, and the average value is 0.0151 MPa/m. However, this point is not located in the middle of oil and water wells, but is skewed to oil wells and distributed unsymmetrically. 3.3

Nonlinear Flow Plane Distribution

The pressure gradient of two typical well groups A56-54 and T236-216 in T14 block has been calculated. In order to determine the pressure gradient of the well-less control area near the fault, five additional virtual wells are increased. The range of nonlinear flow zone is determined by coupling on the plane (Fig. 3). The main flow zone between oil and water wells is nonlinear flow, and the area ratio is 60.1%. Following the law of nonlinear flow, the flow velocity is small, which is the main reason for the rapid decline of the fault block (the initial annual natural decline rate is 17.6%). The next step is to improve the development effect by well pattern encryption. The quasilinear flow zone is very low, mainly within 50 m around the injection well and 20 m around the oil well, and the controlled area ratio is 4.7%. The flow in this area follows the law of quasilinear flow, and the flow velocity is great. In the area of the back of oil–water well line, the pressure gradient is usually lower than the minimum starting pressure gradient, it is mainly dead oil area, and the area ratio is 35.2%. The crude oil in the region is difficult to flow, it is the remaining oil-rich region, and a digging potential well can be deployed near the fault.

A56-54

A56-54

A56-50

A52-50

T236-216 T216

A56-52

T14

Well number

Well group

Injection well Production well production well Injection well Production well Production well

Well type

6.7

12.3

4.6

42.0

31.3

2.1

8.8

7.0

32.0

2.0

3.8

31.2

Bottom hole Water pressure/Mpa injection rate or production of fluid (t/d)

1.2

3.3

6.0

7.1

Water cut (%)

288

201

189

208

Distance between injection well and production well (m)

190

120

120

150

Distance between minimum pressure gradient point and injection well (m)

Table 1. The basic information of T14 block

1.319

1.397

1.004

0.930

36.8

26.9

Average Apparent perforation mobility (mD/mPa s) thickness (m)

0.003

0.003

Minimum starting pressure gradient (MPa/m)

0.060

0.060

Maximum starting pressure gradient (MPa/m)

The Nonlinear Flow Analytical Model and Its Field Use 7

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H. Jia et al. 10

T14 A56-52 1

A52-50 A56-50

0.1

0.01

0

50

100

150

200

250

300

Distance from injection well/m

Fig. 2. The distribution of pressure gradient of T14 block Table 2. The cross-well fluidity and pressure gradient of T14 block Well Well Bottom group number hole flow pressure (MPa)

A5654

Bottom flow pressure of water injection well (MPa) 31.2

Cross-well apparent permeability to viscosity ratio (mD/mPa s)

T14 3.8 0.930 A562.0 1.004 52 T236- A524.9 31.3 1.397 216 50 A561.3 1.319 50 Average 1.163 Remark R is injection-production spacing, m rM is the distance from the well, m

Average pressure gradient (MPa/m) Near water Remaining Near injection production regions well 50 < rM < R well rM  50 m −20 m rM  R −20 m 0.384 0.359

0.034 0.042

0.195 0.252

0.297

0.037

0.258

0.307

0.021

0.216

0.337

0.034

0.230

4 Conclusion (1) According to the superposition principle of potential, a nonlinear analytical model of flow in ultra-low-permeability reservoirs is established, which is under the condition of simultaneous production of multiple wells with unequal production rate. According to the production dynamic data, the pressure gradient distribution on the mainstream line between production wells is determined. By adding virtual

The Nonlinear Flow Analytical Model and Its Field Use

9

Fig. 3. The distribution of nonlinear flow zone

wells, the prediction accuracy of pressure gradient near faults and areas with low well control degree can be improved. Finally, the nonlinear flow area can be determined by coupling the pressure gradient of each point on the plane. (2) The new method has been applied in the field of T14 block. There are three aspects about the pressure gradient and nonlinear flow characteristics. Firstly, the high value of the inter-well pressure gradient is mainly concentrated in the small area near the oil–water well; secondly, the pressure gradient is obviously affected by the well spacing, and its lowest value is inclined to one side of the oil well; thirdly, the nonlinear flow zone in ultra-low-permeability reservoirs is the main reason for the rapid decline of production. Acknowledgements. The authors thank Li Bin at Hailar oilfield for providing the data of T14 block.

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References 1. Yan Q, He Q, Wei L, et al. A laboratory study on percolation characteristics of single phase flow in low-permeability reservoirs. J Xi'Petroleum Institute. 1990;5(2):1–6. 2. Huang Y. Nonlinear peecolation feature in low permeability reservoir. Special Oil Gas Reserv. 1997;4(1):9–14. 3. Chengyuan L, Jian W, Zhigang S. An experimental study on pressure gradient of fluids flow in low permeability sandstone porous media. Petrol Explor Develop. 2002;29(2):86–9. 4. Wang D, Shi D, Li X, et al. The main challenges and the reasonable well spacing for the development of low-permeability sandstone reservoirs. Petrol Explor Develop. 2003;30(1): 87–9. 5. Shi D. Flow state distribution of areal radial flow in low permeability sandstone reservoir. Petrol Explor Dev. 2006;33(4):491–4. 6. Yang R, Jiang R, Liu S, et al. Numerical simulation of nonlinear seepage in ultra-low permeability reservoirs. Acta Petrolei Sinica. 2011;32(2):299–306. 7. Zhengming Y, Rongze Y, Zhixin S. Numerical simulation of the nonlinear flow in ultra-low permeability reservoirs. Petrol Explor Dev. 2010;37(1):94–8. 8. Renfeng Y, Ruizhong J, Shihua L. Demonstration of essentiality of considering nonlinear flow in low permeability reservoir. Fault-Block Oil Gas Field. 2011;18(4):493–7. 9. Renfeng Y, Ruizhong J, Junshu S, et al. Study on nonlinear flow mechanism in low permeability porous medium. Peroleum Geol Recovery Effi. 2011;18(2):90–3. 10. Xu, J., Jiang, R., Xie, L., et al.: Non-darcy flow numerical simulation for low-permeability reservoirs, 2012; SPE154890. 11. Yu R, Bian Y, Zhou S, et al. Nonlinear flow numerical simulation of low-permeability reservoir. J Central South Univ Technol. 2012;19(7):1980–7. 12. Yu S, Zhengming Y, Yanzhang H. Study on nonlinear seepage flow model for lowpermeability reservoir. Acta Petrolei Sinica. 2009;30(5):731–4. 13. Deng Y, Liu C. Mathemat ical model of nonlinear flow law in low permeability porous media and its application. Acta Petrolei Sinica. 2001;22(4):72–7. 14. Jiang R, Li L, Xu J. A nonlinear mathematical model for low-permeability reservoirs and well-testing analysis. Acta Petrolei Sinica. 2012;33(2):264–8. 15. Lijuan S, Fan W, Weihua Z. The study and application of reservoir start-up pressure. Fault Block Oil Gas Field. 1998;5(5):31. 16. Xianke H, Cheng C. The Calculating Method for Effectively Producing Injection-Production Well Spacing of Low Permeability Reservoirs. Xing Jiang petroleum geology. 2006;27(2): 216–8. 17. Xianke H, Cheng C. Establish effective displacement pressure system in low permeability oilfield. Special Oil Gas Reservoirs. 2006;13(2):56–7. 18. Jianguo Z, Guanglun L, Yanyu Z.: The flow law at low speed, In: Dongying SD, editor. ‘Fluid mechanics in hydrocarbon reservoir’. 1st ed. The press of China University of Petroleum, 1998. pp 12–3.

Research on Low Damage Drilling Fluids and Application in Low Permeability Reservoirs of Shengli Oilfield J. Y. Liu(&), E. D. Chen, and X. L. Li Drilling Technology Research Institute of Shengli Petroleum Engineering Corporation Limited, Sinopec, Dongying, China [email protected]

Abstract. The low permeability reservoirs in Shengli oilfield is featured by large buried depth, poor physical properties, strong diagenesis, and heterogeneity, and there exist serious water sensitivity and water lock damage during the drilling process, which significantly restricts the exploration efficiency of low permeability reservoirs. In order to solve the reservoir protection problems, novel polymer plugging agent (SLRP) and water lock prevention agent (SLWB) were optimized and characterized in detail, and the polymer plugging agent (SLRP) could work synergistically with water lock prevention agent (SLWB) to impart reservoir protection performance due to film-forming shielding effect and low surface tension. The low damage water-based drilling fluids were also established, and the results indicated that low damage water-based drilling fluids exhibited excellent reservoir protection performance with permeability recovery of above 90%, and filtrate surface tension is 18.5 mN/m. The low damage water-based drilling fluids have applied in the Bin 425 block and Da 43 block for more than 40 wells. It is concluded that acid fracturing would not be necessary to low permeability reservoirs before well production due to excellent reservoir protection performance of the low damage water-based drilling fluids, and average daily production per well could be increased to 7.63 t/d. Keywords: Shengli oilfield
Low permeability reservoirs Reservoir protection
Drilling fluid
Field application




Copyright 2018, Shaanxi Petroleum Society. This paper was prepared for presentation at the 2018 International Field Exploration and Development Conference in Xi’an, China, September 18–20, 2018. This paper was selected for presentation by the IFEDC Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the IFEDC Committee and are subject to correction by the author(s). The material does not necessarily reflect any position of the IFEDC Committee, its members. Papers presented at the Conference are subject to publication review by Professional Committee of Petroleum Engineering of Shaanxi Petroleum Society. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of Shaanxi Petroleum Society are prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of IFEDC. Contact email: [email protected]. © Springer Nature Singapore Pte Ltd. 2020 J. Lin (ed.), Proceedings of the International Field Exploration and Development Conference 2018, Springer Series in Geomechanics and Geoengineering, https://doi.org/10.1007/978-981-13-7127-1_2

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1 Introduction With the promotion of oil and gas development around the world, the exploration scope has been gradually extended to complicated geological reservoirs, such as deep or ultra-deep, unconventional, tough reservoirs, and low or ultra-low permeability reservoirs which take up the dominate positions (  60%) of undeveloped reservoirs, which could constitute a secondary source of fossil energy to prolong the oil and gas supply in the future [1]. Shengli oilfield, the largest oilfield of SINOPEC, is abundant in low permeability reservoirs such as Bonan, Zhuangxi, Shanghe, and Chunhua block, and it has a great potential for exploration and development. However, to date, production of these low permeability reservoirs has been hampered by the economic risks related to the uncertainties in their size, shape, spatial distribution, and reservoir properties. Compared with similar reservoirs in China, the low permeability reservoirs in Shengli oilfield are featured by large buried depth, poor physical properties, strong diagenesis, and heterogeneity [2–4], and there exist serious water sensitivity damage and water lock during the drilling process and average oil and gas recovery efficiency is only 18.6%, which significantly restricts the exploitation efficiency and benefits of low permeability reservoirs [5]. Reservoir protection is the constant subject of petroleum engineering technology, and reservoir damage would be inevitable throughout the whole development process of oilfield, especially the low permeability reservoirs. While pores and throats of low permeability reservoirs are very tiny, they have a significant influence on flow behavior in those reservoirs. Stronger liquid–solid interaction within finer pore throats having a large interface area and abundant hydrophilic clay tends to be unfavorable to reservoir protection [6]. If there are no effective reservoir protection measures, serious water sensitivity damage and water lock would be inevitable during the drilling process, which significantly restricts the exploitation efficiency and benefits of low permeability reservoirs. In order to solve the reservoir protection problems of low permeability reservoirs in Shengli oilfield, we attempted to optimize the novel polymer plugging agent (SLRP) and water lock prevention agent (SLWB), and they are introduced as potential low permeability reservoirs protection agents in water-based drilling fluids. The novel polymer plugging agent (SLRP) and water lock prevention agent (SLWB) could work synergistically to impart reservoir protection performance due to film-forming shielding effect and low surface tension. Furthermore, the low damage water-based drilling fluids were also established and applied in the Bin 425 block and Da 43 block for more than 40 wells. It is concluded that the low damage water-based drilling fluids displayed excellent reservoir protection performance, and it could be priority alternatives to low permeability reservoirs exploration in Shengli oilfield.

2 Potential Reservoir Damage Analysis The Da 43 block of Yibei oilfield, located in the northwest of Shengli oilfield, is the typical high pressure and low permeability reservoirs, and the target reservoirs are distributed in second and fourth member of the Shahejie formation (Es2/Es4).

Research on Low Damage Drilling Fluids …

13

The second member of the Shahejie formation belongs to shore shallow lake beach and dam facies and is featured by medium porosity and low permeability reservoirs with average porosity of 21% and average permeability of 29 mD. The fourth member of the Shahejie formation belongs to shore lake facies and is featured by medium porosity and low permeability reservoirs with average porosity of 18% and average permeability of 20 mD. According to the reservoir characteristics of typical low permeability reservoirs in Shengli oilfield, potential reservoir damage consists of solid invasion, water lock, sensitivity damage, and formation of water scaling. Solid invasion. The formation of buried depth of target reservoirs, Es2 and Es4 formation, ranges from 2700 to 2900 m, and the reservoir lithology is mainly siltstones, featured by unconsolidated and medium porosity. The harmful solid in the drilling fluids would invade into the target reservoirs under the overbalanced drilling fluid pressure, and depositing and bridging happen at the throats unavoidably, which would lead to plugging and reservoir damage [7]. 2.1

Water Lock

Pores and throats in low permeability reservoirs are very tiny, and water lock would be the main damage of low permeability reservoirs due to strong capillary effect, which could significantly decrease the oil or gas permeability of low permeability reservoirs. The lower the permeability and the smaller the pore-throat radius, the easier the formation of water lock damage, and it is difficult to be eliminated [8–10]. 2.2

Sensitivity Damage

The interface area of low permeability reservoir rocks is quite large, and interaction between pore surface and fluid is strong, especially abundant hydrophilic clay in the pores. Its clay minerals are dominated by kaolinite, with no montmorillonite but some mixed-layer illite/smectite. The sensitivity damage mechanisms, especially water sensitivity damage, include effective throat radius reduction caused by expanding clays, pores, and throat-plugging caused by of fine particles migration [11]. 2.3

Formation of Water Scaling

The formation of water belongs to sodium bicarbonate type with salinity of above 16000 mg/L. If drilling fluid is not compatible with formation of water, chemical precipitation reaction would occur, such as calcium carbonate precipitation reaction, which would plug the pore or pore throat and decrease the effective permeability of low permeability reservoirs. Text including equations must be typed single spaced in any of the following font types: Times, Times Roman, Times New Roman, or Symbol. Use 10 pt for the text, 12 pt for the headings, 11 pt for subheadings, and 18 pt for the title. The title should be typed in capital letters and centered. The text should be set in two columns that are 8.8 cm wide and justified and separated by a margin of 0.4 cm.

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3 Low Permeability Reservoirs Protection Agents Based on the potential damage analysis above, the water sensitivity, water lock, and solid invasion damage take up the dominate positions of low permeability reservoir damage, and shield temporary plugging and low interfacial tension should be deployed to reduce the reservoir damage induced by solid or filtrate invasion. Therefore, novel polymer plugging agent (SLRP) and water lock prevention agent (SLWB) were optimized and characterized in detail, and the polymer plugging agent (SLRP) could work synergistically with water lock prevention agent (SLWB) to impart reservoir protection performance due to film-forming shielding effect and low surface tension. 3.1

Polymer Plugging Agent (SLRP)

Polymer plugging agent (SLRP), a novel polymer plugging agent based on temporary shielding plugging theory, was developed by emulsifier polymerization of styrene (St), butyl acrylate (BA), and 2-acrylamide-2-methyl propane sulfonic acid (AMPS). Polymer plugging agent (SLRP) could work synergistically with superfine calcium carbonate to form a thin, plastic, and compacted sealing film, thus preventing solid or filtrate invasion. The SLRP samples were reacted with the 3% pre-hydrated bentonite slurry and stirred for 30 min. After maintenance for 24 h, the rheological and filtration properties were measured, and the compatibility or applicability of SLRP in the water-based drilling fluid was investigated based on the rheological and filtration properties comparison of fluids with or without SLRP. It could be seen from Table 1 that adding SLRP would not have an adverse effect on rheological properties of water-based drilling fluids, and it is beneficial to decrease the API filtration volume on the contrary. Table 1. Effect of SLRP on rheological and filtration properties of drilling fluids SLRP(%) 0 0.2 0.5 1.0 3.0 5.0

AV (mPa s) 6.5 7.5 8.0 8.5 9.5 10.0

PV (mPa s) 4.5 6.0 6.0 7.5 7.5 8.0

YP (Pa) 2.0 1.5 2.0 1.0 2.0 2.0

API FL (mL) 34.0 21.0 18.0 16.4 13.8 9.6

The reservoir protection performance of SLRP was investigated quantitatively based on the variation of permeability recovery by core flow experiment. The fully preserved rock samples used in this study was cored from ES4 formation of the Da 43 block of Yibei oilfield. The experimental fluids were 3% pre-hydrated bentonite slurry with 3% SLRP. It could be seen from Table 2 that SLRP exhibits good plugging ability with core plugging ratio (PR) of above 97%, and after core being cut off certain length, SLRP also exhibits good reservoir protection ability with core permeability recovery

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(Rd) of above 95%. As indicated in Fig. 1, compared with the bentonite slurry, adding SLRP is beneficial to forming a thin, plastic, and compacted sealing film and protecting low permeability reservoir from solid or filtrate invasion damage. Table 2. Core flow experiment results of SLRP NO K1 (mD) 1# 14.2 2# 22.5 3# 3.24 Note K1—original core K2—core permeability K3—core permeability

K2 (mD) PR (%) 0.17 98.8 0.43 98.1 0.72 97.7 permeability after interacting with fluids after cutting certain length

LC (mm) 3.0 3.1 3.1

K3 (mD) 14.0 21.9 30.3

Rd (%) 98.7 97.4 96.9

Fig. 1. Optical microscope photographs of API filter cake: bentonite(left) and SLRP(right)

3.2

Water Lock Prevention Agent (SLWB)

Due to tiny pores or throats and strong capillary effect, water lock damage would be inevitable during the exploitation and development of low permeability reservoirs [12]. Based on the film-forming plugging of polymer plugging agent (SLRP), decreasing interfacial tension and altering rock wettability is one of the most effective methods to reduce water lock damage. Therefore, novel water lock prevention agent (SLWB) was optimized, which consists of a fluorocarbon surfactant and a hydrocarbon surfactant. Contact angle measurement was carried out to evaluate the effect of water lock prevention agent (SLWB) on the core rock wettability. The natural rock sample, cored from ES4 formation of the Da 43 block of Yibei oilfield, was immersed in the 10% SLWB solution for 4 h and air-dried for 24 h. The original core was adopted for comparison. Then, the drop images were taken with a high-resolution camera (HARKE-SPCA), and contact angles were calculated with specific software. The testing fluids consist of deionized water, oilfield wastewater, hexadecane, and crude oil. It could be seen from Table 3 that the contact angles of original cores using deionized water, oilfield wastewater, hexadecane, and crude oil are 2.52°, 10.62°,

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2.20°, and 35.35°, indicating a favorable hydrophilicity. After immersed in 10% SLWB solution, contact angles were significantly increased no matter what testing fluids used in contact angle measurement, and the core rock wettability was altered from favorable hydrophilicity to hydrophobicity, thus preventing filtrate invasion into the low permeability reservoir and reducing the water lock damage and clay swelling. Table 3. Effect of SLWB on the core rock wettability Testing fluids Deionized water Oilfield Wastewater Hexadecane Crude oil

Contact angle (°) Original 10% SLWB 2.5 139.8 10.6 122.3 2.2 65.5 35.4 85.7

Interfacial tension measurement was also carried out to evaluate the ability of water lock prevention agent (SLWB) to decrease interfacial tension of fluid filtrate. Six conventional surfactants were chosen for comparison. It could be seen from Table 4 that compared with conventional surfactants with the same concentration, SLWB obtains the minimum interfacial tension, which is beneficial to reducing water lock damage and improving fluid filtrate backflow.

Table 4. Interfacial tension measurement of different surfactants Surfactants SLWB ABS OP-10 Tween-40 Tween-80 Span-60 ABSN

Concentration (%) 0.3 0.3 0.3 0.3 0.3 0.3 0.3

Interfacial tension (mN m−1) 8.26 26.06 26.59 30.25 41.36 29.56 25.50

4 Low Damage Water-Based Drilling Fluids Polymer water-based drilling fluids were widely used in the low permeability reservoirs development in Shengli oilfield, but it could not meet the demand for reservoir protection for lack of effective polymer plugging agents. On the basis of conventional polymer water-based drilling fluids (CPWM), low damage water-based drilling fluids (LDWM) were established through adding novel polymer plugging agent (SLRP) and water lock prevention agent (SLWB). The rheological, filtration properties, and reservoir protection performance of low damage water-based drilling fluids were

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evaluated in detail using conventional polymer water-based drilling fluids for comparison, and reservoir protection mechanism was also investigated in this study. The water-based drilling fluids tested were prepared using standard commercial additives, and the trade names of additives were replaced by generic description. The formulation of the tested drilling fluid is listed in Table 5. Table 5. Formulation of tested drilling fluids Additives

CPWM % (m/v) 3.0 0.2 2.0 3.0 2.0 2.0 – – –

Bentonite Polyacrylamide Potassium humate Phenolaldehy resin Walchowite Sulfonated asphalt. Amino silicone glycol SLRP SLWB

4.1

LDWM % (m/v) 3.0 0.2 2.0 3.0 2.0 2.0 2.0 3.0 0.3

Rheological and Filtration Properties

Table 6 shows the rheological and filtration properties of CPWM and LDWM before and after hot rolling at 120 °C for 16 h. It could be concluded that compared with CPWM, adding SLRP and SLWB would not have an adverse effect on rheological and filtration properties, and low damage water-based drilling fluids (LDWM) exhibit stable rheological and filtration properties before and after hot rolling, which could satisfy the field requirements. What’s more, the interfacial tension of LDWM filtrate is much lower than that of CPWM due to usage of SLWB, and it is beneficial to reduce water lock damage. Table 6. Rheological and filtration properties of drilling fluids Fluids CPWM LDWM

AV (mPa s) 39.0 34.5 41.5 34.5

PV (mPa s) 28.0 25.5 30.0 25.0

YP (Pa) 11.0 9.0 11.5 9.5

API FL (mL) 3.4 4.2 3.4 4.5

Interfacial tension (mN m−1) – 57.8 – 18.5

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Reservoir Protection Performance

The core flow tests, CT scan core analysis (CT), and formation of water compatible tests were adopted to comparatively evaluate the reservoir protection performance of CPWM and LDWM fluids. The reservoir protection performance of CPWM and LDWM fluids was investigated with the core plugging ratio (PR) and core permeability recovery (Rd) as evaluation parameters. The fully preserved rock samples used in core flow experiments were cored from ES4 formation of the Da 43 block in Yibei oilfield. The Core flow experiment results of CPWM and LDWM are reported in Table 7. The permeability of natural cores all decreased after interacting with CPWM and LDWM fluids, and the plugging ratio of LDWM (above 90%) was much higher than CPWM fluids. After being cut a certain length, the permeability of natural cores all recovered to some extent, and the permeability recovery of LDWM (above 95%) was also higher than CPWM fluids. It is concluded that low damage water-based drilling fluids (LDWM) could form a thin and tight sealing film near the wellbore to prevent solid deep invasion into the reservoirs and protect low permeability reservoir from solid plugging damage. Table 7. Core flow experiment results of SLRP NO CPWM

K1 (mD) K2 (mD) PR (%) 117.3 45.6 61.1 89.8 39.7 55.8 LDWM 92.4 7.3 92.1 95.8 9.5 90.1 Note K1—original core permeability K2—core permeability after interacting with fluids K3—core permeability after cutting certain length

LC(mm) 3.0 3.0 3.0 3.0

K3 (mD) 55.9 44.2 88.3 91.0

Rd (%) 47.7 49.3 95.6 95.0

The pore structure of natural cores before and after core flow tests was quantitatively characterized by CT scan core analysis instrument, and porosity of twodimensional slices extracted from the full three-dimensional digital cores interacting with CPWM or LDWM was calculated with specific software. Figures 2 and 3 present the porosity measurement of different two-dimensional slices before and after tests. As indicated in Figs. 2 and 3, after interacting with CPWM, the porosity of natural cores significant decreased within the length of 30 mm from polluted part, that is to say, the drilling fluid invasion depth or damage depth was much more than 30 mm. On the contrary, after interacting with LDWM, the porosity of natural cores decreased only within the length of 15 mm from polluted part, and the porosity was nearly the same within the length of 15–30 mm. It could be visually concluded from Figs. 4 and 5 that LDWM could effectively protect low permeability reservoir from solid or fluid invasion damage, and the core slice porosity at 30 mm length remained nearly constant. The flocculation and precipitation method was adopted to investigate the formation of water compatible of LDWM fluids. According to formation of water ionic

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Fig. 2. Porosity measurement of different three-dimensional core slices using CPWM

Fig. 3. Porosity measurement of different three-dimensional core slices using LDWM

composition and salinity of ES4 formation of the Da 43 block, simulated formation of water was prepared as follows: potassium chloride (20 g), sodium chloride (55 g), magnesium chloride (4.5 g), and calcium chloride (5.5 g) were dissolved in deionized water (1000 mL) with continuous stirring for 0.5 h. Then, API filtrate of LDWM fluids was mixed with simulated formation of water of the same volume with continuous stirring for 0.5 h and quiescent settling for 24 h. As indicated in Fig. 6, LDWM filtrate has good compatibility with formation of water, and no flocculation or precipitation

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Fig. 4. Core slices photographs: original (left), interacting with CPWM (right)

Fig. 5. Core slices photographs: original (left), interacting with LDWM (right)

exists in the mixture of simulated formation of water and LDWM filtrate, thus preventing formation of water scaling and solid plugging damage.

5 Field Application The low damage water-based drilling fluids (LDWM) were successfully applied in Bin 425 block and Da 43 block for more than 40 wells. The Da 43 block of Yibei oilfield, typical high pressure and low permeability reservoirs of Shengli oilfield, is taken as an example to introduce the field test results of low damage water-based drilling fluids (LDWM). Polymer water-based drilling fluids were widely used in the early stages of exploration and development in the Da 43 block, but it could not meet the demand of reservoir protection with average daily production per well of only 2.7 t/d even after acid fracturing operation. In order to increase the output of the low permeability reservoirs, before drilling into the ES4 reservoirs, conventional polymer water-based drilling fluids (CPWM)

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Fig. 6. Photographs of formation of water (left) and formation of water with drilling fluid filtration (right)

were converted to low damage water-based drilling fluids (LDWM) to effectively protect low permeability from solid invasion and water lock damage. It was concluded that the low damage water-based drilling fluids displayed stable rheological and filtration control behavior, and no complex situations exist during the drilling process, which could satisfy the field requirements. Due to good lubrication ability of low damage water-based drilling fluids, the average drilling period was significantly shortened by 11.73 d that is beneficial to decreasing soaking time in drilling fluids and reducing reservoir damage. As indicated in Table 8, the low damage water-based drilling fluids also exhibited excellent reservoir protection performance, and acid fracturing would not be necessary to low permeability reservoirs before well production, and average daily production per well could be increased from 3.32 to 7.63 t/d. The field test results confirmed that the low damage water-based drilling fluids could be priority alternatives to low permeability reservoirs exploration in Shengli oilfield.

Table 8. Well production comparison using different drilling fluids Fluids CPWM

LDWM

Well X366 X384 X392 X346 X395 X381 X393 X394

Acid fracturing Yes Yes Yes Yes No No No No

Flowing No No Yes Yes Yes Yes Yes Yes

Production (t d−1) 3.7 3.1 4.2 2.3 9.5 6.6 7.5 6.9

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6 Conclusions The polymer plugging agent (SLRP) and water lock prevention agent (SLWB) were optimized and characterized in detail as low permeability reservoir protection agents in water-based drilling fluids. The polymer plugging agent (SLRP) could internally bridge and seal pore or pore throats and finally form a thin and tight sealing film near the wellbore, which could prevent solid or filtrate invasion. The water lock prevention agent (SLWB) could alter rock wettability and decrease interfacial tension to reduce water lock damage through chemical adsorption. Furthermore, the low damage waterbased drilling fluids (LDWM) were established based on the cooperative reservoir protection performance of polymer plugging agent (SLRP) and water lock prevention agent (SLWB). Low damage water-based drilling fluids (LDWM) were successfully applied in Bin 425 block and Da 43 block for more than 40 wells. The field tests results indicated that low damage water-based drilling fluids (LDWM) exhibited excellent reservoir protection performance, and acid fracturing would not be necessary to low permeability reservoirs with average daily production per well of 7.88 t/d. The low damage water-based drilling fluids (LDWM) could be priority alternatives to low permeability reservoirs exploration in Shengli oilfield. Acknowledgements. We would like to thank the financial support from China Postdoctoral Science Foundation (2017M612344), Shandong province postdoctoral innovation projects (201703044).

References 1. Liu JY, Qiu ZS, Huang WA, Xing XJ, Luo Y. Experimental study on stress sensitivity in reservoirs with different permeability. J China Univ Petrol (Edition of Natural Science). 2014;38(2):86–91. 2. Zhao JZ, Xue YZ, Li GR. Formation damage control for low-permeability reservoir during drilling operation in Shengli Oilfield. J China Univ Petrol. (Edition of Natural Science). 2007;31(3):148–51. 3. Li Y, Cao G. Development technology for low-permeability sandstone reservoir in Shengli Oilfield. Petrol Explor Develop. 2005;32(1):123–6. 4. Li XL, Chen ED. Research on synergistic effect drilling fluid and acting mechanism in low permeability reservoir. Drilling Fluid Completion Fluid. 2013;30(5):18–21. 5. Zhao X, Qiu ZS, Huang WA, Wang ML. Mechanism and method for controlling lowtemperature rheology of water-based drilling fluids in deepwater drilling. J Petrol Sci Eng. 2017;154:405–16. 6. Zhao X, Qiu ZS, Wang ML, Huang WA, Zhang SF. Performance evaluation of a highly inhibitive water-based drilling fluid for ultralow temperature wells. J Energy Res Technol. 2018;140(1):1–6. 7. Wu XH, Pu H, Zhu KL, Lu S. Formation damage mechanisms and protection technology for Nanpu nearshore tight gas reservoir. J Petrol Sci Eng. 2017;158:509–15. 8. Fan WY, Shu Y, Li L, Yan JN. Researches on the water block in low permeability reservoir and minimized-reservoir-damage drilling fluid technology. Drilling Fluid Completion Fluid. 2008;25(4):16–9.

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9. Wei MW, Xue YZ, Li GR, Lan Q, Zhang JH. Research progress in water block removal. Drilling Fluid Completion Fluid. 2009;26(6):65–8. 10. Li G, Cai WQ, Meng YF, Wang L, Wang LM, Zhang XB. Experimental evaluation on the damages of different drilling modes to tight sandstone reservoirs. Natural Gas Ind B. 2017;4 (4):256–63. 11. Zhao F, Tang HM, Meng YF, Li G, Xing X. Damage evaluation for water-based underbalanced drilling in low-permeability and tight sandstone gas reservoirs. Petrol Explor Dev. 2009;36(1):113–9. 12. Fan HM, Lyu J, Zhao JB, Zhan SZ, Fan, HJ, Geng J, Dai CL, Kang WL. Evaluation method and treatment effectiveness analysis of anti-water blocking agent. J Natural Gas Sci Eng. 2016;33:1374–80.

Multistage Fractures Optimum of Different Cluster Wells in Tight Gas Reservoirs Shihua Liu(&) SINOPEC Research Institute of Petroleum Engineering, Beijing, China [email protected]

Abstract. At present, many influenced factors were not taken into consideration during optimum design for multistage fractures optimum design for cluster horizontal wells, which leads to lower accuracy, even error decision. In this paper, taking pressure sensitive effect, high-velocity non-Darcy effect, fracture conductivity decreasing along with time, and fracturing fluid leak off into consideration, four kinds of cluster horizontal wells pattern were studied including line pattern with two wells, parallel pattern, K pattern, and X pattern with four wells. The greatest innovation was that the optimal fracture parameters could be obtained according to the quantitative parameters plate without timeconsuming simulation. The interference between different well branches in lineshaped dual-well cluster mainly appears between the toe ends. The fractures distributed like W shape could reduce investment, and the long fractures at both ends are best. For parallel four-well cluster wells, the fractures should be staggered distributed and W shape distributed, long fractures are distributed at toe ends, and the fracture length/well interval ratio should be between 0.3 and 0.4. Furthermore, the most optimal fracture length increases with permeability decreasing. The “K type” and “X type” cluster wells need longer fracture length, so the out end fracture length needs to be longer. Keywords: Multistage hydraulic fracturing Non-Darcy flow


Cluster horizontal wells


Copyright 2018, Shaanxi Petroleum Society. This paper was prepared for presentation at the 2018 International Field Exploration &Development Conference in Xi’an, China, September 18–20, 2018. This paper was selected for presentation by the IFEDC Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the IFEDC Committee and are subject to correction by the author(s). The material does not necessarily reflect any position of the IFEDC Committee, its members. Papers presented at the Conference are subject to publication review by Professional Committee of Petroleum Engineering of Shaanxi Petroleum Society. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of Shaanxi Petroleum Society are prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of IFEDC. Contact email: [email protected]. © Springer Nature Singapore Pte Ltd. 2020 J. Lin (ed.), Proceedings of the International Field Exploration and Development Conference 2018, Springer Series in Geomechanics and Geoengineering, https://doi.org/10.1007/978-981-13-7127-1_3

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1 Introduction In recent years, natural gas gets more and more attention as a kind of clean energy. But as the natural gas industry keeps further exploration and development, conventional natural gas resources have been gradually running out; therefore, more and more tight gas reservoirs were put into production. Actually, the tight gas reserve is abundant, and most of them are located in a tough environment or complexed terrain. Cluster well pattern is featured with land conservation, relocation reduction, convenience in united management, etc. and is gradually drawing attention. But the natural productivity is very low for tight gas reservoirs. Generally, it needs artificial fracturing to improve the productivity. The advantage of cluster wells is further enlarged. Firstly, it is easier to conduct unified management on ground construction. In addition, since overall fracture of cluster wells is conductive to form inducing fractures and maximize fracturing transforming volume, etc., it has been widely promoted in recent years. The optimum design in cluster wells’ staged fracturing and single horizontal well fracturing is different. The well group shall be an integrated unit to be optimized and make maximum control reserves and recovery factor of well groups. However, there are still some issues existing on tight gas cluster wells fracturing as follows [1–10]. (1) Current studies on cluster well fracturing mainly focus on flooring work and fracturing field construction, etc. But there are no systematic conclusions in fracture parameters’ optimum design of cluster wells. (2) Comparing with the conventional gas reservoir, the tight gas reservoir is more subtle in pore throats. At the same time, a complex fracture system is generated after fracturing. It leads to a more complicated seepage flow, such as stress sensitive effect, non-Darcy flow in fractures, start-up pressure in matrix, and voltage-sensitive effect. Currently, not all factors are considered in cluster well fracture design. (3) Cluster wells pattern include different types such as two-well type, parallel fourwell type, K type, and X type. Different types should have different cluster well fracturing optimization parameters. Currently, there is no clear conclusion for the optimal fracturing parameters. This article systematically considers percolation mechanisms such as non-Darcy flow in the pore throat of tight gas reservoirs, the water lock effect, high-velocity non-Darcy flow in fractures, and voltage-sensitive effects. It comes up with recommended parameters for cluster wells optimum design in different types, to guide fracturing operation, reduce fracturing cost, thus to further improve the comprehensive benefit in fracturing development of tight gas reservoir cluster wells.

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2 Methods 2.1

Complex Seepage Mechanism in Tight Sandstone Gas Reservoirs with Artificial Fracturing

Different from the conventional sandstone gas reservoir, the tight sandstone gas reservoir is complex in its seepage mechanism. Before the optimum design study of fracturing parameters, its complex seepage mechanism needs to be analyzed, to try best to achieve the best development effect of optimal fracturing parameters and reduce investment risks. This article discusses from five aspects: non-Darcy flow in matrix pores, water block effect, stress sensitivity, high-velocity non-Darcy flow in man-made fracture, and fractures’ long-term flow conductivity. 2.1.1 Non-Darcy Flow in Matrix Pores of Tight Gas Reservoirs As to tight gas reservoirs, nanometer throat and micro-capillary pore throat are main channels for gas flow in tight sandstone gas reservoirs [2] (seeing Table 1). When the gas flows in tight pore throat, the resistance is far more than that in conventional sandstone gas reservoirs. Especially when the natural gas is flowing in un-hydrated sandstone with permeability less than 0.1 10−3 lm2, and water-bearing sandstone with permeability less than 1.0  10−3 lm2, there is relatively a large gas flow resistance and also a start-up pressure which leads to low-speed non-Darcy seepage flow(see Fig. 1). Water containing also exerts a great influence on core gas flow. Table 1. Pore throat types of different types’ sandstone gas reservoirs Pore throat types

Pore Throat radium (lm)

Nanometer pore throat Micro-capillary pore throat Capillary pore throat Super capillary pore throat

1.00

There may be three periods in tight gas reservoir transfusion (see Figs. 2 and Fig. 3): super low-speed nonlinear transfusion period, low-speed nonlinear transfusion period, and low-speed linear transfusion period [8]. Under the function of super lowpressure gradient, super low-speed nonlinear transfusion gets a terribly low speed and achieves an obvious gas slippage effect. With the increase in pressure gradient, the fluid velocity gradually increases, the slippage effect gradually weakens, and apparent

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27

1000000 100000 10000

f

1000 100 10

Darcy flow 1 0.0001

0.01

1

100

10000

Re

Flow Rate(mL/s)

Fig. 1. The application of Darcy’s law

2 1.8 1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 0

0

0.5

1

Pressure Gradient

1.5

2

MPa/cm

Fig. 2. Relation between tight gas flow rate and pressure gradient

permeability reduces. Though the gas breakthroughs the medium capillary pressure of pore throats under the role of the injection pressure and makes medium pore throat gradually engage in transfusion, pore throats in this level are rarely distributed, which makes the apparent gas permeability reduces with the increase in pressure. When the displacement pressure gradient keeps increasing, a stable gas flowing channel gradually forms. The apparent permeability gradually increases to be the absolute permeability, and the transfusion turns to be linear seepage. But its oppositely elongated line still has intersection points with the X-axis, which shows by starting-up pressure gradient. The related calculation model taking starting-up pressure and slippage effect into consideration is as follows: v¼

   ki b dp G 1þ p dx l

ð1Þ

v is gas flow velocity through porous media; ki is permeability; b is slippage effect factor; p is average formation pressure; ddpx is pressure gradient; G is starting-up pressure;

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Permeability(

10−3 μm2)

0.6 0.5 0.4 0.3 0.2 0.1 0

0

0.5

1

Pressure Gradient

1.5

2

2.5

MPa/cm

Fig. 3. Relation between tight gas reservoir permeability and pressure gradient

2.1.2 Water Lock Effect in Tight Sandstone Gas Reservoir The ultra-low porosity and permeability of tight gas reservoirs decide its super low natural productivity. Only after stimulation, measures such as fracturing transformation can gain economic benefits. From well drilling, well completion till man-made fracturing, it inevitably will contact with the aqueous phase. But after self-absorption of the aqueous phase, due to the super dense pore throats, the starting pressure of the aqueous phase is generally relatively large, and hard to flow back thoroughly, and then water lock damage occurs. Lots of scholars have studied influence factors of water lock damage [4], mainly including (1) pore structures. Generally, the smaller the pore throat radius, the greater the capillary pressure, the more obvious the aqueous phase trapping function, and the more serious the water lock damage. (2) Rock wettability. Hyper-tight sandstone is generally with strong water wettability, so water lock damage usually cannot be neglected. (3) Fluid property. The influence of the fluid property on water lock is a “double-edged sword.” On the one hand, the larger the fracturing fluid viscosity, the more difficult the flowback, and the more serious the water lock damage. On the other hand, the larger the fracturing fluid viscosity, the more difficult to enter into the reservoir stratum, and the smaller an impact. But due to high operating pressure in man-made fracturing, it generally can drive part of fracturing fluids into the reservoir stratum. (4) Fracturing operation differential pressure and operation time. In the fracturing process, since the bursting pressure of the stratum is required to be exceeded, there is generally a large differential pressure, and a deep invasion depth of the fracturing liquid. Besides, the longer the fracturing time, the deeper the invasion depth and more serious the water lock damage. And it is better to spend enough flowback time to make fracturing liquids flow back completely. In an optimum design of fracturing parameters, water lock damage in areas near wellbores needs to be considered, and the relative permeability curve needs to be amended (seeing Fig. 4). Water-sensitivity damage can also be handled in the similar way.

Multistage Fractures Optimum of Different Cluster …

Permeability Ratio( 10−3 μm2)

Frcture Fluid

29

Distilled Water

Low Sality Water

120 100 80 60 40 20 0

0

20

40

60

Sw

80

100

120

%

Fig. 4. Water lock damage test

Permeability( 10−3 μm2)

2.1.3 Stress Sensitivity of Tight Gas Reservoirs Tight gas reservoirs are generally with strong stress sensitivity. It is mainly because in the process of late diagenesis or overburden pressure increase in rocks, with the increase in effective stress, when particles cannot be compressed, particles become more and more tight to each other, pore space becomes more and more smaller, connectivity becomes worse and worse, and permeability becomes obviously reduced. When the pressure recovers, the permeability is hard to recover to the original level (seeing Fig. 5). 0.014 0.012 0.01 0.008 0.006 0.004 0.002 0 0

10

20

30

Confining pressure（MPa）

Fig. 5. Evaluation curve of reservoir stress sensitivity

The stress sensitivity is usually obvious in tight gas reservoir, not only for medium, but also the artificial fracture. The calculation model could be used as follows. kf ;m ¼ kfi;mi eaf ;m ðpi pÞ

ð2Þ

kf ;m is the permeability of fracture and matrix; kfi;mi is the initial permeability of matrix and fracture; af ;m is the stress sensitivity factor.

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2.1.4 High-Velocity Non-Darcy Flow in Artificial Fractures In tight gas reservoirs, gas finally flows to artificial fractures after seepage and then flows to the well bore. The fluid velocity around the well bore will be relatively large. Once it exceeds a certain Reynolds number, the inertial effect of gases generally cannot be neglected [7]. If calculating by default Darcy flow, it will lead to a high gas production rate in early stage (see Fig. 1). The oil sample is analyzed in this paper. And the high-speed seepage in the well bore is calculated according to the permeability rule of fluids in natural reservoirs. The gas reservoir is 11.5 m thick, the flow in the fracture is 50  104 m3/d, fluid density is q ¼ 0:81  103 g/cm3 , fluid viscosity is l ¼ 0:0205 mPa s, fracture permeability is Kf ¼ 100 lm2 , and fracture porosity is /f ¼ 0:0909. Reynolds number is calculated to be Re ¼ 2:939. The applicable limit of Darcy law is 0.022–0.290. Since the Reynolds number of seepage in fractures is far greater than the Reynolds number of applicable limit of Darcy law, the flow in fractures does not comply with classical Darcy law anymore. Many scholars have carried on researches from two aspects of experiments, and theory [10, 11], put forward a lot of nonlinear seepage model, of which Forchheimer Equation shows the non-Darcy percolation model is most widely used: dp l ¼ v þ bqg v2 dx k

ð3Þ

dp is pressure gradient; l is the viscosity of crude oil; K is the formation pero dx meability; v is gas flow velocity through tight gas porous media. qg is gas density; b is high-speed non-Darcy seepage factor. 2.1.5 Long-Term Flow Conductivity of Artificial Fractures Artificial fractures are the main flow path of the tight sandstone gas. The flow conductivity is a vital index to judge if the fracture is effective. So especially in fracturing design, usually the most concerned is the flow conductivity of fractures in early stage. But in actual production process, due to the impact of proppant embedment and falling off, liquid damage, and mutation ability, etc., the flow conductivity of artificial fractures keeps being reduced with the extension of the production time till invalidation. As to the tight sandstone gas, artificial fracturing of cluster well network is adopted. Due to more fracturing sections involved, the long-term flow conductivity of fractures may become a key factor [5, 6] to decide if it is with economic benefits and even decides the final optimization result. Thus, it needs to be fully considered in fracture optimum design. A long-term flow conductivity test analysis is conducted on the propping agent to be used in target oil fields, and the relation between flow conductivity ability level and time is as shown in Fig. 6.

Permeability Ratio(

10−3 μm2)

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31

1.2 1 0.8 0.6 0.4 0.2 0

0

50

100

150

200

250

Time(h)

Fig. 6. Fracture conductivity along with time change under 20 MPa closing pressure

Usually, the long-term flow conductivity could be regressed through the following three kinds of models: Logarithmic form, exponential form, and power product form. FRCD ¼ 1  d
ln t

ð4Þ

FRCD ¼ FRCDi
ect

ð5Þ

FRCD ¼ atb

ð6Þ

FRCDi —Initial dimensionless flow conductivity of fractures; FRCD —Dimensionless flow conductivity of fractures; t—Production time after fracturing. a, b, c, d— Regression parameters. 2.2

Multistage Fracturing Optimum Design of Tight Sandstone Gas Reservoir with Cluster Wells

In 2.1, the characterization methods of the complex seepage law of tight sand gas reservoirs and its necessity are discussed. This chapter emphasizes on the multistage fracturing optimum design of cluster wells. Theoretically the more fractures, the higher productivity after fracturing. But since the increase in fractures leads to smaller fracture interval, it is the elliptical porous flow that is firstly stimulated in the stratum. With the development ongoing, the flow regime among hydraulic fractures after compression is converted to linear streams. The outward is the quasi-elliptical flow. The more fractures, the more severe interference among fractures. It shows that with the increase in fractures, tired production is not increased in proportion. Instead, an inflection point occurs. So there shall be an optimal fracture number and adjacent well interval. Two horizontal sections will inevitably come close to each other in the cluster well network. Though it is better to make the fracture longer, if it exceeds a certain limit, the fracture of two wells will definitely get closer and closer. So the fractures among wells are better to be in an intervened arrangement. The unusable area between wells can be

32

S. Liu

decreased as far as possible. But it does not mean the longer the better. When the fracture length exceeds a certain percentage, interference among fractures will be aggravated, and the increasing amplitude of recoverable reserves will be lower and lower; then, there must be an optimal fracture length and fracture distribution method. It can be concluded from the above discussion that there surely has optimal fracture parameters in multistage fracturing of tight gas reservoir cluster wells. The maximum Basic Informa on of Target Oil Fields Pore throat parameters & QRelative curve measurement

Water Lock Effect

Stress Sensib ility

Non-Darcy percola on with high velocity

Fracture longterm flow conduc vity determina on

Fine characteriza on digital model and numerical model

Two-well type cluster well fracture arrangement strategy & Fracture parameters op mum design Long and short fracture combina on strategy

Fracture length ra o

Heel end interval between two wells

Fracture interval

Interlaced fracture arrangement

Fracture flow conduc vity

Extended fracture length ra o

Four-well type cluster well fracture arrangement strategy & Fracture parameters op mum design

Parallel fourwell type

“K” shape fourwell type

“X” shape fourwell type

Four-well type op miza on & fracture parameters economic evalua on op miza on

Recommended Parameters

Fig. 7. Optimum design flowchart of multistage fracturing of tight gas reservoirs cluster wells

Multistage Fractures Optimum of Different Cluster …

33

economic benefit shall be gained while we try best to control the investment. The overall optimum design idea can be summarized as follows (seeing Fig. 7): (1) Analyze physical property parameters of tight sandstone gas reservoirs, sensitivity experiments, fracture fluid properties, fracturing process data, and analyze and judge the non-Darcy flow in matrix pores, water block effect, stress sensitivity, high-velocity non-Darcy flow in artificial fractures, and the necessity of detailed characterization of long-term conductivity of fractures, to further establish the integral fracturing numerical model of tight gas reservoirs cluster wells. (2) Fracture distribution strategy of two-well type cluster well group and fracture parameters optimum design analysis. Since two-well type is the foundation of four-well cluster wells, to avoid too many designing cases for four-well cluster well group, the fracture distribution strategy of two-well type cluster well group, and fracture parameters optimization need to be studied. • To establish an individual well numerical model to simulate the influence of fracture length ratio, fracture length distribution strategy, fracture interval (fracture section number), flow conductivity, etc. on single well deliverability, optimize fracture parameters, thus to get the optimal value range of each parameter. • Two-well type shall be adopted to discuss the fracture interval, interlace fracture distribution strategy, and the optimal extended fracture length ratio, to lay a foundation for four-well type fracture arrangement. (3) Based on the single-well and two-well type fracture arrangement principle, respectively, design multiple layout cases including parallel four-well type, K type, and X type four-well layout, simulate multi-well fracture arrangement method, and adopt a reasonable method for multi-wells fracture layout. (4) Economic evaluation of the integral fracturing design of cluster horizontal well groups. Adopt the established cluster horizontal well numerical model to simulate the influence of fracture parameters, fracture length, flow conductivity, fracture intervals, etc. on well group capacity and establish the economic evaluation model, to consider to gain the maximum economic benefit with minimum investment.

3 Results and Discussions According to the actual situation, analyze the corresponding optimal fracture parameters of the optimum design of different types of cluster wells fracturing. The target tight gas oil field ground is covered by sands and sand dunes, with a weak natural ecoenvironment. Therefore, multistage fracturing of cluster wells is adopted to improve productivity and reach a good development effect. The target oil reservoir is a tight sandstone gas reservoir, and the foundational parameters could be found in Table 2. According to complex seepage mechanism discussed in 2.1, a numerical simulation model considering non-Darcy flow in matrix pores, water lock effect, stress sensibility, non-Darcy flow with high velocity in

34

S. Liu Table 2. Basic parameters of gas reservoirs Gas reservoirs depth, m Effective thickness, m Single well control area, km2 Porosity, % Effective Permeability, % Gas saturation,% Ground crude oil density, g/cm3 Rock compressibility,/MPa Initial formation pressure, Mpa

2645 11.5 3.03 9.09 0.05 56 0.7672 2.6  10−4 24.12

artificial fractures, and long-term conductivity of fractures is established, to lay a foundation for further optimum design of cluster wells’ fracturing parameters. 3.1

Optimum Design of Cluster Wells’ Fracturing Parameters

Fracture parameter case optimization of X-27 four-well cluster well group shall be as follows: (1) Single-well fracturing parameters optimization ① Fracture number: Fracture number optimization is the same as that of fracture interval in essence. The optimization result is that fracture interval is around 150 m. The corresponding fracture number is optimal. There reaches a balance between interference among fractures and high yield. ② Fracture length (fracture length ratio): The best fracture length ratio shall be about 0.35. ③ Fracture conductivity: It is better to be about 20 lm2 cm. ④ Fracture distribution–joint interval distribution: Try best to guarantee equal interval distribution. ⑤ Fracture distribution–fracture distribution of the two ends: The fracture is suggested to be close to the two ends as much as possible and keep the intervals between two fractures the optimum. (2) Fracturing parameters optimization of four-well type cluster horizontal well group ① Fracture arrangement method optimization: The average interlace fracture arrangement yield is a little higher than the opposite fracture arrangement. The interleaved fracture arrangement advantage is much more obvious when the fracture interval is above 150 m. If the actual stratum is with strong anisotropy, the advantage will be greater. ② Optimization of fracture length ratio and joint interval: As long as the fracture length can sweep the region between two wells in a certain time, the fracture length is enough. If increasing the length, we can only improve the gas output in early stage, but there is no influence on

Multistage Fractures Optimum of Different Cluster …

35

final recovery efficiency. Cluster wells’ fracture length is suggested to keep within 0.4. The bigger the well interval, the greater the optimal fracture length ratio, and then the more optimal the fracturing sections. But the amplification is just a little. And the optimum fracturing section of 450–1000 m well interval is about 7–9. The optimum fracture length ratio at 450–700 mm is about 0.35, and it will be 0.35–0.4 if longer than 700 m. ③ Optimization in heel end and toe end: No matter how large the both ends, they have the same optimal fracture ratio. If the heel end interval between the two wells is larger than 300 m, it will be hard to sweep. Mutual interference shall not be considered. (3) Case Design(seeing Fig. 8) ① Design of endpoints parts: The well site far-end of P1 well is 580 m away from the boundary, and the well site far-end of P2 well is 500 m away from the boundary. The end interval of well site near-end between the two wells is 720 m. They all are above 300 m with little interference. Thus, the endpoints parts of four wells do not need to consider the interference with other wells. Besides, the control distance of end B is relatively large, and the fracture length can be properly increased. The well site near-end of P3 and P2 wells also need to properly the fracture length can be properly increased. The well site near-end of P3 and P2 wells also needs to properly increase the fracture length, to achieve better displacement of the four wells. ② Fracture length design: It is about 900 m horizontal section long with seven sections to be fractured for P1 well. The average fracture is 140 m long. The well interval from P1 is 680 m. It can also be regarded as a two-well type well group. According to the four-well type fracture arrangement principle, fracture length of well P1 shall be average, so does well P2. The fracture length in each endpoints part shall be properly increased. Since it is the K-type well arrangement, the interval between P3 and P4, P1 and P2 is not the same. To get a larger swept area, the optimal fracture length ratio in four-well type well group fracture arrangement is adopted.

Equivalent Fracture Interval

Fig. 8. K-type cluster horizontal wells and fracture distribution figure

36

S. Liu

③ Fracturing section number design: According to previous single-well section number optimization, and four-well type optimization, considering the about 150 m well interval and its variance, the fracturing section number of well P1 is 7, 8, and 9. And corresponding fracturing section number of well P2 is 8, 9, and 10. That of well P3 and P4 is 6, 7, and 8, respectively. According to the principle above, take 3 years of cumulated gas production quantity as the target to conduct preliminary case reference selection. A total of 18 cases are designed. According to cases optimization table, the optimum design is as follows: • First group cases (seven sections P1, eight sections P2, six sections P3 and P4) (seeing Tables 3 and 4 and Fig. 9). • Second group cases (eight sections P1, nine sections P2, seven sections P3 and P4) (seeing Tables 3 and 4 and Fig. 10). • Third group cases (nine sections P1, 10 sections P2, eight sections P3 and P4) (seeing Tables 3 and 4 and Fig. 11). Table 3. Corresponding table of fracture intervals Well

P1(X-27-1)

No. of fractures Fracture interval (m)

7 163

8 140

P2(X-27-2) 9 123

10 131

P3(X-27-3) and P4 (X-27-4) 6 7 8 172 143 123

Second group cases 8 sections’ P1, 9 sections’ P2, 7 sections’ P3, 7 sections’ P4 0.3 0.35 0.4 0.35 0.4 0.4

Third group cases 9 sections’ P1, 10 sections’ P2, 8 sections’ P3, 8 sections’ p4 0.3 0.35 0.4 0.35 0.4 0.4

8 168

9 147

Table 4. Case design table Well

Fracture length ratio

3.2

First group cases 7 sections’ P1, 8 sections’ P2, 6 sections’ P3, 6 sections’ P4 0.3 0.35 0.4 0.35 0.4 0.4

Optimal Fracturing Parameters Preference Selected by Economic Evaluation

According to the design principle of cluster well groups, totally 18 cases have been designed. There is a relatively big gap in accumulated output. There come the optimal cases by economic evaluation. It considers the relation among fracture length, sand adding amount, and liquid consumption volume, and meanwhile consider different work amounts and job time, etc. to establish an economic evaluation model and screen to get the optimal result.

3 years’ Cum. gas production(104m3)

Multistage Fractures Optimum of Different Cluster …

37

16,500 16,000 15,500 15,000 14,500 14,000 13,500 13,000

0.3

0.3+0.35 0.3+0.4

0.35 0.35+0.4

0.4

Fracture Length Ratio

3 years’ Cum. gas production(104m3)

Fig. 9. Three years of Cum. gas production comparison chart of the first group cases

17,000 16,500 16,000 15,500 15,000 14,500 14,000 13,500

0.3 0.3+0.350.3+0.4

0.35 0.35+0.4

0.4

Fracture Length Ratio

Fig. 10. Three years of Cum. gas production comparison chart of the second group cases

The 18 cases rank according to the amount of NPV. Just the top five cases are shown in the list. The top three cases with the highest net earnings are (eight sections P1, nine sections P2, seven sections P3 and P4—fracture length ratio 0.4), (nine sections P1, 10 sections P2, eight sections P3 and P4—fracture length ratio 0.4). The first two cases get the similar NPV, which are 2.5 million RMB higher than the third case. Therefore, the optimal case of this design will be preference selected from the first two cases (seeing Table 5). It can be analyzed from the table that the fracture length ratio is the most significant factor. It is mainly because the well interval varies a lot in K-type cluster wells, and the fracture length shall be increased as much as possible. In the case that the fracture

S. Liu 3 years’ Cum. gas production(104m3)

38

17,000 16,500 16,000 15,500 15,000 14,500 14,000 13,500

0.3

0.3+0.35 0.3+0.4

0.35 0.35+0.4

0.4

Fracture Length Ratio

Fig. 11. Three years of Cum. gas production comparison chart of the third group cases

Table 5. Case Preference Table No.

1

NPV, 10,000 RMB 18699.7

2

18676.5

3

18429.5

4

18209.5

5

17946.5

Designing cases

(8 sections’ P1, 9 sections’ P2, 7 sections’ P3 and P4—fracture length ratio 0.4) (9 sections’ P1, 10 sections’ P2, 8 sections’ P3 and P4 —fracture length ratio 0.4) (7 sections’ P1, 8 sections’ P2, 6 sections’ P3 and P4—fracture length ratio 0.4) (9 sections’ P1, 10 sections’ P2, 8 sections ‘P3 and P4 —fracture length ratio 0.35 + 0.4) (8 sections’ P1, 9 sections’ P2, 7 sections ‘P3 and P4—fracture length ratio 0.35 + 0.4)

Preference case p p

length does not exceed the fracture length 0.45, we shall try our best to enlarge the two fractures which are closest to end B of well X-27-1, two fractures closest to end B of well X-27-2, the first fracture closest to end A, two fractures closest to end B of well X27-3, the first fracture closest to end A, and two fractures closest to end B of well X-274. Then, we need to consider the fracturing section number. If only increase the section number, gas production output may be the highest, but it cannot reach the optimal economic benefit. Besides, with the reduction in cost of fracturing materials and tool cost, and the increase in factory price of the natural gas, the optimal fracturing section number will be increased accordingly. According to the result of economic optimization, fracture parameters designing case of X-27 cluster well groups are recommended to be as follows:

Multistage Fractures Optimum of Different Cluster …

39

① Design 0.35–0.4 fracture length ratio; ② Design 135–145 m fracture interval; ③ Design nine sections’ X-27-1 fracture, 11 sections’ X-27-2 fracture, 10 sections’ X-27-3 fracture, and 10 sections’ X-27-4 fracture. X-27 “K type” cluster well group fracture arrangement method: ① “W”-type fracture arrangement of well X-27-1 and X-27-2; ② Try to increase the fracture length in toe end of well X-27-3 and X-27-4; To increase the fracture length in heel end of well X-27-3. 3.3

Post-fracturing Evaluation of Multistage Fracturing of Cluster Wells

Field fracturing construction has been conducted to the DPT-27 cluster well group since April 2013. Well DPT-27-3 and DPT-27-4 are constructed first. Then, well DPT27-1 and DPT-27-2 were constructed in May. It generally goes smoothly with 100% success rate. DPT-27 well group fracturing achieves good effect, which is 2.2 times of average open flow capacity of surrounding wells in the same layer. The steady gas production of four wells after fracturing is 8.11–9.43  104 m3/d. The open flow capacity is estimated to be 12.11–26.77  104 m3/d. They both are larger than the average high-efficiency well standard 12  104 m3/d. So the four wells reach a good fracturing effect (seeing Table 6).

Table 6. Post-fracturing Effect Table Well No. DPT-27-1 DPT-27-2 DPT-27-3 DPT-27-4 Average

Daily output/open flow capacity, 104 m3 8.6/14.4 8.7/26.8 8.1/12.1 9.4/19.9 8.7/18.3

4 Conclusions (1) The key point of optimization of two-well type cluster well groups: The heel end interval between two wells is larger than 300 m, and there is no need to consider the interference between wells. The fracture arrangement of “W” type is much better than “U” type. The fracture length of the two ends of the horizontal well shall be increased as far as possible. And the fracture in both ends shall try to be close to heel part and toe part. Try to guarantee equal interval fracture arrangement. It will achieve a relatively sound effect when the fracture interval is 100–120 m, fracture length is about 200 m, and the optimal flow conductivity reaches 20 lm2 cm.

40

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(2) The horizontal four-well cluster well groups shall interlace with each other. And “W” fracture arrangement is adopted. Try to set up long fractures in toe end. It will achieve a relatively good effect when the fracture interval is 100–120 m, the fracture length ratio is controlled to be within 0.3–0.4 along with the well distance change, and the fracture flow conductivity reaches 20 lm2 cm. (3) Since cluster type fracture length mainly varies with the change of borehole distance, permeability characteristics of reservoir stratum, and well distribution type change of cluster well groups, and the optimum fracture length ratio increases as permeability reduces, “K-type” and “X’-type cluster well groups need a larger fracture length ratio. Try best to increase the fracture length in the endpoints. (4) Whether the fracture arrangement shall be interlaced or relative mainly depends on the reservoir status. Since the output in uniform formation nearly has no difference, no matter in which way it can be ignored. (5) Fracture interval distribution: Try best to arrange fractures with the equal interval. The fracture of both ends shall try to be close to heel part and toe part. (6) It forms a full set of optimum design method of integral fracturing parameters of cluster well groups. It covers geologic modeling, fracture parameters optimization, construction parameters optimization, and economic evaluation. Acknowledgements. This study was supported by National Science and Technology Major Project [Grant 2017ZX05005-005].

References 1. Yong H, Li X, Wan Y, et al. Physical simulation on gas percolation in tight sandstone. Petrol Explor Dev. 2013;40(5):580–4. 2. Clarkson CR, Freeman M, He L, et al. Characterization of tight gas reservoir pore using USANS/SANS and gas adsorption analysis. Fuel. 2012;95:371–85. 3. Dutta R, Lecc O. Experimental investigation fracturing-fluid migration caused by spontaneous imbibition in fractured low-permeability sands. SPE Reserv Eval Eng. 2014;17(1):74–81. 4. Tang H, Xu S, Wang X, et al. Water blocking damage of hyper-tight sandstone gas Oil & Gas Field in Kelasu gas field, 2017;24(4):541–45. 5. Wen Q, Zhang S, Wang L, et al. The effect of proppant embedment upon the long-term conductivity of fractures. J Petrol Sci Eng. 2007;55:221–7. 6. Li KW, Gao YP, Li YC, et al. New mathematical models for calculating proppant embedment and fracture conductivity. SPE J. 2015;20(3):496–507. 7. H HY, Ayoub JA. Applicability of the forchheimer equation for non-Darcy flow in porous media. SPE J. 2008;13(1):112–22. 8. Olson KL, Milton TD. Multiphase non-Darcy pressure drop in hydraulic fracturing. In: Proceedings of the SPE annual technical conference and exhibition, Houston, Texas, Society of Petroleum Engineers (2004).

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9. Lai BT, Miskimins JL. A new technique for accurately measuring two phase relative permeability under non-Darcy flow conditions. SPE-134501-MS In: Proceedings of the SPE, annual technical conference and exhibition, Florence, Italy, Society of Petroleum Engineers 2010. 10. Amini S, Ilk D, Blasingame TA. Evaluation of the elliptical flow period for hydraulically— fractured wells in tight gas sands—theoretical aspects and practical considerations. In: SPE Hydraulic Fracturing Technology Conference. 2007. College Station, Texas, USA, Jan 29–31. 11. Ruth Ma. On the derivation of the Forchheimer equation by means of the average theorem. Transp Porous Media. 1992;7(3):255–64.

Deliverability Evaluation on Horizontal Well with DHC in Tight Sandstone Gas Reservoir Yundong Xu1,2,3(&), Zhen Sun3, Liangrong You1,2, Long Chen4, Liu He1,2, Shunzhi Yang5, and Yilin He1,2 1

National Engineering Laboratory for Low-Permeability Petroleum Exploration and Development, Inner Mongolia, China [email protected] 2 Research Institute of Exploration and Development, Changqing Oilfield Company, Xian, Shaanxi, China 3 No.5 Natural Gas Plant of Chang Qing Oil-Field Company, Wushenqi, Inner Mongolia, China 4 No.3 Natural Gas Plant of Chang Qing Oil-Field Company, Wushenqi, Inner Mongolia, China 5 Sulige Gasfield Development Company, PCOC, Inner Mongolia, China

Abstract. Sulige gas field is a typical tight sandstone gas reservoir. In order to reduce the pressure in gathering line, cut engineering investment, and enhance recovery, down-hole choke (DHC) is widely applied in the area. However, this device could lead to unstable production, plus the lack of data of pressure and deliverability test in the area, traditional deliverability methods like empirical method, index curve, and IPR relationship could not be applied. Since the year of 2011, horizontal wells are widely developed in Sulige gas field. Take block S1 for instance, based on production data, decline analysis and flowing material balance equation; three deliverability forecasting methods are developed, which include using conventional production data, initial production rate, and absolute open flow. Applying this combined deliverability forecasting method in block S1, field application shows that rational rate of horizontal wells in the first three years of the area is about 4.3
104 m3/d, which caters to the practical situation. This method has provided a research strategy for the similar gas field and could be used as a reference for well deployment, gas gathering line construction, and reservoir development potential prediction.

Copyright 2018, Shaanxi Petroleum Society. This paper was prepared for presentation at the 2018 International Field Exploration and Development Conference in Xi’an, China, 18–20 September, 2018. This paper was selected for presentation by the IFEDC Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the IFEDC Committee and are subject to correction by the author(s). The material does not necessarily reflect any position of the IFEDC Committee, its members. Papers presented at the Conference are subject to publication review by Professional Committee of Petroleum Engineering of Shaanxi Petroleum Society. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of Shaanxi Petroleum Society is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of IFEDC. Contact email: [email protected]. © Springer Nature Singapore Pte Ltd. 2020 J. Lin (ed.), Proceedings of the International Field Exploration and Development Conference 2018, Springer Series in Geomechanics and Geoengineering, https://doi.org/10.1007/978-981-13-7127-1_4

Deliverability Evaluation on Horizontal Well …

43

Keywords: Tight sandstone reservoir  DHC  Rational rate  Forecasting method based on conventional production data  Forecasting method based on initial production rate  Reservoir development potential prediction

1 Introduction Sulige gas field is located on the northwest side of Yishan slope of Ordos basin. As a typical tight sandstone reservoir, the pay zone of the field is He 8 and Shan 1 layers. And both layers yield severe heterogeneity, low pressure, low abundance, and low permeability. Since 2006, large-scale development becomes reality for enhancing technology, encouraging creativity, and controlling cost. Since 2011, horizontal wells were largely developed in Sulige field, especially S1 block. S1 block is located in the middle part of Yishan slope of Ordos Basin, the Upper Paleozoic is dominated by delta plain, and the following formations are developed in the field: Ben Xi, Shan Xi, lower Shihezi, upper Shihezi, and Shiqianfeng. The pay zones are Shanxi and lower Shihezi, which developed a reservoir with 6–9 m thickness, 6–12% porosity, and 0.1–1 mD permeability. There are a few pressure, and deliverability test data in the block S1 for DHC is widely applied in the area. More than 50% wells in the area are horizontal wells, and accurate production prediction is vital in making developing decisions.

2 Rational Rate Elevation In order to maintain plateau, reduce pressure decline influence, and improve production rate, the allocation should take single well-controlled reserve into consideration, so that a gas well could maintain a 2–3 years of plateau. Conventional deliverability evaluating method includes empirical method, inflow performance relationship, and nodal analysis [1]. Absolute open flow is the prerequisite for empirical method, and coefficient A and B in deliverability equation are requirements for inflow performance relationship and nodal analysis. However, these factors could only be acquired from deliverability tests. Due to the DHC, deliverability tests’ data are rare in Sulige gas field; as a result, conventional deliverability predicting method can hardly applied in the area. Based on production data, decline analysis, and flowing material balance equation, three deliverability forecasting methods are developed, which include using conventional production data, initial production rate, and absolute open flow. 2.1

Allocation Evaluation Method Based on Conventional Production Data

Block D1 in Jingbian oilfield is a neighboring reservoir of S1 block. They share similar geological condition and the same pay zone. But, block D1 has a pretty long production history and owns abundant pressure testing material for not applying DHC. As a result, material balance equation could be used for GIIP (gas initially in place) evaluation. Based on GIIP evaluation result of more than 100 wells in D1 block and cumulative

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Y. Xu et al.

production rates when casing pressure decline to 16 MPa/14 MPa/12 MPa/ 10 MPa/ 8 MPa/ 6 MPa, a deliverability predicting equation (Eq. 2) has been established.

In Gp GIIP Pc Q t

Gp ¼ f ¼ 6:0846
p1:4954 c GIIP

ð1Þ

Q ¼ GIIP
f =t

ð2Þ

which = cumulative production rate (104 m3) = gas initially in place (104 m3) = casing pressure (MPa) = gas production rate (104 m3/d) = elapsed time (d)

In order to predict deliverability using conventional production data, a relationship of production rate, casing pressure, and GIIP is developed based on Eq. (2). As shown in Fig. 1, the rational allocation of block S1 should be 4.3
104 m3/d, with a GIIP of 0.81
108 m3 and a casing pressure of 5.7 MPa.

Fig. 1. Plate of deliverability prediction using conventional production data

2.2

Allocation Evaluation Method Based on Initial Production Rate

Due to the DHC, gas rate in Sulige gas field yields a decline character from the beginning of production. And the analysis shows that the decrease follows the rule of depletion decline (n = 0.5), as shown in Eq. (3), which could be transformed as Eq. (4). According to Eq. (4), a correlation chart between initial gas rate, rational allocation, and producing time has been established (Figs. 2 and 3).   Qi 1 Gp ¼ 1 1 þ 0:5Di t 0:5Di

ð3Þ

Production rate(104m3/d)

Deliverability Evaluation on Horizontal Well …

45

Qi Q

Time d

Fig. 2. Correlation chart between rational allocation and initial gas rate

Qi ¼

Qi Di t

 ð1 þ 0:5Di tÞGp ð1 þ 0:5Di tÞQ  t ¼ ð1 þ 0:5Di tÞQ ¼ t t

ð4Þ

In which = initially gas rate (104 m3/d) = initial decline rate (dimensionless) = elapsed time (d)

Figure 3 is the production history of three different types of well. Equation (4) and Fig. 3 indicated that rational allocation in the first three years of the first class of horizontal wells in block S1 is about 7.1
104 m3/d, the second class of horizontal wells 4.1
104 m3/d, and the third class of horizontal wells 2.3
104 m3/d. Weighed by well number, the average allocation in the first three years in block S1 is about 4.2
104 m3/d.

Fig. 3. Production history of block S1

46

2.3

Y. Xu et al.

Allocation Evaluation Method Based on AOF

AOF shows the fracture permeable feature of initial producing history near the wellbore. The empirical method, which is taken 1/4–1/6 of AOF as the rational allocation, may trigger problem [2]. A higher allocation may cause a quick rate decline and reservoir damage due to pressure sensitivity effect. And a lower allocation may initiate liquid loading [3, 4]. Large-scale fracture changed the relationship between allocation coefficient and AOF [5]. Statistical data show that these two variables follow the rules of power function, as shown in Fig. 4, which indicate a larger AOF corresponding to a smaller allocation coefficient.

Fig. 4. Relationship between AOF and allocation coefficient

The average AOF of horizontal wells in the study area is about 41.4
104 m3/d. And according to the relationship, the rational allocation in the first three years is about 4.3
104 m3/d.

3 Comprehensive Evaluation Based on production data of more than 200 horizontal wells in block S1, three evaluation methods show that the average rational allocation of the study area is about 4.3
104 m3/d, as shown in Table 1.

Table 1. Allocation evaluation result of horizontal wells in the first three years No.

Allocation evaluation method

1 Conventional production data 2 Initial production rate 3 AOF Comprehensive evaluation

Rational allocation (104 m3/d) 4.3 4.2 4.3 4.3

Deliverability Evaluation on Horizontal Well …

47

4 Inclusion and Cognition (1) Wells in tight sandstone reservoir with DHC yield short producing history, unstable production rate, and rare pressure testing material. Based on production data, three allocation evaluation methods are developed, which include using conventional production data, initial production rate, and absolute open flow. (2) Allocation evaluation method based on conventional production data shows that the rational allocation in the first three years is about 4.3
104 m3/d, initial production rate method indicates a rational allocation of 4.2
104 m3/d, and AOF method implies an allocation of 4.3
104 m3/d. (3) The above allocation evaluation method is independent of deliverability test and long producing history. And so, it provides an effective method to evaluate rational allocation of horizontal wells with DHC.

References 1. Hong’en D. A new method of predicting the productivity of horizontal well. Oil Drilling Prod Ind 1996;18(1):76–81. 2. Jemert TA, Selseng H. Permeability function describes core permeability in stress-sensitive rocks. Oil & Gas J Dec 1998:60–6. 3. Zhihai C. Deliverability prediction of horizontal gas well. Nat Gas Ind 2006;26(2):98–9. 4. Blasingame TA, Lee WJ Properties of homogeneous reservoirs, naturally fractured reservoirs and hydraulically fractured reservoirs from decline curve analysis. In: Paper SPE 15028 Presented at the 1986 SPE Permian Basin Oil and Gas Recovery Conference 1986. 5. Xiaoping L. Analysis of factors influencing productivity of horizontal gas wells. Nat Gas Ind. 1998;18(2):36–53.

Author Biography Yundong Xu (1983), male, Shandong Heze, Master, Gas Reservoir Engineer, research on dynamic monitoring of gas field development.

The Integration of Checking Seal and Testing Regulation of Bridge Concentric Layered Water Injection Technology Research and Application Lingzhi Yang1,2(&), Jiuzheng Yu1,2, Bin Yao1,2, Yanqing Liu1,2, Changlong Yu3, and Fuwei Bi1,2 1

Oil & Gas Technology Research Institute Changqing Oilfield Company, 710018 Xi’an, China [email protected] 2 National Engineering Laboratory of Tight Oil & Gas Field Exploration and Development, 710021 Xi’an, China 3 Oil Production No.10 Changqing Oilfield Company, 745000 Qingyang, China

Abstract. Fine-layered water injection is the most economical and effective technical means to keep the formation of energy and improve water driving use in low permeability reservoirs. Changqing oil field adopts directional well and small water flow-rate development, and the problem of short duration of injection pipe column, low success rate of test, and low efficiency restrict the efficient development of low permeability reservoir. With the advancement of low permeability oil field water injection work, focusing on the demand of the oil field development efficiency, this paper puts forward the integration technology of bridge concentric layered water injection, which keeps the water distributor and adjustable water nozzle concentric integrated design, breaks through the original test, inspection seal traditional process step by step, innovative research and development of the second-generation bridge concentric layered water injection key tool, and forms on testing the integration process, with a process to finish each layer checking seal and testing and regulation, so it improves test mixing efficiency significantly by all the advantages. In Nanliang experimental zone water injection development, the field application of bridge concentric layered water injection technology is 65 wells and enlarges the

Copyright 2018, Shaanxi Petroleum Society. This paper was prepared for presentation at the 2018 International Field Exploration and Development Conference in Xi’an, China, 18–20 September, 2018. This paper was selected for presentation by the IFEDC Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the IFEDC Committee and are subject to correction by the author(s). The material does not necessarily reflect any position of the IFEDC Committee, its members. Papers presented at the Conference are subject to publication review by Professional Committee of Petroleum Engineering of Shaanxi Petroleum Society. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of Shaanxi Petroleum Society is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of IFEDC. Contact email: [email protected]. © Springer Nature Singapore Pte Ltd. 2020 J. Lin (ed.), Proceedings of the International Field Exploration and Development Conference 2018, Springer Series in Geomechanics and Geoengineering, https://doi.org/10.1007/978-981-13-7127-1_5

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comprehensive application covering Changqing oil field in 2018. Meanwhile, the success rate of measured is 95%, and the average checking seal and testing time of single well are 4–6 h. Bridge concentric layered water injection technology for highly inclined wells significantly improves the success rate and efficiency of the injection well test, saving single well’s operation time more than 30% and cost over 20%, and enhances water driving use degree by 10.7%. The successful application of this technology has enriched and improved the technology system of layered water injection technology, which has realized the upgrading of the fine-layered waterflooding technology and has a wide application prospect. Keywords: Integration Efficiency




Bridge concentric




Layered water injection




1 Introduction Changqing oil field is a typical three low reservoirs, low permeability, low pressure, and low abundance, and requires energy supplement by water injection reservoir, but due to the interlayer contradiction from reservoir interlayer development and uneven water injection profile, layer water injection becomes the key method to improve production and ultimate recovery [1–3]. Combining with directional well and small water flow rate, in 2012, Changqing oil field developed bridge concentric layered water injection technology, adopting concentric structure design and cable-efficient testing method to improve the efficiency and precision of measuring success rate in high angle well [4–8]. Furthermore, this technology relieves the contradictions of the longitudinal water-drive reservoir section effectively and improves the effect of the fine water flooding development [9, 10]. As the separate injection wells increasing year by year, adjustable volume (14000 times) is larger, and the cost (200 million yuan nearly) is higher. In order to enhance the efficiency and quality of the separate injection, in 2015, Changqing oil field innovation has formed an integration technology of bridge concentric inspection testing, and packer sealing has developed the second-generation bridge concentric water distributor and the integrated instrument of testing and packer sealing as the key tools. The integrated technology realizes each job in a well including packer sealing, testing, and water flow rate controlling, so that it improves measuring adjustment efficiency, saves operating costs 3500 yuan per test, and helps bridge concentric separate injection technology updates.

2 Integrated Technology of Packer Sealing and Testing in Bridge Concentric Separate Injection 2.1

Pipe String Structure

Bridge concentric layered water injection string is shown in Fig. 1, mainly by the pipeline compensator, long-term packer, the second-generation bridge concentric water

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Fig. 1. Bridge concentric layered water injection string

distributor, preset working barrel, double action van, screen, and plug. The tubing compensator acts as a compensation for peristaltic deformation and protects the packer for a long time. Long-term packer designs non-metallic anchor institution and long plastic tube sealing mechanism, sets the packer centralizer structure to support string in the inclined well, uses non-metal anchor claw surface of vulcanization processing mode, to ensure that the string anchoring effect, and to avoid casing extrusion and wear, ascending anti-wearing effect, extending the string seal by long rubber tube with metal composite rubber material. Second-generation bridge concentric water distributor keep early integration of adjustable water nozzle concentric integration design, optimize concentric canister to bottom water nozzle structure, docking adjustment from the upper adjusting adjustment to lower adjustment to ensure that the high-angle wellstratified flow test deployment success rate, to improve the test efficiency at the same time. 2.2

Theory

Bridge concentric layered water injection technology uses long-term packer to separate each layer, uses compensator for separate injection tubing string expansion amount caused by the reservoir pressure fluctuation, and applies the second-generation bridge concentric water distributor for each layer water injection. In test process, the bridge concentric integration of packer seal checking and testing communicates with the ground controller and matches to the second-generation bridge concentric water distributor under test. Then, the inspection seal structure promotes test sealing glue tube setting and checks the packer seal. After that, the controlling structure adjusts water nozzle, changing the opening of nozzle and obtaining the right injected water volume adjustment. Data acquisition control system controller is connected with the ground, which can real-time online monitoring of packer test situation, flow rate, temperature, and pressure, achieve seal checking, testing and controlling in a trip, and meet the demand of geological injection allocation.

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Technical characteristics (1) High success rate of the measurement. With the concentric structure design of the water distributor, the integrated instrument is aligned with the water distributor to ensure the success rate of the measurement, and it can meet the needs of the high angle well and deep well-stratified water distribution. (2) High measurement efficiency. Check seal structure and adjustable structure are integrated in one instrument, firstly check packer seal, then test regulating stratified flow, so one trip operation can complete the whole test of one well. And the testing results are shown on the ground controller directly in the visual operation, so the process increases efficiency of the fieldwork. (3) High string series. With the water injection in central channel mode, the length of the water distributor is shortened, the series is not limited, and the difficulty of multi-level subdivision measurement is solved. (4) Small interference between layers. Bridge concentric water distributor has a large area of overpass, which does not affect normal water flooding in other layers.

3 Key Tools 3.1

Long-Term Packer

Compared with common injection well packer, long-term packer is designed its anchoring mechanism, adopt hydraulic setting, pull the string up to unseal. The packer is mainly composed of upper joint, anchoring mechanism, unlocking mechanism, sealant plastic tube, protection plastic tube, backwashing well mechanism, setting mechanism, center pipe, and lower joint (shown as Fig. 2), which working pressure is 45 MPa, and working temperature is 120 °C.

Fig. 2. Long-term packer

Technical features: It uses multiple sets of packer rubber tube; first, the protection rubber tube is composite metal rubber materials which can improve the compressive strength, wear-resisting properties of the rubber tube. Second, sealant tube uses new rubber polymer materials to ensure the rubber tube elasticity, improve the anti-aging performance of the rubber tube, increase the radial expansion volume, and improve the contact stress at the same time. The anchor mechanism is added, the metal anchor claw is designed, and the surface is treated with non-metallic material, so it guarantees the

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anchoring effect of the pipe column and avoids the wear of casing surface. By improving the setting mechanism, the design of multi-stage push tube and balance pressure structure is realized, and the sealing effect is improved, which solves the problem of peristalsis and unsealing during pressure fluctuation. 3.2

Second-Generation Bridge Concentric Water Distributor

Second-generation bridge concentric water distributor is the key part of the integrated technology; it contains upper joint, positioning mechanism, outer protector, main body, adjustable nozzle, concentric movable tube, centralizing mechanism, and lower joint (shown as in Fig. 3).

Fig. 3. Second-generation bridge concentric water distributor

Compared with first-generation bridge concentric water distributor, the secondgeneration bridge concentric water distributor retains the adjustable water nozzle and the water distributor integration design, water nozzle and the main structure are optimization to the central water distributor, and concentric movable tube becomes downward adjustment instead of the upward adjustment, meanwhile centralizer body synchronization design on the lower part of water distributor. In the completion process, the nozzle is in a fully closed position, meeting the requirement of packer setting and realizing the free throw for the whole job. At the time of the sealing, the integrated instrument and the water distributor are concentric positioning and docking, and the sealing rubber tubes of the sealing mechanism under the action of the motor are compressed and sealed to complete the packer inspection. When measuring and adjusting, the integrated instrument drives the concentric movable tube and the movable nozzle to turn up and down, so it can change the opening degree of the water nozzle and realize the adjustment of the water injection amount. Between main body and outer protector it designs greater bridge type of channel, when the integration takes up the center channel, part of the injected water flow from bridge type the path of circulation to the next level bridge concentric water distributor, in order to meet the needs of other interval stratified water distribution, minimize interference between the layers.

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The Integrated Instrument of Packer Seal Checking and Flow Rate Adjusting

The integrated instrument is the other key part of the integrated technology, and it integrates two tools into one, concentric adjusting instrument and electric packer seal checker. Checking seal mechanism and adjusting mechanism are in clutch structure design, so it can implement a motor, respectively, complete sealing mechanism of the longitudinal compression action, and adjust claw rotation action. The instrument is mainly composed of cable joint, centralizing mechanism, flow meter, magnetic orientation, circuit device, motor, positioning mechanism, seal checking institution and regulate claw structure, and so on (Fig. 4). Under the effect of the centralizer and the magnetic orientation, the bridge concentric inspection and adjustment integrated instrument realize to match to the secondgeneration bridge concentric water distributor. The upper and lower parts of the sealing mechanism are located in the upper and lower parts of the water distributor, the sealing machine is sealed through the motor, and the water injection system is changed through the ground control valve to complete the sealing work.

Fig. 4. Integrated instrument of packer seal checking and flow rate adjusting

In the test process, the anti-rotating claw is attached to the main positioning end of the positioning mechanism to prevent the device from turning. The adjustable jaw matches to the hole of the concentric movable tube to adjust the flow rate under the drive of the motor. The power transmission design of the integrated instrument is a concentric connecting rod mechanism with simple mechanical structure and highpower transmission efficiency. The integrated instrument can adjust the integration of the packer seal checking and the stratified flow test, and greatly improve the efficiency of the test.

4 Field Application In low permeability reservoirs of Changqing oil field, the integrated technology of bridge concentric water injection applies 92 wells, testing success rate is 100%, measuring the success rate is 95%, measuring the qualification rate is 96%, and injection string is valid for more than 3 years. In 2018, the comprehensive promotion application, Changqing oil field is expected to promote more than 500 wells. In 2015– 2017, 65 wells were tested in the large angle wells in Nanliang oil field, and the water flooding reserve in the pilot area increases by 10.7%. Well S4-2 is an example in Nanliang oil field. The well is put into operation in general water injection in 2010, with four water injection layers. Due to poor reservoir

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physical properties, strong heterogeneity, great difference in water absorption between layers, 13.8% of water absorption in the second layer, and no water absorption in the fourth layer, so the separate injection measures for the well were implemented to improve the longitudinal profile. Combined with the well deviation is larger (49.5° deviation) of the actual situation, in 2015, it was implemented the integration technology of bridge concentric water injection; four points on injection allocation of each layer is 10, 15, 10, and 10 m3, respectively. First of all, after the injection pipe is placed into the design position, the long-term packer can be seated and anchored by a gradual pressure down to 15 MPa through the tubing. The cable carries the integrated instrument to open the water nozzle and complete the packer test. After passing the seal, according to the geological injection allocation quantity of four layers of water injection test, a trip to complete open nozzle, packer seal checking, and each layer flow test, measuring adjustment layers after all meet the requirements of geological injection allocation, measuring the time 4.6 h, the average measurement error within 5%. After stratified water injection, the water absorption thickness increased by 6.3 m, the water absorption profile was uniform, the water driving degree was improved, and the production effect of the oil well was greatly improved, as shown in Table 1.

Table 1. Well S4-2 injection data Term Before After

Water injection (m3) First Second Third 19.86 6.21 16.25 10.21 14.88 10.55

Fourth 2.31 9.49

Absorption thickness /m

Average output (t d−1)

8.50 14.8

1.65 2.12

5 Conclusion (1) The integrated technology of packer seal checking and flow rate adjusting effectively solves the high-angle well layer injection problem, not only improves the success rate of the measurement and test efficiency and extends the validity of the separate injection string, but also helps bridge concentric layered water injection technology updates. (2) The integrated technology of packer seal checking and flow rate adjusting in the Nanliang oil field scale applies 65 wells in directional well, implements a trip to finish all test well testing operation, saves the average check testing time from 6– 8 h to 5 h, improves measuring the efficiency, and boosts quality and efficiency of separate injection technology. (3) The success rate of the integrated technology of the bridge concentric and the qualified rate of the test are kept above 95%, which improve the water driving degree of the pilot area and the development effect of reservoir water flooding.

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Acknowledgements. The authors wish to thank the management and personnel of Oil and Gas Technology Research Institute, Changqing Oil field Company for their support of this work. A special acknowledgement is made to Yu Jiuzheng and Ju Yafeng for collecting data and Trican technical and engineering staff for their contributions on the collection of field results.

References 1. He L, Xiaohan P, Kai Luo, Fuchao Sun, Lichen Zheng, Qinghai Yang. Current status and trend of separated layer water flooding in China. Petrol Explor Dev. 2013;40(6):733–7. 2. Zhou W, Xie ZY, Li JS, et al. The development and practice of separate layer oil production technology in Daqing Oilfield. SPE 30813. 3. Pei XH, Yang ZP, Ban L, et al. History an actuality of separate layer oil production technologies in Daqing Oil-field. SPE 100859. 4. Jiuzheng YU, Lingzhi YANG , Fuwei. BI. Research on Bridge type Concentric Layered Water Injection in Nanliang Oilfield and its Application. Drilling Prod Technol 2016;39(5): 30–2. 5. Yu J, Ju Y, Guo F. Research and experiment on bridge concentric separated layer water injection technology. Petrol Explor Dev. 2015;37(5):92–4. 6. Luo Y, Wang S, Li L, et al. Technology of separate layer water injection on inclined shaft in Nanpu Oilfield. Petrol. Explor. Dev. 2009;31(2):124–6. 7. Jiuzheng YU, Fangyuan GUO, Yafeng JU. Development and test of bridge concentric water distributor. China Petrol Mach. 2013;41(9):88–90. 8. Li M, Jin W, Ju Y, et al. The application of bridge eccentricity slicing water injection technology in large slope well. China Petrol Mach 2010;38(12):70–2. 9. Hou G, Han J. Resear ch on zonal injection technology of Tr iassic ultr a”low permeability r eservoir in Changqing Oilfield. Fault Block oil Gas Field. 2008;15(3):110–2. 10. Li M, Wang Z, Zhu L, et al. Application test of bridge eccentric stratified water flooding in oilfield. China Petrol Mach. 2010;39(10):66–70.

Author Biography Lingzhi Yang (1986.11–), man, master, engineer, Mainly engaged in water injection Oilfield.

Permeability and Viscosity Index Range Estimation of Imbibition Agent Suitable for Low-Permeability Reservoir Yi Zhang1(&), Jianguo Li1, Fangge Gong2, Yun Sun2, Haihui Chen2, Hongyan Cai1, and Hongfu Fan2 1 State Key Laboratory of Enhanced Oil Recovery/Petro China CO.LTD Research Institute of Exploration and Development Enhanced Oil Recovery Research Institute, Beijing, China {Zhangyi2008,Lijianguo3,Caihongyan}@petrochina.com.cn 2 China University of Geosciences (Beijing) Energy, Beijing, China {2386932613,1430724246}@qq.com, [email protected]. cn, [email protected]

Abstract. Permeability and viscosity are important factors that influence the recovery efficiency of the imbibition agent. Based on the experimental data form 310 ultra-low- permeability cores and 360 oil sands, by curve-fitting method and binary regression method, the regressive analysis of imbibition efficiency, viscosity, and permeability force were carried out. The optimum range of permeability force ratio and viscosity ratio was estimated. The optimum range of each parameter in the extra/ultra-low-permeability reservoir pore was determined, by regression analysis and model experiments. The optimum interval of viscosity ratio was (2,28), which from the preliminarily estimated by curve-fitting method. The model passed the inspection of significance at the level of a = 0.01 which can explain 70% of the experimental data, which determined the optimum range of viscosity ratio in more than 6. The model obtained by analyzing the results of oil sand experiment passed the inspection of significance at the level of a = 0.01, which can explain 70% of the experimental data, which determined the optimum range of viscosity ratio in more than 2.9. By synthetically analyzing the consequence of oil sand and core experiment, the optimum range of viscosity was more than 2.9. The imbibition efficiency and the permeability of imbibition agent obtained by analyzing the results of oil sand experiment passed Copyright 2018, Shaanxi Petroleum Society. This paper was prepared for presentation at the 2018 International Field Exploration and Development Conference in Xi’an, China, 18–20 September, 2018. This paper was selected for presentation by the IFEDC Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the IFEDC Committee and are subject to correction by the author(s). The material does not necessarily reflect any position of the IFEDC Committee, its members. Papers presented at the conference are subject to publication review by Professional Committee of Petroleum Engineering of Shaanxi Petroleum Society. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of Shaanxi Petroleum Society is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of IFEDC. Contact email: [email protected]. © Springer Nature Singapore Pte Ltd. 2020 J. Lin (ed.), Proceedings of the International Field Exploration and Development Conference 2018, Springer Series in Geomechanics and Geoengineering, https://doi.org/10.1007/978-981-13-7127-1_6

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the inspection of significance at the level of a = 0.01, which can explain 75% of the experimental data, which determined the high imbibition efficiency when the permeability force ratio was more than 1.65. The model obtained passed the inspection of significance at the level of a = 0.01, which can explain 37.5% of the experimental data, which determined the high imbibition efficiency when the permeability force ratio was more than 1.35. By synthetically analyzing the consequence of these two experiments, the most suitable permeability force ratio between imbibition agent and water was greater than 1.35. The estimated results of the two properties of imbibition agent provide an important experimental and theoretical basis for screening and evaluation of imbibition agent and study the imbibition behaviors. Keywords: Binary regression method Permeability
Viscosity


SPSS
Low-permeability reservoir


1 Introduction The properties such as interfacial tension, emulsifying property, viscosity, and permeability are the basic properties of the recovery efficiency of the imbibition agent (referred to as the imbibition agent); the combined effect of the basic properties in the process of oil displacement and imbibition oil recovery shows a good displacement, wetting reversal, reduce capillary resistance, and other effects. In the medium- and highpermeability reservoirs, the interfacial tension of the oil displacement agent is better than that of the ultra-low (10–3 mN/m) according to the number of capillary or low tension theory. The theory suggests that the oil displacement efficiency can reach a high level [1]. Viscosity ratio is reflected in the sweep efficiency, and “permeability force” is a newly defined concept, which is used to quantitatively characterize the permeability and diffusivity of porous media [2]. How these two parameters affect the imbibition efficiency and how to determine the values in extra/ultra-low-permeability reservoirs have not been reported. In recent years, all scholars of oil recovery in China Petroleum Exploration and Development Research Institute [3, 4] proposed to evaluate the displacement effect of oil displacement agent by evaluating the comprehensive index of emulsification of oil displacement agent system. However, the evaluation of the imbibition agent for the imbibition oil recovery, a capillary number model is proposed, and the wetting angle is introduced [5]. It can explain that the imbibition agent can overcome the capillary resistance problem in the oil-wet state, but it does not take into account the complex wetting condition of the actual reservoir. The interfacial tension, emulsification stability, viscosity, and permeability force have significant impact on the imbibition efficiency by the study of the influencing factors and the imbibition law. The trend of single factor on the effect of imbibition efficiency was obtained by indoor physical simulation experiment. In the porous medium of special/ultra-lowpermeability, the four parameters have the best range, which is confirmed by multiple regression analysis. In this paper, the optimal range of viscosity and permeability

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force of the imbibition agent for special/ultra-low-permeability reservoirs is determined by multiple regression analysis.

2 Mathematical Analysis Principle and Tool Software 2.1

Binary Response Regression Equation

2.1.1 The Significance of Binary Response Regression Equation Assuming that the dependent variable y is a qualitative variable that reads only two values of 0 and 1. The simple linear regression model is yi ¼ b0 þ b1 Xi þ ei . In this case, the mean value Eðyi Þ ¼ b0 þ b1 Xi of the dependent variable y has a special significance. Because yi is a 0–1 type Bernoulli random variable, the probability distribution is as follows: Pðyi ¼ 1Þ ¼ pi

P ð y i ¼ 0 Þ ¼ 1  pi

ð1Þ

According to the definition of the expected value of the discrete random variable: E ðyi Þ ¼ 1pi þ 0ð1  pi Þ ¼ pi

ð2Þ

And then get: E ðyi Þ ¼ pi ¼ b0 þ b1 Xi . So the regression function is given the dependent variable mean E ðyi Þ ¼ pi ¼ b0 þ b1 Xi . The mean is when the independent variable level Xi is the probability of yi ¼ 1. The interpretation of the mean of the dependent variable applies to both simple linear regression functions and complex multivariate regression functions [6, 7]. 2.1.2

Special Problems of Binary Response Regression Equation

1. Discrete abnormal error term For a dependent variable of 0 or 1, the error term ei ¼ yi  ðb0 þ b1 Xi Þ can only take two values: When yi ¼ 1; ei ¼ 1  ðb0 þ b1 Xi Þ ¼ 1  pi . When yi ¼ 0; ei ¼ 0  ðb0 þ b1 Xi Þ ¼ pi . Obviously, the error term ei obeys the 0–1 discrete distribution, and of course, the assumption of the normal error regression model is not applicable. 2. Zero mean heteroscedasticity When the dependent variable is a qualitative variable, the error term ei still holds the zero mean. Another problem that arises at this time is that the variance of the error term ei is not equal. 3. Restriction of regression equation When the dependent variable only takes 0 or 1, the regression equation represents the probability distribution, so the mean value of the dependent variable is limited as

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follows: 0  E ðyi Þ  1. The general regression equation itself does not have this restriction, and the linear regression equation yi ¼ b0 þ b1 Xi þ ei will exceed this limit. 2.1.3 Logistic Regression Model The dependent variable takes only two discrete values of 0 and 1, and the proportional b ¼ ni of yi ¼ 1 is called the relative frequency, which is used as an estimate number P Ni b i will be a good estimate of Pi . The of every Xi true Pi . If the sample is quite large, P b i can be as follows: estimated logistic regression model using P b L i ¼ ln

bi P bi 1P

! ^ þb ^ Xi ¼b 0 1

ð3Þ

If the number of observations is Ni large enough, each observation of Xi can be considered as an independent binomial variable, so ui  [0; N P 11P ] is to say, ui i ið iÞ obeys the normal distribution whose mean value is zero and variance is N P 11P . i ið iÞ 1  as an estimator of r2 . Therefore, we can use r2 ¼ Ni b P i 1b Pi Steps to estimate the logistic regression model: b ¼ ni for each Xi . Step 1: Calculate the estimated probability P Ni   b P i Step 2: Calculate b L i ¼ ln ¼ b1 þ b2 Xi þ ui for each Xi . 1bP i Step 3: The following transform to solve the problem of heteroscedasticity: pffiffiffiffiffi pffiffiffiffiffi pffiffiffiffiffi pffiffiffiffiffi wi Li ¼ wi b1 þ wi b2 Xi þ wi ui , It can be abbreviated as pffiffiffiffiffi   Li ¼ wi b1 þ b2 Xi þ vi , among them: weight wi ¼ Ni Pi ð1  Pi Þ, Li can be transformed and weighted to get Li , Xi can be transformed and weighted to get Xi . vi denotes the error term of the transformation, and it is easy to verify that the transformed error term vi has the same variance; Step 4: Using OLS estimation pffiffiffiffiffi pffiffiffiffiffi pffiffiffiffiffi pffiffiffiffiffi wi Li ¼ wi b1 þ wi b2 Xi þ wi ui ; Step 5: Establish confidence intervals and test hypotheses according to OLS. 2.1.4

To Test the Regression Eq.

1. T test method ^ pffiffiffiffiffiffiffiffi Take the test statistic T ¼ br^1 LXX  tðn  2Þ. When jT j [ ta2ðn2Þ , the regression effect is remarkable.

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2. F test method Take the test statistic F ¼ S

Sregression ðn2Þ

test =

 Fð1; n  2Þ.

When F [ Fað1;n2Þ , the regression effect is remarkable. 3. Correlation coefficient test method n P

ðxi  xÞðyi  yÞ Lxy R ¼ sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffisffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ¼ pffiffiffiffiffiffiffipffiffiffiffiffiffiffi n n Lxx Lyy P P ðxi  xÞ2 ðyi  yÞ2 i¼1

i¼1

ð4Þ

i¼1

When R [ raðn2Þ the regression effect is remarkable. 2.2

Analyzing Software

Using the corresponding functions of SPSS software, such as correlation analysis, regression analysis, and factor analysis, the optimal interval prediction and parameter influence size sorting are solved. The coefficients of influence parameters of imbibition efficiency were estimated and verified by using the corresponding functions of structural equation model analysis and regression analysis in Stata software. The calculation function of MATLAB software was used to solve the polynomial equation and the matrix operation, in order to obtain the best value interval of imbibition efficiency [8].

3 Experimental Methods and Materials 3.1

Experimental Materials

The ML and YT are represented as special low-permeability reservoirs, JY and QX represent ultra-low-permeability reservoirs, and crude oil and formation simulated water are obtained in the corresponding field. The oil–water properties are shown in Table 1. The measurement of the indicators in the experiment was carried out at the formation temperature. The cores used in the experiments were natural cores and purchased outcrop cores with a permeability of 0.1–10.0 mD and a size of 10 cm 2.5 cm. Contact angle test with quartz powder by oil-wet treatment, the use of

Table 1. Oil and water properties used in the experiment Property Crude oil density (g cm−3) The salinity of formation water (mg L−1) Formation temperature °C

ML oilfield 0.8506 23895.7 50

YT oilfield 0.8405 21039.9 63.5

JY oilfield 0.8025 13919.7 70

QX oilfield 0.7989 96926.8 80

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chemical reagents is analytical pure, and the reagent is produced by the National Pharmaceutical Group Chemical Co., Ltd.. The use of petroleum sulfonate was produced by Shengli oilfield and DaQing Refining & Chemical Company, respectively, and other surface active agents were also purchased commercial products. 3.2

Experimental Apparatus and Method

In the experiment, the interfacial tension test was carried out by using the Rotary Drop Interfacial Tension Meter (TEXAS 500 USA). The wettability evaluation was carried out according to the industry standard SY/T 5153–1999 “Reservoir rock wettability measurement” method, using OCA20 video contact angle survey instrument (Data physics company), Viscosity test using BROOKFIELD DV-II + Pro viscometer (Brookfield, USA). The test methods for the displacement efficiency and emulsification stability index are carried out according to the relevant contents of the enterprise standard “Technical Specification for Binary Flooding Surfactants” (Q/SY1583-2013) [9]. The emulsification stability was measured using our self-developed emulsion stability evaluator (RHY-III or RHY-IV) [10, 11]. The method of oil displacement experiment is carried out according to industry standard method “Performance test method of composite flooding system “(SY/T6424-2000). Static imbibition test and the use of instruments can see the national patent technology and self-developed constant pressure and pressure imbibition instrument [12, 13]. The oil sands were formulated with 100–160 mesh quartz sand and dehydrated crude oil, according to the ratio of sand to oil ratio of 7:1, and aging in the formation temperature for more than 1 weeks, the oil sands preparation device is a patented product developed by ourselves [14]. The test of imbibition efficiency is described in the patented technique “a quantitative evaluation method of imbibition effect of imbibition agent” [15]. The calculation formula of imbibition efficiency is: Rim ¼ ðVi =V0 Þ  100, V0 ¼ m=d. Among them, V0 is the original oil volume value in oil sand or rock core; ml; Vi is the volume of the oil that is released at time i, m is the original mass of the crude oil in the oil sands, g; and d is the density of dehydrated crude oil at formation temperature, g/cm3. The permeability force calculation formula is: Fp ¼ Sc  Sp , where Sc is the capillary lift coefficient (dimensionless parameter), Sp is the infiltration velocity (ml/min), both can be determined by experiment, methods and apparatus refer to “Imbibition agent performance evaluation device” [16].

4 Interval Estimation 4.1 4.1.1

Viscosity Ratio Range Estimation of Viscosity Range

1. Experimental data processing The viscosity of the imbibition agent solution, the viscosity of the crude oil, and the viscosity of the simulated water can be measured by a viscometer. The ratio of the viscosity of the crude oil to the viscosity of the imbibition agent solution at the same

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temperature is called the viscosity ratio. There were 310 experimental data on the relationship between the viscosity of the imbibition agent solution and the imbibition efficiency of the core. The interval of viscosity ratio is divided into four small blocks, and the ratio of the imbibition efficiency in each interval is calculated, respectively. The calculation results are shown in Table 2 (Rim is the imbibition efficiency, % is represented by X).

Table 2. Experimental results of partitioning statistics Viscosity ratio Distribution X  50 30  X 6. 4.1.3 Data Analysis of Oil Sand Imbibition Experiment Oil sands imbibition refers to the use of crude oil and the corresponding mesh quartz sand according to the mass ratio of 7:1, and oil sands are used for imbibition experiments after aging for one week, the experimental methods see Sect. 3.2. 1. Data processing 308 sets of experimental data of viscosity ratio and oil sand imbibition efficiency were processed. The results are shown in Table 5. 2. Regression analysis

  p Fitting data with curve Lp ¼ L 1p ¼ a þ b1 ln X þ b2 ln2 X þ b3 ln3 X, the results are shown in Table 6. (1) Model verification a ¼ 0:01; F ð1; 12Þ ¼ 9:33; F ¼ 9:356 [ F ð1; 12Þ ¼ 9:33, the regression equation has a significant effect at a ¼ 0:01 level (reliability was 99.99%). pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi raðn2Þ ¼ r0:01ð10Þ ¼ 0:708; R ¼ 0:757 ¼ 0:87 [ 0:708. The regression equation has a significant effect at a ¼ 0:01 level (reliability was 99.99%). It shows that the model can explain the point change ratio is 75.7%.

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Order number 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

X

N1

n1

P1

1−P1

P1/1−P1

lnX

0.979 1.051 1.194 1.194 1.345 1.542 1.609 1.644 1.796 1.829 2.056 2.233 2.242 2.535 2.535 2.844

10.000 12.000 11.000 20.000 14.000 23.000 11.000 10.000 15.000 18.000 5.000 25.000 16.000 17.000 18.000 20.000

1.000 3.000 3.000 5.000 10.000 13.000 6.000 4.000 4.000 7.000 4.000 11.000 6.000 8.000 10.000 11.000

0.100 0.250 0.273 0.250 0.714 0.565 0.545 0.400 0.267 0.389 0.800 0.440 0.375 0.471 0.556 0.550

0.900 0.750 0.727 0.750 0.286 0.435 0.455 0.600 0.733 0.611 0.200 0.560 0.625 0.529 0.444 0.450

0.111 0.333 0.375 0.333 2.500 1.300 1.200 0.667 0.364 0.636 4.000 0.786 0.600 0.889 1.250 1.222

−0.021 0.050 0.177 0.177 0.296 0.433 0.476 0.497 0.586 0.604 0.721 0.803 0.807 0.930 0.930 1.045

ln(P1/ 1−P1) −2.197 −1.099 −0.981 −1.099 0.916 0.262 0.182 −0.405 −1.012 −0.452 1.386 −0.241 −0.511 −0.118 0.223 0.201

Table 6. Model and parameter estimation Equation Model summary Parameter estimation F df1 df2 Sig. constant b1 b2 b3 R2 cubic 0.757 9.356 3 9 0.004 −1.744 14.519 −31.606 19.054

(2) Interval forecast Predicting the optimal interval with the model that has passed the test.   P LP ¼ ln 1P

ð11Þ

¼ 1:744 þ 14:519 ln X  31:6 ln X þ 19 ln X 2

L0P ¼

14:52  63:2 ln X þ 57 ln2 X ¼0 X

3

ð12Þ

D ¼ b2  4ac ¼ 683:68

ð13Þ

pffiffiffiffiffiffiffiffiffiffiffiffiffiffi 63:2 683:68 63:2 26:15 ¼ ðln X Þ1;2 ¼ 2  57 114

ð14Þ

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63:2 þ 26:15 ¼ 0:78 114 63:2  26 ln X2 ¼ ¼ 0:325 114 ln X1 ¼

L00P ¼

77:2 þ 177:2 ln X  57 ln2 X X2

ð15Þ

When ln X1 ¼ 0:78 77:2 þ 177:2 ln X  57 ln2 X 26:35 ¼ [0 2 X2   X P LP ¼ Ln 1P

L00P ¼

¼ 1:744 þ 14:519 ln X  31:6 ln2 X þ 19 ln3 X Prove that LP has minimal values, 

LPmin

 P ¼ Ln 1P ¼ 1:744 þ 14:519  0:78  31:6  0:782 þ 19  0:783 ¼ 0:628 ðgive upÞ

When ln X2 ¼ 0:325, L00P ¼

77:2 þ 177:2  0:33  57  0:332 20:77 ¼ \0 X2 X2

It is proved that   P LP ¼ ln 1P ¼ 1:744 þ 14:519 ln X  31:6 ln2 X þ 19 ln3 X has maximum value and the maximum is 0.29. Therefore, X2 ¼ e0:33 ¼ 1:4, the percentage of imbibition efficiency was 57%. Let P ¼ 0:5; 0 ¼ 1:744 þ 14:519 ln X  31:6 ln2 X þ 19 ln3 X; ln X ¼ 0:2; X ¼ e0:2 ¼ 1:22; ln X ¼ 0:5; X ¼ e0:5 ¼ 1:6; ln X ¼ 0:98; X ¼ e0:98 ¼ 2:66:

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The range of viscosity ratio is (1.2, 1.6) [ (2.7,80); the rate of high imbibition efficiency is more than 50%. Let P ¼ 0:7, 0:85 ¼ 1:744 þ 14:519 ln X  31:6 ln2 X þ 19 ln3 X; Solution is ln X ¼ 1:065; X ¼ e1:065 ¼ 2:9. Therefore, the optimum interval of viscosity ratio is X > 2.9, and the proportion of high imbibition efficiency is higher than 70%. Considering the experimental results of core and oil sands, the optimum interval for determining the viscosity ratio is X > 2.9 and X = 8 is the best point. 4.2

The Best Range of Permeability Force Ratio

4.2.1 Permeability Evaluation Experiment of Imbibition Agent How to assess the permeability of the imbibition agent, so far no reports have been reported. In order to give a quantitative description of the method, we put forward the “permeability force” concept. Permeability force definition: permeability force is the product of the infiltration velocity and the lift coefficient, which is used to represent the physical quantity of the permeation and diffusion capacity of the imbibition agent molecules in the porous media of the actual reservoir. Its unit is ml/min. Permeability force (FP ) = Lift coefficient (Sc )  Infiltration velocity (Sp ). Infiltration velocity (Sp ): A certain amount of imbibition agent flows through the volume of oil sands in the graduated tube over a unit time. Capillary lift coefficient (Sc ): The lifting height (h, mm) of the imbibition agent in the capillary is divided by the capillary radius (r, mm). This physical quantity is no unit. We usually use the permeability ratio when comparing the permeability of different imbibition agents, that is to say, the permeability force of the imbibition agent solution is divided by the permeability force of the formation simulated water. 1. Experimental data There are 52 sets of laboratory physical simulation data about the relationship between permeability force and core imbibition efficiency. After standardized treatment, the logarithmic relationship between permeability force ratio and imbibition efficiency is plotted, as shown in Fig. 2. 2. Regression analysis Variable description: The dependent variable lnRim is represented by lnY. The independent variable ln(Fp agent/Fp water) is represented by lnX. Fitting data with curve ln Y ¼ a þ b1 ln X þ b2 ln2 X, the results are as follows (Table 7).

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Fig. 2. Scatter diagram of relation between ln(FP agent/FP water) and lnRim

Table 7. Model and parameter estimation Equation quadratic

Model summary F R2 0.747 72.345

f1 2

f2 9

Sig. 0.000

Parameter estimation constant b1 -0.077 0.166

b2 −0.002

(1) Regression model verification a ¼ 0:01;

F ð1; 40Þ ¼ 12:61;

F ¼ 72:45 [ F ð1; 40lÞ ¼ 12:61:

The regression equation has a significant effect at a ¼ 0:001 level. raðn2Þ ¼ r0:01ð50Þ ¼ 0:478;

R¼

pffiffiffiffiffiffiffiffiffiffiffi 0:747 ¼ 0:8642 [ 0:4788:

The regression equation has a significant effect at a ¼ 0:01 level (reliability was 99.99%). The explanation that the point has 75% proportional changes can be explained by the model. (2) Predict the best interval ln y ¼ 0:077 þ 0:166 ln X  0:002 ln2 X

ð16Þ

ln y ¼ 0:002ðln X  41:5Þ2 þ 3:37

ð17Þ

When ln X ¼ 41:5, ln y ¼ 0:002ðln X  41:5Þ2 þ 3:37. It has the maximum value. Let y ¼ 1; ln X ¼ 41:5  41 ¼ 0:5 ) X ¼ e0:5  1:65 The permeability force ratio should be greater than 1.65, and the imbibition efficiency of core experiment is higher than 1.

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4.2.2

Experimental Data Analysis of Oil Sands

1. The experimental data were collated and calculated (55 groups). There are 55 sets of experimental data about the imbibition efficiency and permeability force ratio of oil sands. After standardized treatment, a scatter diagram of logarithmic relation between them is drawn (Fig. 3).

Fig. 3. Scatter diagram of the relationship between ln(FP agent/FP water) and lna

2. Regression analysis (1) Data is fitted with curve ln Y ¼ a þ b1 ln X þ b2 ln2 X þ b3 ln3 X, and the results are shown below (Table 8). Table 8. Model and parameter estimation Equation Model R2 quadratic 0.145 cubic 0.357

summary Parameter estimation F df1 df2 Sig. constant b1 b2 b3 2.718 2 2 0.081 3.569 0.295 −0.069 5.729 3 1 0.003 3.588 0.703 −0.496 0.092

(2) Regression model verification a ¼ 0:025;

F ð1; 60Þ ¼ 5:29;

F ¼ 5:729 [ 5:29:

The regression equation has a significant effect at a ¼ 0:025 level (reliability was 99.975%). raðn2Þ ¼ r0:01ð60Þ ¼ 0:325;

R¼

pffiffiffiffiffiffiffiffiffiffiffi 0:325 ¼ 0:60 [ 0:325:

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The regression equation has a significant effect at a ¼ 0:01 level (reliability was 99.99%). The model can be used to explain the change of 37.5% point. (3) Interval forecast L ¼ ln Y ¼ 3:588 þ 0:703 ln X  0:496 ln2 X  0:092 ln3 X; L0 ¼

0:703  0:992 ln X  0:276 ln2 X ¼ 0; X

Solution is ln X ¼ 0:964; L00 ¼

X 2 ð1; 30Þ

X 2 ð1; 30Þ

ð18Þ

ð19Þ

ln X ¼ 2:63

0:992 þ 0:552 ln X X2

X 2 ð1; 30Þ

ð20Þ

When ln X ¼ 0:964, L00 ¼

0:992 þ 0:552  0:964 \0; X2

X 2 ð1,30Þ

Prove that when ln X ¼ 0:964, or that is X ¼ e0:964 ¼ 2:622, the function has a maximum value. When ln X ¼ 2:63, L00 ¼

0:992 þ 0:552  2:63 [ 0; X2

X 2 ð1,30Þ

It proves that ln X ¼ 2:63 or that is X ¼ e2:63 ¼ 14, the function has a minimum and the minimum is 3.77, this time the imbibition efficiency is 43%, also shows that the point in a good range. When ln X ¼ 0:3 or X ¼ e0:3 ¼ 1:35, the imbibition efficiency is 30% and this is within a good range. Therefore, the permeability force ratio should be greater than 1.35 in the fine oil sands experiment, and the imbibition efficiency of oil sands is higher than 30%. (4) The range of the permeability force ratio is analyzed by the quadratic equation ln y ¼ 3:57 þ 0:295 ln X  0:069 ln2 X; ln y ¼ 3:886  0:069ðln X  2:14Þ2 When ln X ¼ 2:14; X ¼ e2:14 ¼ 8. Imbibition efficiency is the highest. Let y ¼ 30, 3:4 ¼ 3:886  0:069ðln X  2:14Þ2 , solution is: ln X ¼ 0:58, X ¼ e0:58 ¼ 1:76; ln X ¼ 3:7, X ¼ e3:7 ¼ 40. The permeability force ratio of fine oil sands is higher than 30% in the (1.76, 40) interval.

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The absolute value of the fine oil sands formula is obviously higher than the absolute value of the core experiment, which shows that the permeability force ratio has a greater impact on the imbibition efficiency of fine oil sands. The best range of permeability force ratio in core experiment was larger than 1.65. The optimum interval of the permeability force ratio in the oil sands experiment is greater than 1.35. Considering the two analysis results, so as to determine the optimal range of permeability force ratio is greater than 1.35. And the best point is X = 8.

5 Conclusions The optimal range of permeability force ratio and viscosity ratio was estimated by binary response regression equation and curve-fitting method. Through the regression analysis and model verification, the optimal interval of each parameter in the rock pore of the special/ultra-low-permeability reservoir is determined: (1) The experimental results of imbibition efficiency and viscosity ratio of 310 groups of cores were analyzed by curve-fitting method. The results show that the optimal viscosity ratio is (2.28). (2) The regression analysis of the imbibition efficiency and viscosity ratio of 310 sets of cores was carried out by using two element response method. The results show that the model has passed a significant verification at a ¼ 0:01 level (reliability was 99.99%), and the model can explain the change of 70% point, the best value of viscosity ratio is above 6. Regression analysis was carried out on 308 groups of oil sands experimental results. The results show that the model has passed a significant verification at a ¼ 0:01 level (reliability was 99.99%), and the model can explain the change of 75.7% point, the best value of viscosity ratio is above 2.9. Considering the results of core and oil sands, the optimum range of viscosity ratio is greater than 2.9. (3) Regression analysis was conducted on 52 groups of experiments about core imbibition and imbibition agent permeability. The model passed the significant verification at a ¼ 0:01 level (reliability was 99.99%), and the model can explain the change of 75% point. Therefore, the permeability force ratio of the high imbibition region was determined to be greater than 1.65 (the daily imbibition efficiency was higher than 1.0%). The regression analysis was performed on 55 groups of oil sands experiments. The model passed the significant verification at a ¼ 0:01 level (reliability was 99.99%), and the model can explain the change of 37.5% point. When the permeability force ratio is better than 1.35, the imbibition efficiency is better (above 30%). Considering the core and oil sands experimental results, it is recommended that the permeability force ratio of the imbibition agent in the special/ultra-low-permeability reservoir is greater than 1.35, and the best point of permeability force ratio is 8.

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Acknowledgements. This study was supported by the National Natural Science Foundation of China: (1) Physical and chemical initiation mechanism of crude oil in micro–nano-pores. No.51774318. (2) Development and application of imbibition agent for special/ultra-low-permeability reservoir. No.2015yj-03.

References 1. Aronofskfsky J, Masse L, Natanson SG. A model for the mechanism of oil recovery from the porous matrix due to water invasion in fractured reservoir. Trans AIME1958, 17–9. 2. Zhang Y, Cai H, Fan J, et al. Device for evaluating the performance of imbibition agent: China, 201520120972.4, 05 Aug 2015. 3. Zhang Y, Liu H, Zhu Y, et al. A comprehensive quantitative evaluation method of emulsifying properties. In: 2014 International conference on experimental and applied mechanics (EAM 2014), Miami, USA, 20–21 Jan 2014. 4. Zhang Y, Fu C, Zhu Y, et al. Nonlinear regression analysis of binary flooding recovery influence factors, ICCMME2013, Zhuai, Guangdong, China, 10–11 Dec 2013. 5. Zhang Yi, Wu Kang-yun, Rao Huan, et al. Imbibition oil recovery theory and influencing factors: a review, ICEEP 2014. Adv Mater Res. 2014;962–965:429–36. 6. Huixuan Gao. Application of multivariate statistical analysis. Beijing, China: Peking University Press; 2011. 7. Xie L, Song Z, He X. SPSS statistical analysis using tutorial,2nd ed.; People’s Posts and Telecommunications Press: Beijing, China, 2013. 8. Wang D. Multivariate statistical analysis and SPSS application. Shanghai, China: East China University of Science and Technology Press; 2010. 9. Q/SY1583-2013, Binary composite drive with surfactant technical specifications. Beijing: China Petroleum Enterprise Standard, 2013. 10. Liu Hualong, Zhang Yi, Li Yiqiang, et al. Influence on emulsification in binary flooding of oil displacement effect. J Dispersion Sci Technol. 2016;37:89–96. 11. Zhang Y, Zhu Y, Wu J, et al. An instrument for evaluating emulsification stability of crude oil: China, 201210265482.4, 04 July 2014. 12. Zhang Y, Han D, Ma D, et al. An instrument for spontaneous imbibition: China, 201120075849.7[P]. 09 Nov 2011. 13. Zhang Y, Fan J, Zhu Y, et al. Imbibition instrument: China, 201110252824.4. 04 May 2014. 14. Zhang Y, Ma D, Liu H, et al. Quantitative evaluation method for imbibition oil recovery effect of imbibition agent: China, 201310451182.X. 10 Feb 2016. 15. Yi Zhang, Desheng WU, Kangyun Wu, et al. An experimental oil sands preparation device: China, 201420343137.2. 26 Nov 2014. 16. Zhang Y, Cai H, Fan J, et al. Device for evaluating performance of imbibition agent: China, 201520120972.4, 05 Aug 2015.

Influence of Low-Frequency Vibration Acceleration on the Permeability of Low Permeable Porous Media During Water Flooding Liming Zheng1,2(&), Wenhao Cui3, Jing Liu2, and Lei Zhang4 1

College of Vehicles and Energy in Yanshan University, 066004, Qinhuangdao, China [email protected] 2 College of Petroleum Engineering in China University of Petroleum(East China), 266580, Qingdao, China 3 Oil & Gas Technology Research Institute in Changqing Oil Company, CNPC, 710018, Xi’an, China 4 Department of Petroleum Engineering in China University of Geosciences, 430000, Wuhan, China

Abstract. Seismic production technology utilized physical wave field to stimulate the reservoir. Though this technology was applied once in the oil fields, the mechanisms were not analyzed comprehensively. Influence of lowfrequency vibration acceleration instead of vibration frequency on rock properties of low permeable rock during water flooding was studied thereby. The variations of absolute or relative permeability were talked in detail. With introduction of four relative permeability models, coefficients of the models were matched and the change of pore size of rock under low-frequency vibration was discussed indirectly. It was found that, besides the vibration frequency, the vibration acceleration had also affected the properties of low permeable rock during water flooding. The absolute permeability, which decreased gradually due to stress sensitivity, had been retrieved partly by vibration. When the vibration acceleration was chosen properly, the relative permeability of water phase could be decreased and the relative permeability of oil phase could be enhanced. Because of the improved hydrophilicity of rock by vibration, violent

Copyright 2018 Shaanxi Petroleum Society This paper was prepared for presentation at the 2018 International Field Exploration and Development Conference in Xi’an, China September 18–20, 2018. This paper was selected for presentation by the IFEDC Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the IFEDC Committee and are subject to correction by the author(s). The material does not necessarily reflect any position of the IFEDC Committee, its members. Papers presented at the Conference are subject to publication review by Professional Committee of Petroleum Engineering of Shaanxi Petroleum Society. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of Shaanxi Petroleum Society are prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of IFEDC. Contact email: [email protected]. © Springer Nature Singapore Pte Ltd. 2020 J. Lin (ed.), Proceedings of the International Field Exploration and Development Conference 2018, Springer Series in Geomechanics and Geoengineering, https://doi.org/10.1007/978-981-13-7127-1_7

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vibration acceleration might enhance the oil recovery in low permeable formation. Through matching four relative permeability models, a mechanism as enlarging the pore size distribution by vibration was verified further. It helped to substitute the capillary force test, which required a static measurement background and provided only experimental data of samples before or after vibration. Keywords: Vibration acceleration model
Pore size




Water flooding




Relative permeability

1 Introduction The crude oil price had decreased sharply in the last years, which hit the oil production seriously. In recent days, Corp. Petroteq had announced that BRPT was a low-cost technology for extremely shallow field to adapt to the serious background of low oil price. A key in this technology was that a physical wave field stimulated by artificial wave source was used. This news had made a surprise and might brought new vitality for technologies which were closely related to wave source. Two classical technologies utilizing wave during oil and gas field development process were seismic production technology and ultrasonic production technology. Seismic production technology used low-frequency wave, and ultrasonic production technology used high-frequency or ultrasonic wave. It had a substantial advantage in low wave attenuation and large operating range of 1–2 km. Till now, seismic production technology had been used successfully in low permeability or heavy oil reservoirs of many fields. The mechanisms were verified with experiments, numerical studies, and field trials [1]. Besides the well-known mechanisms such as pressure supplement, permeability increase, and recovery enhancement, this technology was attractive as a physical method. It was environmental friendly and of low pollution to the reservoirs. Though there was a controversial statement worrying the damage to the cement, noise pollution, and minor effect, the unfavorable factors could be controlled after optimization of operating parameters. Especially, the low cost was very tempting and the harm was minor 50 m away from the source [2]. The experiments verified that seismic production technology improved oil recovery during water flooding through complex mechanisms [3, 4]. Though qualitative cognitions to the micromechanisms were obtained, the extent of influence of low-frequency vibration on rock property was not still clear. For the object of optimization of operating parameters, quantitative study on the microvariation of rock properties should be done. A relation between the rock property variation and vibration parameters could be fitted through experiments or derived through dynamic mathematic analysis. Yan [5] analyzed the dimensionless relative flow velocity and porosity under different vibration frequency with capillary model. Sudo [6] and Shang [7] investigated the deformation of a drop under vibration in vertical direction and horizontal direction, respectively. Elkhoury [8] investigated the influence of pore pressure oscillations on the effective permeability of rocks fractured after placement in an experimental apparatus. An approximate semi-log relation was

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found between normalized permeability increase and normalized pressure amplitude. The authors [9] also found a double-log relation between normalized permeability increase and solid displacement amplitude. Regardless of the specific values, a good agreement with the trend was achieved. Manga [10] reviewed the progress in changes in action distance, water level, and permeability. He also gave the mechanisms that enhance permeability as mobilization of particles, drops, and bubbles. Deng [11] presents a theoretical fluid dynamics model to describe how low-frequency elastic waves mobilize isolated droplets trapped in pores by capillary resistance. The ability of the theoretical model to predict the critical mobilization amplitudes and the displacement dynamics of the non-wetting droplet were validated. Karve [12, 13] outlined a systematic framework to assess the reliability of wave energy delivery to subsurface formations through numerical simulation. The characteristics of low permeability rock during water flooding under lowfrequency vibration were studied with experiments in this paper. A comparison of the absolute permeability at different water flooding stages before and after vibration was conducted. The relative permeability was got with unsteady-state technique. The fitting parameters in several classical functions about relative permeability were then derived, which explained indirectly the influence of low-frequency vibration on rock wettability and average pore radius. In the last, the variation of irreducible water saturation and the average pore radius was combined to describe the variation of capillary force cure under vibration. The analysis was used to provide a theoretical reference for mechanism explanation in seismic production technology.

2 Experiments and Results 2.1

Experimental Materials and Equipment

In the experiment, the simulated oil was a mixture of crude oil from Fengfuchuan oil field (79.9% saturates, 17.06% aromatics, 3.04% resins and asphaltenes) and kerosene with a proportion of 1:1. The viscosity of simulated oil at 30 °C was 28.8 mPa s. The simulated injection water was a solution of sodium chloride, calcium chloride, and magnesium chloride of mass concentration 70%: 12%: 18%. The simulated water was with a salinity of 40000 mg/L. The low permeable sand rocks were with similar gas permeability of 28  10−3 lm2. The main instruments (Fig. 1) included a horizontal vibration table (made by Haian Oil Research instruments Co. Ltd., China), a core holder, and 2PB00C-type constant flux pump(Beijing Feisifurui Technology Ltd., China). 2.2

Experimental Procedure

(1) Method of absolute permeability under vibration According to the conditions of oil reservoirs in Fengfuchuan oil field, the experiments were done at a constant temperature of 44 °C. The permeability of low permeable rock was measured at three times: end of water saturation kw1 , end of oil saturation (before and after vibration), and end of water flooding kw2 . After 8 h (no water flowed out) for oil saturation process, the oil permeability koi and irreducible water saturation Swci were

Influence of Low-Frequency Vibration Acceleration …

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oven distilled water pump

pressure gauge valve

simulated water

rock holder

vf

pump

back pressure valve

us vibration table simulated oil

graduated cylinder mass balance

Fig. 1. Schematic diagram of water flooding under low-frequency vibration

measured. Then, the low-frequency wave stimulation of certain vibration parameters was activated until the end of the experiment. The direction of vibration was the same as the flow velocity. The operating frequency was chosen 20 Hz which was close to the natural frequency of matrix. Water was produced again under vibration. After 4 h (no water flowed out) for second oil saturation, the oil permeability kom and irreducible water saturation Swcm were measured again. Through changing the vibration acceleration 0.1–0.6 m/s2, the influence of vibration intensity on absolute permeability of low permeable rock during water flooding was conducted. The variation of irreducible water saturation was defined as rSwc ¼ 1  Swcv =Swci . (2) Testing of relative permeability under vibration During the water flooding process, the outputs of oil and water were recorded and used for calculation of relative permeability with unsteady-state technique. The saturation at equal-permeability point was got from the relative permeability curve. The residual oil saturations of rocks after water flooding under vibration Sorm or without vibration treatment Sori as well as the equal-permeability point were calculated.

3 Variation of Rock Properties Under Vibration The influence of low-frequency vibration acceleration on absolute permeability, relative permeability, displacement efficiency of low permeable rock in water flooding was got as below. 3.1

Changes in the Absolute Permeability

The absolute permeability during water flooding in low permeable rock was found to decrease with time. For example, the rock without vibration treatment had a water permeability of 18.04  10−3 lm2 during water saturation, an oil permeability of 9.27  10−3 lm2 after oil saturation, and a water permeability of 2.12  10−3 lm2 at the end of water flooding. The decrease in pore pressure during water flooding and the

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increase in stress sensitivity effect had caused the reduction in absolute permeability value [14, 15]. The ratios including kom =koi and kw2 =kw1 were used to demonstrate the influence of low-frequency vibration acceleration on absolute permeability. The ratio kov =koi reflected a direct effect of vibration on flow connectivity of rock. The ratio kw2 =kw1 reflected an indirect effect on retrieve of producing energy and decrease in stress sensitivity. The above ratios under different vibration acceleration are shown in Fig. 2.

Fig. 2. Variation of absolute permeability and inducible water saturation under different vibration acceleration

Obvious fluctuation was found with both curves. Many papers had shown that artificial seismic could improve the permeability of the rock, especially around the natural frequency. However, the ratio kov =koi was lower than 1.0 when the acceleration was in the range 0.1–0.4 m/s2, whereas the ratio was larger than 1.0 when the acceleration was larger than 0.4 m/s2. When the vibration frequency was kept constant, the vibration amplitude indeed influenced the wave-induced cross-motion between solid and fluid. The cross-motion stimulated by sustained wave seemed to enhance the initial flow rate only when the vibration amplitude exceeded a certain value. There might exist a local optimal vibration amplitude to obtain the best enhancement of low connectivity in the low permeable rock saturated with low viscosity fluid. A stronger fluctuation inclined to cause desorption of liquid droplet from the rock surface. The isolated dispersing liquid droplet in the pore throats would also be carried out more easily by another displacement fluid, which can be verified by the variation of irreducible water saturation under vibration to some extent. The largest decrease in inducible water saturation (13.70%) and largest increase in absolute oil permeability (3.04%) were found at 0.5 m/s2. The phenomena indicated that both vibration amplitude and vibration frequency were important for proper effect of the artificial seismic production technology. The data of kw2 =kw1 shown the mechanism of artificial seismic production technology just as in other articles [16, 17]. The rock stimulated with vibration had a larger absolute permeability after water flooding in contrast to that without vibration treatment after water flooding. The indirect effect on retrieve of producing energy and decrease in

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stress sensitivity was achieved. This ratio got a maximum value at 0.3 m/s2, which was different from that for kov =koi . The proper amplitude was suggested to be 0.3–0.5 m/s2 to improve the whole flow conductivity combing the trends of kov =koi , kw2 =kw1 , and rSwc . 3.2

Changes in the Relative Permeability

The influence of vibration on relative permeability was talked in some papers [18, 19]. The effects of lowering the inducible water saturation and residual oil saturation, increasing the oil permeability, as well as decreasing water permeability can also be found in Fig. 3. It was notable that the horizontal axis—water saturation Sw —was normalized. Though the rock samples were of same components as well as similar porosity and gas permeability, they had different irreducible water saturation and residual oil saturation without vibration because of the anisotropy and individual difference of the samples. The normalized water saturation for samples was defined as the product of water saturation without vibration treatment and ð1  rSwc Þ.

Fig. 3. The variation of relative permeability curve (a) and equal-permeability point (b) under vibration

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The maximum decrement of water permeability and the maximum increment of oil permeability were found around the vibration acceleration of 0.3–0.4 m/s2. Here, the oil/water permeability here referred to the relative permeability of a certain phase during water flooding. The oil/water permeability in Sect. 3.1 referred to the absolute permeability before or after water flooding, when one kind of fluid flowed mainly as a continuous phase. The isotonic points mainly move rightward under vibration. The variation of isotonic points meant that the hydrophilicity of rock was improved, which also verified the conclusion of other researchers [20, 21]. The vibration enhanced hydrophilicity of core achieved the highest increase under vibration acceleration of 0.3–0.4 m/s2. Though the mechanism of artificial seismic production technology as decreasing the inducible water saturation and connate oil saturation was talked, the trend of vibration amplitude versus connate oil saturation was scarcely shown. The variation of residual oil saturation under different acceleration rSor in Fig. 4 was defined as Eq. 1 instead of Sorv =Sori  1. Though it was easy to make comparison between the irreducible water saturations under different vibration acceleration (measured before water flooding), the variation of residual oil saturation had to consider the influenced by the sample difference and various initial oil saturations.

Fig. 4. Variation of residual oil saturation under different vibration acceleration

rSor ¼

Sorv Swcv 1 Swci Sori

ð1Þ

Wherein rSor is the variation of residual oil saturation under vibration; Sorv and Sori are the residual oil saturations of rocks after water flooding under vibration or without vibration treatment, respectively; irreducible water saturation Swci and Swcv are the irreducible water saturation under vibration or without vibration treatment, respectively.

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According to Eq. 1 and experimental data, rSor was negative at most of the vibration accelerations. In addition, rSor was found positive at 0.2 and 0.3 m/s2, where the maximum equal-permeability point and increment of oil relative permeability were achieved. The relation between proper vibration acceleration, residual oil saturation (negatively correlated with oil recovery), and wettability might be linked in low permeable sand rock under vibration. Anyway, it seemed that the residual oil saturation was prone to be decreased at violent vibration. As in Fig. 5 (left side), the main mechanisms of oil recovery enhancement of seismic production technology included detachment of a droplet from the soil surface and the droplet passing through a blocking throat successfully under a violent low-frequency vibration. The contact angle between oil phase and soil surface increased gradually to achieve a separation from the continuous phase. The decreases of residual oil saturation in Fig. 4 and in Fig. 2 inducible water saturation were mainly caused by these two mechanisms. Besides the increase in hydrophilicity, the decrease in oil viscosity had also enlarged the oil–water mobility ratio, which displaced water into smaller pore-throat and uniformed the waterflood front relatively. A strong vibration treatment was suggested in the field trial, and a negative effect might be caused by the artificial seismic production technology when an improper acceleration was set.

Initial droplet

Uniformed waterflood front in heterogeneous pore-throats No vibration

Droplet on the surface

Hydrophilicity Deformation Separation enhancement of droplet

Vibration stimulated

Retained dispersed phase

Deformation and stimulated by wave

Pass into a next pore

Fig. 5. The mechanism for oil recovery enhancement by vibration (droplet deformation and assisted displacement by wave)

4 Fitted Parameters About Relative Permeability and Pore Size Distribution Laboratory determination methods of effective permeability and relative permeability included steady-state techniques, unsteady-state techniques, empirical techniques, and calculation from field data [22, 23]. The relative permeability curve in this paper was got through experiments with unsteady-state technique. In unsteady-state techniques, the production data were dealt, and a set of relative permeability curves were obtained using various mathematical methods, which were based on the Buckley–Leverett

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equation for linear displacement of immiscible and incompressible fluids. Although the curves were got, a visible evaluation was only made with the variation of equalpermeability point, water or oil relative permeability. A deep discussion around the influence of low-frequency vibration on physical properties was needed. It may be conducted through curve match based on the empirical techniques such as Corey’s model and Land’s model. Chen [24] and Ataie [25] listed several classic models which were widely used in reservoir engineering. Here, the functions including VGM, VGB, BCM, and BCB were referred in this paper to match the relative permeability curves. In VG model, the functions of the capillary and permeability related to water saturation were in Eqs. 4–6. It was assumed that m ¼ 1  1=n. The fitted parameters in VGM model and VGB model are both shown in Fig. 6. A proper assumption of g = 0.5 was based on the intermediate wettability of the rock without vibration treatment in Fig. 3, which was also given in Chen [24] in parameter optimization. The minor decrease in the values of n and m indicated that the width of pore size distribution seemed to increase generally with a large vibration acceleration. With a similar right value of main interval in pore size distribution (Fig. 7) before and after vibration in Yang [26], the probability distribution of large pore radius was increased. However, the width of pore size distribution at the acceleration 0.3 m/s2 was smaller than that without vibration treatment.

Fig. 6. The variation of fitted parameters in VG model under different vibration acceleration

Correspondingly, the probability distribution of large pore radius might have decreased to cause a high value of variation of residual oil saturation in Fig. 4. In addition, the fitted parameters in VGM model were a little larger than those in VGB model. The fitted parameters in both model had similar trend with vibration acceleration increasing. The values of m and m
n were in the range of 0.017–0.31 and in the range of 0.034–0.73, respectively, with the vibration acceleration 0–0.6 m/s2.

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Fig. 7. The increase in width of pore size distribution and pore size after vibration in rock 4-1-1 in Yang [26]


n m VG model; Sew ¼ 1 þ avg hc

ð4Þ


m 2 ; VGM model, krw ¼ Sgew 1  1  Sm ew
g m 2m kro ¼ ð1  Sew Þ 1  Sew

ð5Þ


m  ; VGB model, krw ¼ S2ew 1  1  Sm ew
2 m m kro ¼ ð1  Sew Þ 1  Sew

ð6Þ

Wherein Sew is the normalized water saturation; hc is capillary force height; avg is a fitting parameter inversely proportional to the non-wetting fluid entry pressure value; n is a fitting parameter inversely proportional to the width of pore size distribution; g is the tortuosity parameter. In BC model, the functions of the capillary and permeability related to water saturation were in Eqs. 7–9. The fitted parameters in BC model are shown in Fig. 8.

Fig. 8. The variation of fitted parameters in BC model under different vibration acceleration

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BC model; Sew ¼ ðhe =hc Þk ; hc [ he ; Sew ¼ 1; hc  he g þ 2 þ 2=k BCM model; krw ¼ Sew ;

 2 kro ¼ ð1  Sew Þg 1  S1ewþ 1=k

BCB model; krw ¼ S3ewþ 2=k ;

  kro ¼ ð1  Sew Þ2 1  S1ewþ 2=k

ð7Þ

ð8Þ

ð9Þ

Wherein he equaled to the non-wetting fluid entry pressure; k is the characteristic soil parameter, characterizing the pore size distribution. The fitted value of k under certain vibration acceleration in BCM model was almost same with that in BCB model. It decreased generally with violent vibration. The VG model was asymptotically equaled to the BC model in the dry range when hc becomes large, Sew ¼ ½ð1  aÞ=hc mn , such that 1  a ¼ he and k ¼ m
n. Because the experimental rock was low permeable, the capillary force was large enough. A similar trend of k in Fig. 6 with m
n was observed successfully. Certainly, the fitted values of k, were in the range of 0.006–0.11 and lower than m
n. The tortuosity parameter had increased from 0.42 to 0.48 under vibration, which indicated that g = 0.5 in Fig. 6 was properly assumed. The largest value of g was found with 0.3–0.4 m/s2. The mechanisms about seismic production technology had shown than the properties of fluid and rock grain would be a little influenced by low-frequency vibration. Especially, the property of fluid would basically return to its initial value after stopping vibration for a certain time. When avg was assumed to keep constant under lowfrequency vibration, the variation of n would only lead to a minor change of avg as well. The minor decrease in m or k (less than 1.0) would cause the generalized water saturation to increase according to Eqs. 4 and 7. Thereby, the saturation of non-wetting phase was increased when the capillary force curve of rock sample was measured quickly after vibration treatment.

5 Conclusions The properties of rock were affected under the stimulation of artificial seismic production technology, which might improve the injection or production in actual sand reservoir. The influence of low-frequency vibration acceleration on variation trend of properties of low permeable rock during water flooding was studied through experiments and further discussion. The main results can be summarized as follows: (1) It was observed that amounts of the properties during water flooding in a low permeable rock, including conductivity of rock, relative permeability of oil–water phase and oil recovery, were changed under vibration. As the displacement

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proceeded, the conductivity gradually decreased due to the stress sensitivity, but this degree of variation was degraded by vibration. (2) The hydrophilicity of rock was enhanced by vibration, which was indicated from the rightward movement of equal-permeability point, to make the water pass through more throats and to detach more oil droplet from the soil surface. Thereby, the relative permeability of water phase was decreased, and the relative permeability of oil phase was increased. (3) It was concluded that a violent vibration was proper for artificial seismic production technology because of the largest decrease in inducible water saturation and residual oil saturation, as well as the largest improvement in water displacement efficiency. The increased width of pore size distribution under vibration, which was got from relative permeability curve matching, might play a role for above improvement. Acknowledgements. This study was supported by the China Postdoctoral Science Foundation (2018M631765), a grant from Hebei Province Postdoctoral Advanced Programs (B2018003011), Scientific and Technological Research Project of Higher Education Institutions in Hebei Province (QN2019163), and the Doctoral Funds of Yanshan University(BL17024).

References 1. Uetani Takaaki, Matsuoka Toshifumi, Honda Hiromi. Investigation of the conditions required for improved oil recovery by an earthquake. SPE Prod Oper. 2016;31(3):219–27. 2. Yu HL. Experimental study on increase of oil yield by means of artificial ground shaking for an oil pool in Inner Mongolia. Earthquake Eng Eng Vibr. 2000;20(4):148–53. 3. Ariadji T. Effect of vibration on rock and fluid properties: on seeking the vibroseismic technology mechanisms, In: SPE Asia Pacific oil and gas conference and exhibition, Jakarta, Indonesia, April 2005, pp. 1–8. 4. Kurawle I, Kaul M, Mahalle N, et al. Seismic EOR—the optimization of aging waterflood reservoirs. Offshore Europe: Aberdeen, UK, September; 2009. p. 1–5. 5. Yan P. Reservoir analysis using intermediate frequency excitation. Ph.D. Thesis, Stanford University, 1999. 6. Sudo S, Goto A, Kuwano H, et al. The dynamic behavior of liquid droplets on vibrating plate. J JSEM. 2010;10:38–45. 7. Shang XS, Pu CS, Yu GL, et al. Study on micro-dynamic mechanism of droplet motion under vibration. Sci Technol Eng. 2013;13(8):2166–9. 8. Elkhoury JE, Niemeijer A, Brodsky EE, et al. Laboratory observations of permeability enhancement by fluid pressure oscillation of in-situ fractured rock. J Geophys Res Solid Earth. 2011;116(B2):1–15. 9. Zheng LM, Pu CS, Liu J. Influence of low-frequency vibration oil recovery on the initial flow of radial reservoir. Petrol Geol Recovery Effi. 2018;25(1):68–76. 10. Manga M, Beresnev I, Brodsky EE, et al. Changes in permeability caused by transient stresses: Field observations, experiments, and mechanisms. Rev Geophys. 2012;50(2):1–24. 11. Deng W, Cardenas MB. Dynamics and dislodgment from pore constrictions of a trapped non wetting droplet stimulated by seismic waves. Water Resour Res. 2013;49:4206–18.

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12. Karve PM, Kucukcoban S, Kallivokas LF. On an inverse source problem for enhanced oil recovery by wave motion maximization in reservoirs. Comput Geosci. 2015;19:233–56. 13. Karve PM, Kallivokas LF, Manuel L. A framework for assessing the uncertainty in wave energy delivery to targeted subsurface formations. J Appl Geophys. 2016;125:26–36. 14. Li S, Tang DZ, Pan ZJ, et al. Characterization of the stress sensitivity of pores for different rank coals by nuclear magnetic resonance. Fuel. 2013;111:746–54. 15. Geng YG, Tang DZ, Xu H, et al. Experimental study on permeability stress sensitivity of reconstituted granular coal with different lithotypes. Fuel. 2017;202:12–22. 16. Belonenko VN. Vibro seismic technology for increasing hydrocarbon bed recovery”, New Technologies for the 21st Century, Joint English/Russian Magazine, 2000, 4, p. 14. 17. Cidoncha JG. Application of acoustic waves for reservoir stimulation In: International oil conference and exhibition in Mexico, Veracruz, Mexico, June 2007, pp. 1–7. 18. Nikolaevskiy VN, Lopukhov GP, Liao YZ, et al. Residual oil reservoir recovery with seismic vibrations. SPE Prod Facil. 1996;11(2):89–94. 19. Liu J, Pu CS, Lin CY, et al. Effect of low-frequency vibration on a relative permeability curve and irreducible water saturation. In: International conference on artificial intelligence and industrial application, Hangkang, China, January 2015, pp. 889–896. 20. Li MY, Dong ZX, Ji SL, et al. Sound vibration on wettability of rock surface. Acta Petrolei Sinica. 1999;20(6):57–62. 21. Sun RY, Cheng GX. Effect of artificial vibration on liquids flow through porous media. J Hydrodyn. 2004;19(4):552–7. 22. Krause MH, Benson SM. Accurate determination of characteristic relative permeability curves. Adv Water Resour. 2015;83:376–88. 23. Kianinejad A, Chen XY, DiCarlo DA. Direct measurement of relative permeability in rocks from unsteady-state saturation profiles. Adv Water Resour. 2016;94:1–10. 24. Chen J, Hopmans JW, Grismer ME. Parameter estimation of two-fluid capillary pressure– saturation and permeability functions. Adv Water Resour. 1999;22(5):479–93. 25. Ataie-Ashtiani B, Raeesi-Ardekani D. Comparison of numerical formulations for two-phase flow in Porous Media. Geotech Geol Eng. 2010;28:373–89. 26. Yang L, Ma JG, Wei RL, et al. The effects of mechanical vibration on the capillary pressure curve and the wettability of a core. J. Xi’an Petrol Inst 1997;12(5):23–25, 35.

Long Horizontal Section Well Application in Developing Ultra-Low Permeability Layer Baixue Chen(&) Engineering Technology Brigade of no. 8 Oil Production Company, Daqing Oilfield Co.Ltd, Heilongjiang Province, China [email protected]

Abstract. The F oil layer is a typical low permeability reservoir. Conventional development cannot develop the low permeability reservoir effectively, so the long horizontal wells cooperate with volume fracturing in the way to transform the ultra-low permeability reservoirs. Well P1 is the first long horizontal section well drilled by our company. Based on its condition and formation characteristics, it conducts a large-scale multi-segment multi-cluster volumetric fracturing field test of horizontal wells to realize the volume utilization of the layers. The test verifies the feasibility of volume fracturing in the reconstruction of horizontal wells and the applicability of the supporting process in the application of ultra-low permeability reservoirs. At the same time, the fiber sand-adding process test for tight oil type II reservoirs was conducted. After the fracturing, tracer monitoring was performed on the flowback liquid to ascertain the produced fluid of each layer, and it was determined that the crack cutting technology had a good transformation effect. The design and development of well P1 is of guiding significance for the development of horizontal wells in low permeability reservoirs in the future. Keywords: Horizontal wells
Long horizontal section permeability reservoirs
Fracturing




Ultra-low

Copyright 2018, Shaanxi Petroleum Society. This paper was prepared for presentation at the 2018 International Field Exploration and Development Conference in Xi’an, China, September 18–20, 2018. This paper was selected for presentation by the IFEDC Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the IFEDC Committee and are subject to correction by the author(s). The material does not necessarily reflect any position of the IFEDC Committee, its members. Papers presented at the Conference are subject to publication review by Professional Committee of Petroleum Engineering of Shaanxi Petroleum Society. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of Shaanxi Petroleum Society are prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of IFEDC. Contact email: [email protected]. © Springer Nature Singapore Pte Ltd. 2020 J. Lin (ed.), Proceedings of the International Field Exploration and Development Conference 2018, Springer Series in Geomechanics and Geoengineering, https://doi.org/10.1007/978-981-13-7127-1_8

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1 Introduction The utilization rate of our main production reservoir has reached 94.0%. Therefore, as a replacement reservoir, the effective use of the F oil layer will affect the steady production of our crude oil. The F oil reservoir is characterized by poor geological conditions, low porosity, low permeability, small reservoir thickness, small throat radius, undeveloped natural fractures, low formation pressure, and ineffective water injection. The conventional horizontal well development can improve the contact area between wells and strata. However, the effective use of the unrecoverable reserves cannot be greatly improved. Therefore, long horizontal wells cooperate with volume fracturing in the way to realize the effective use of low permeability reservoir [1]. Since 2014, we have drilled six long horizontal wells with an average horizontal section footage of 873.8 m and an average drilling depth of 2954.2 m. Now take P1 well as an example to describe the detailed effect of long horizontal well cooperate with fracturing technology on the transformation of ultra-low permeability reservoirs.

2 Well Condition and Formation Conditions of Well P1 The target layer for well P1 is the F reservoir group. The designed drilling depth is 2915.0 m, the target depth is 1872.0 m, the horizontal section is 2014–2915 m, the footage is 901 m, and the sandstone is 819 m in total. The sandstone drilling rate is 90.9%. Oil immersion is 373 m, oil spot is 333 m, oil trace is 63 m, oil sandstone total is 769 m, and oil sandstone drilling rate is 85.35%. The horizontal well path shows that the reservoir of this group is located in the F oil layer, and the lithology is dominated by siltstone, silt-bearing siltstone, and argillaceous siltstone, with good oil-bearing properties. A total of 53 layers are explained, of which eighteen I-1 tight oil layers, sixteen I-2 tight oil layers, eleven II-1 tight oil layers, six II-2 tight oil layers, and two dry layers. The construction situation and test results show that the flowback rate of fracturing fluid is low and also the reservoir yield. According to the analysis, the physical properties of the reservoir in this well are poor, and the single-slot modification model which controls the volume is small, and it is impossible to achieve a breakthrough in production capacity. An ultra-long horizontal well volume fracturing transformation mode is required. For the tight oil reservoir in this well, the concept of crack cutting and reformation is adopted. By increasing the scale of reform, improving the fracture conductivity and increasing the volume of reservoir control, the reservoir can be effectively transformed.

3 Field Test In order to further verify the increase in the contact area between the fracture and the reservoir, the feasibility and applicability of the sand body volume design concept and supporting technology in the Fuyang oil zone are also verified. At the same time, the long-term stable production of the horizontal well and the elastic production period is

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improved. The fracturing construction scheme of well P1 was optimized from five aspects including fracture spacing, fracture length, flow conductivity, effective fracture support, and construction parameters. 3.1

Fracture Crack Spacing Optimization

The principle for the fractured section design is based on the geological reservoir division. The cracks should be arranged as far as possible in the areas with good oil and gas indications to ensure that the sweet spots are fully reformed, in order to ensure the effective extension and support of the layout cracks. The parameters such as fracture pressure, Young’s modulus, and GR value, which affect the crack initiation and extension of the perforation point in the same section, must be as uniform as or close to each other. In order to reduce interlamellar strata and other issues, there must be a certain length of cementing quality between the fractures. The plug should be placed in a well cemented part; the perforation point and bridge plug location should avoid a certain distance from the coupling, at least 1 m. According to the geology condition of the reservoir and the similarity in terms of physical properties and oil content, similar GR values, similar densities, and similar lithology, sand bodies are classified into tight layer I-1, I-2 and tight layer II-1, II-2. According to geological data, the permeability of the tight layer I-1 and I-2 is 0.3– 1.37 mD, the permeability of the tight layer II-1 and II-2 is 0.01 mD, by comparing permeability and single-seam control the control width of the tight layer I-1 and I-2 is between 35 and 50 m, and that of the tight layer II-1 and II-2 is between 5 and 9 m. Considering the construction safety distance and the control range of the single joint, the perforation position was optimized according to the principle of the fracture layout of the ultra-long horizontal well and the logging interpretation results, and the fracture spacing was optimized. A total of 22 cracks in eight sections were designed in the horizontal well section of the P1 well (Fig. 1).

Fig. 1. Permeability and single-slit control width curves

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Crack Length Optimization

According to the law of distribution of sand bodies, in order to achieve the matching of cracks and sand bodies, the length of cracks is optimized and the maximum sand body is used. The east side of P1 well is adjacent to the fault, and the distance between the wellbore and the fault is 190–316 m. Considering the condition of the sand body and the distance from the fault, the half-length of the fracture is designed to be 170–320 m. Considering the possibility of sand body change and gradual recognition, in the design of fracturing construction parameters, considering the fault distance around the P1 well and the width of the sand body of the river channel, half-length of the fracture is arranged. The impact of the construction was adjusted piece by piece in the later on-site implementation (Table 1; Fig. 2).

Table 1. Design slot length and production forecast after fracturing in well P1 Fractured section 1st 2nd 3rd 4th 5th 6th 7th 8th

Lift (m) 120 120 387 466 442 422 71 85

Right (m) 80 80 97 103 100 54 127 108

Fault distance 410 399 228 190 220 240 312 316

Design Half-length 320 300 200 170 200 220 280 280

Fracturing yield 2.8 2 2.4 2.2 2.4 2.6 3.2 3.1

Fig. 2. P1 sand body distribution and slot length optimization

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High-Pressure Crack Optimization

The drilling layer of well P1 was located at the FI6 layer of the well H3 which is the neighboring well. The target layer had a stress of about 2 MPa and the difference between the GR values of the storage layer reached 51API, and there was a certain lithology block. According to the crack stress and gap spacing and segment spacing formula: "


2 #3=2 h F ¼ 1  x3 x2 þ 2 Substituting the optimized segment spacing and crack spacing, the crack stress interference was calculated. When crossing the fracture, if dx/H > 2, the flow resistance is lower, if dx/H > 2, the slit width is larger; when there is the longitudinal crack, if dx/H > 2, the slit width is larger. According to the simulation of stress disturbance and the seepage distance under different permeability, the height of the adjacent well is about 7–10 m. 3.4

Fracturing Construction Parameter Optimization

I. Fracture cracks conductivity optimization Through simulation studies, because of the low demand for fracture conductivity in low permeability reservoirs and the permeability range of this well, the optimal flow conductivity range is 3.5–26 lm2 cm. Considering factors such as proppant embedding, the design range is 16– 25 lm2 cm (Table 2). Table 2. Matching matrix permeability and optimum fracture inducing capability Permeability 10−3 lm2 0.3 0.5 1.0 1.5 2.0 2.5 3.0

Fracture conductivity lm2 cm 3.5 6.5 22.0 26.0 35.0 40.0 50.0

II. Fracturing fluid optimization According to the surrounding construction conditions of neighboring wells, it is determined that the conventional fracturing fluid formulation system is adopted for well P1. According to the prediction of adjacent wells, the formation temperature of well P1 is predicted to be 86.3 °C. Considering the safety of construction, a fracturing fluid

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system of 90 °C is recommended for the pre-flush stage. Using Fracpt software simulation and previous well temperature measurement data, the temperature of the reservoir can be reduced to below 60 °C after injection of the pre-liquid. In order to reduce the cost of fracturing fluid, it is recommended to use a 60 °C fracturing fluid system for the sand-carrying fluid, which requires the fracturing fluid to adhere to more than 50 cp. Considering the difference between on-site liquid quality and laboratory experiments, the ratio of pre-liquid tannin glue was initially set at 0.36%, and the ratio of sand-carrying liquid tannin glue was initially set at 0.32% (Fig. 3).

Fig. 3. Temperature simulation curve

The actual ratio of field fracturing fluid was determined based on the on-site test results. Considering that the temperature in spring and autumn and winter is low, the fracturing fluid has a long shelf life. Considering the cost reduction requirement, no stabilizer is added to the fracturing fluid in spring and autumn. Based on the optimization of the above parameters, according to the different conditions of the Stratosphere, the reasonable scale of the safety reconstruction of the fracturing construction, the maximum sand ratio, and the construction time are given through the project risk assessment. The stimplan fracturing geological model was used to determine the sanding scale, construction displacement, construction sand ratio, and pre-liquid ratio. Through the combination of design and on-site construction, P1 well fracturing accumulatively adds 527 m3 of sand, 6720 m3 of construction liquid, 46m3 of acid, and includes 4 m3 of 40–70 mesh ceramsite, slick water 600 m3, fracturing fluid 6120 m3, predicted output about 20.7 t/d.

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4 Tracking Evaluation of Fracturing Effect In the staged fracturing process, different types of indicators are selected for different reservoirs to follow the fluids in and out of the reservoir and carry fluid information [2]. The indicators are classified, purified, analyzed, and processed [3] to obtain relevant information. By analyzing the fluid production of each reservoir, it is possible to evaluate the flowback of each stage. The fluid production profile at the initial stage of production can be evaluated by analyzing the fluid produced during the stationary period of each reservoir. Through the contribution rate of each reservoir, that is, the regular solution of each section of liquid, the engineering problem must be solved. Combine the geological conditions, the contribution rate of the reservoir, and the indicator recovery rate to comprehensively evaluate the effect of fracturing. In order to realize the follow-up evaluation of the fracturing effect, the indicator is introduced into the well and the type, model, amount, and dosing method of the indicator are designed according to the characteristics of the fracturing interval. Analyze the sampled samples to evaluate the effect of fracturing (Table 3). Table 3. Fracture transformation effect of well P1 No.

Perforation

Log

1st 2nd 3rd 4th 5th 6th 7th 8th

22 22 24 24 24 24 24 24

I-2 II-2 I-1 I-2 I-1 I-1 I-2 II-1

Indicator evaluation Recovery Contribution 28 6.4 39.3 8.3 53.2 12.4 57.4 14 61.9 16.1 58.7 16.5 49.2 15.2 33.2 11.1

Indicator minor minor minor major major major major minor

Effect medium medium medium good good good good medium

5 Understanding and Suggestions The field test of well P1 further validates the concept of increasing the contact area between the fracture and the reservoir, and the feasibility of using the design concept of the volume of the sand body and the supporting process in the F oil layer. It is of great significance to the effective utilization of the F layer.

References 1. Dong J, Guo N, Sun B, et al. Application of segmental fracturing technology in horizontal wells in the development of low-permeability oilfields. Petrol Drilling Technol. 2013, 41, pp. 115–9.

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2. Jin ZJ. Application of tracer detection yield evaluation technique and application in horizontal wells. Well Testing, Aug 2015, pp. 15–8. 3. Zhang HJ. Using LWD and tracer techniques to analyze the characteristics of fractured sections in horizontal wells of tight reservoirs. J Yangtze Univ, Nov. 2016, pp. 21–3.

Performance Evaluation and Optimization of Temporary Plugging Agent Used in Diverting Fracturing Haiyang Ma1, Qingzhi Wen2(&), Mingliang Luo1, Tingting Yu1, Gang Lei2, Xiaofei Duan1, and Liu Yang1 1

2

College of Petroleum Engineering, China University of Petroleum (East China), Qingdao 266580, China {978894602,68348424,826206564, 478938178,444864384}@qq.com Beijing Innovation Center for Engineering Science and Advanced Technology, College of Engineering, Peking University, Beijing 100871, China [email protected], [email protected]

Abstract. Temporary plugging and diverting fracturing is an important method for oil and gas reservoirs stimulation, in which the temporary plugging agent (TPA) plays a vital role. The degradability and plugging performance of JRS-1 fiber TPA and QXD-1 granular TPA were evaluated by the self-designed experimental device. Meanwhile, the fiber TPA and the granular TPA were mixed into a new type of composite TPA. The mixing ratio of fiber and granule was further optimized according to the plugging performance. The results show that the fiber and granule both can be degraded more than 95%, the degradation speed meets the construction requirements, and the damage to reservoir is small. Both the fiber and granular TPA can block the simulated fracture. When the fiber and granule in the composite TPA account for 35–45 wt% and 55–65 wt%, respectively, the plugging effect is better than that of the fiber or granule used alone. When the ratio of the fiber and granule is 40 and 60 wt%, respectively, its plugging performance is the best, and the composite temporary plugging layer can stand the pressure up to 7 MPa above. The results can provide reference for improving the diverting fracturing effect.

Copyright 2018, Shaanxi Petroleum Society. This paper was prepared for presentation at the 2018 International Field Exploration and Development Conference in Xi’an, China, September 18–20, 2018. This paper was selected for presentation by the IFEDC Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the IFEDC Committee and are subject to correction by the author(s). The material does not necessarily reflect any position of the IFEDC Committee, its members. Papers presented at the Conference are subject to publication review by Professional Committee of Petroleum Engineering of Shaanxi Petroleum Society. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of Shaanxi Petroleum Society are prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of IFEDC. Contact email: [email protected]. © Springer Nature Singapore Pte Ltd. 2020 J. Lin (ed.), Proceedings of the International Field Exploration and Development Conference 2018, Springer Series in Geomechanics and Geoengineering, https://doi.org/10.1007/978-981-13-7127-1_10

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H. Ma et al. Keywords: Diverting fracturing
Composite temporary plugging agent Performance evaluation
Degradability
Plugging performance




1 Introduction Hydraulic fracturing has become one of the important stimulation techniques for the economic development of unconventional reservoirs [1–3]. Many scholars have suggested that the fracturing method in unconventional reservoirs should take natural fractures into consideration, link original micro-fractures in the reservoir, and increase the stimulated area as much as possible [4, 5]. However, in many cases, due to the influence of in situ stress, conventional fracturing can only produce a single fracture or just expand the original fracture. To solve this problem, temporary plugging and diverting fracturing technology is used to transform the reservoirs by plugging the original fracture with the temporary plugging agent (TPA), which can create new fractures in different directions and increase reconstruction volume [6–9]. As TPA is a key factor for this technology, which has great influence on the construction result, many researchers have focused on the plugging performance evaluation of TPA [10–14]. Cohen et al. carried out the fiber bridging experiments to discuss the effect of fiber cake permeability and spurt loss on the plugging ability of fiber-laden acid fluid system [10]. Droger et al. found that temporary plugging layers could form under two conditions which respectively are bridging with fiber and plugging with fiber [11]. Sau et al. used the fiber TPA to block the 3D-printed cores. Through the experiment, they optimized the injection rate of fiber plugging fluid and the fiber concentration [12]. Wang et al. tested the plugging ability of fiber through the dynamic filtration experiments. The effects of injection rate, fracture width, and horizontal principal stress difference were considered in these experiments [13]. Gomma et al. concluded that far-field steering required small size granules, but nearwellbore and perforation steering both required large size granules [14]. Although many successful experiments and applications have been reported in the literature, most of the reports are limited to fiber TPA or granular TPA used alone. There are few studies on composite TPA with fiber and granule. What’s more, whether the plugging effect of composite TPA is better than that of fiber or granule used alone. And whether there is an optimal proportion of composite TPA to make it the best plugging performance. To solve these questions, the work needs to be done are as follows: (1) to evaluate the degradability of the fiber TPA and granular TPA; (2) to compare the plugging ability of the composite TPA with that of the fiber TPA and granular TPA; (3) to optimize the mixing ratio for the composite TPA.

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2 Methodology 2.1

Experimental Materials and Setups

The experimental materials include the JRS-1 fiber TPA (hereinafter referred to as fiber) and QXD-1 granular TPA (hereinafter referred to as granule), as shown in Fig. 1. The technical specifications of the two TPA materials are summarized in Table 1. The other experimental materials mainly include 40/70 ceramsite, simulated formation water, guar gum, etc.

Fig. 1 The fiber (left) and granule (right)

Table 1 Technical specifications of the TPA materials Technical specifications Appearance Length (mm) Diameter (lm) Density (g cm−3) Dispersibility

JRS-1 fiber TPA white, straight, silk shape 6 40 1.1 Dispersed evenly

QXD-1 granular TPA yellow, translucent, column shape 2–3 4000 1.2 —

The experimental setups include the following: self-designed temporary plugging performance evaluation device (TPPED), as shown in Fig. 2, analytical balance, measuring cylinder, thermostat water bath, beaker, filter paper, and drying oven. It can be seen from Fig. 2 that the apparatus mainly comprises pressurization module, pressure reducing valve module, temporary plugging fluid (TPF) container module, and measuring module (used to measure and record experimental data). The pressurization module is a high-pressure nitrogen cylinder, providing the stable high-pressure gas for the experiment. The pressure reducing valve module can adjust the pressure to the required pressure. The structural diagram of TPF container, used to place the simulated fracture and hold the experimental fluid, is illustrated in Fig. 3.

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Fig. 2 Principle diagram of TPPED. (1 The pressurization module; 2 The pressure reducing valve module; 3 The TPF container module; 4 The measuring module)

Fig. 3 Structural diagram of the TPF container module. (1 The deflated hexagonal connector; 2 The container cup; 3 The TPF; 4 The container seal cap; 5 The simulated fracture or the holes; 6. The O-ring; 7. The compression screw; 8. The outlet 9. The compression bolt)

2.2

Experimental Procedure

2.2.1 Degradation Experiment In order to evaluate the degradability of the TPAs in different temperatures, the constant temperature bath is used to control the experimental temperature. The experimental temperatures are set to 25, 70, 90 °C, respectively. Based on the downhole

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environment, simulated formation water is chosen as the base fluid. The experimental steps are as follows: Use the thermostat water bath to control the experimental temperature at a constant value; add a certain mass of the TPA to the base solution to degrade a period of time; use the filter paper to filtrate the residue of the TPA; fully dry the residue in the drying oven; use the analytical balance to weigh the residue mass; calculate the degradation rate (DR) of TPA in different time periods; the calculation method is shown in Eq. (1); change the experimental temperature or base fluid; and repeat the above steps. DR ¼

M1  M2  100% M1

ð1Þ

where DR is the degradation rate of TPA (%), M1 is the initial mass of TPA (g), M2 is the residue mass of TPA (g). 2.2.2 Temporary Plugging Experiment Firstly, the temporary plugging performance of fiber, granule, and composite TPA with different proportions of fiber and granule will be tested by the self-designed TPPED, respectively, then through the TPPED to test the pressure-bearing capacity of the temporary plugging layers. During the experiment, the simulated fracture width is 1 mm, and the experiment will last for about 30 min. The relevant experimental parameters are listed in Table 2. Table 2 Experimental parameters of plugging experiment Temperature °C

25

Materials

Fiber, ceramsite Granule, ceramsite a Composite TPA (fiber + granule), ceramsite a The proportions of the granule in composite

Fluid

TPF: 0.4% Guar gum fracturing fluid + 1 wt% TPA + 5% ceramsite

Experimental pressure (MPa) 0.4, 0.6, 0.8

TPA are 20, 40, 50, 60, 80%, respectively

In addition, the working process can be summarized as the following: Prepare TPF, and pour TPF to the TPF container; select and install the desired simulation fracture, through the compression bolt and compression screw sealing the TPF container; connect the TPF container to the high-pressure gas source, and check the air tightness; then through the pressure reducing valve adjusting the experimental pressure; record the experimental data according to the measuring module at the same time; decompression and empty the remaining gas; open the TPF container to observe the temporary plugging layer in the simulated fracture; reconnect the device to test the pressure bearing capacity of the temporary plugging layer.

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3 Results 3.1

Degradation Experiment

Degradability is a crucial property for TPA. The degradation speed of TPA can neither be too fast nor too slow. If the degradation speed is too fast, it may cause the TPA to be unable to give full play to the plugging performance. However, if the degradation speed is too slow or even the TPA cannot degrade, the flow conductivity of the original fracture may not be recovered and may cause pollution to the reservoir. The DRs of TPAs at different temperatures are shown in Table 3. From Table 3, we can see that when the experimental temperature is 25 °C, the DRs of fiber and granule after 4 h are all 0%. When the experimental temperature is 70 °C, the DRs are less than 5% after 2 h and less than 10% after 4 h. According to the field experience, after the TPF into the formation, most of the reservoir temperatures will drop to around 60–70 ° C due to the cooling effect of the liquid. This ensures that the plugging performance of TPA is not affected by degradation when actually applied. When the temperature is raised to 90 °C, the DRs of TPAs are more than 50% after 4 h, which have increased obviously. And 24 h later, the fiber and granule can be degraded 98.3 and 95.8%, respectively. After construction, the formation temperature will gradually rise. Some formation even can reach above 100 °C. Therefore, the TPA can degrade rapidly in the high-temperature condition, and the flow conductivity of the original fracture can be recovered. To sum up, the degradability of the fiber and granule used in this paper can meet the requirement of temporary plugging. Table 3 The DRs of TPAs at different temperatures Solution

Temperature °C

Time (h)

Simulated formation water

25

2 4 2 4 2 4 24

70 90

3.2

DRs of TPAs % Fiber Granule 0 0 0 0 4.3 3.5 8.1 5.2 33.5 35.9 56.1 61.1 98.3 95.8

Temporary Plugging Experiment

3.2.1 Fiber Plugging Experiment The relation curves of leakage versus time at different pressures are shown in Fig. 4. As shown in Fig. 4, the leakage curves all show the same trend, the speed of loss is quick at the beginning, then the speed gradually slows down, and finally, the curves tend to be steady. As the leakage increases, fiber will be pressed into the simulated fracture and form a tight temporary plugging layer. With the accumulating of the fiber, the temporary plugging layer will become tighter, and the speed of leakage will become slower

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and slower. And the system finally reaches a balanced state without leakage at each experimental pressure. And the system finally reaches a balanced state without leakage at each experimental pressure, which means that the fracture is blocked successfully. 60

0.4MPa 0.6MPa 0.8MPa

Leakage/ml

50 40 30 20 10 0

0

5

10

15

Time/min

20

25

30

Fig. 4 Leakage of fiber TPF at different pressures

In addition, as shown in Fig. 4, the final fluid leakage of fiber TPF reduces by 44.4% with the pressure increases from 0.4 to 0.6 MPa. When the pressure increases from 0.6 to 0.8 MPa, the final fluid leakage of fiber TPF reduces by 8%. During the whole process, the overall decrement is 49.5%. The main reason is that as the pressure increases, the transient leakage of TPF becomes greater. So the fiber, accumulating in the cracks, is more easily entangled in a short time, an effective plugging layer will be formed quickly, the latter fiber will be easier to be captured, and a benign cycle is formed. Thus, as the pressure increases, the leakage will be reduced. The fiber temporary plugging layer is shown in Fig. 5. 3.2.2 Granule Plugging Experiment The relation curves of leakage versus time with different pressures are shown in Fig. 6. It can be seen from Fig. 6 that all curves have similar rules. At the beginning of the experiment, the loss rate is quick and then gradually slows down. The reason for this phenomenon is that the temporary plugging layer gradually becomes tighter with the time. And as shown in Fig. 6, with the experimental pressure increasing from 0.4 to 0.6 MPa, the fluid leakage of granule TPF is increased by 51.3%. When the pressure increases from 0.6 to 0.8 MPa, the fluid leakage of granule TPF increases by 51.3%, and the overall amount of increase is 76.3% from 0.4 to 0.8 MPa. It should be noted that the experimental rule of granule (seen in Fig. 6) is contrary to that of the fiber (seen in Fig. 4), which can be explained with the different plugging principle of the fiber TPA and the granular TPA. Because of the entanglement

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Fig. 5 Fiber temporary plugging layer in the simulated fracture

50

0.4MPa 0.6MPa 0.8MPa

Leakage/ml

40

30

20

10

0

0

5

10

15

20

25

30

Time/min Fig. 6 Leakage of granule TPF at different pressures

deformation between the fibers which do not have the fluidity, and the squeezing force and friction force generated between the fiber and the fracture coarse surface, the fiber TPA will form a filter cake with a complex network structure. Thus, as the pressure increases in a certain pressure range, the fiber will be compacted in a shorter time and the amount of leakage will be less. However, due to the effect of viscosity and dilatability which is generated by the granule dissolution, the granular TPA will be stuck together to the surface of the crack and proppant. As the pressure increases, due to the own certain mobility of granular TPA and the faster flow rate of TPF, it is more

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difficult to block the stimulated fracture with the dissolved matter of TPA. Thus, in order to form an effective temporary plugging layer, more granular TPF needs to flow through the plugging point of the fracture. 3.2.3 Composite TPA Plugging Experiment The relation curves of leakage with time in different pressures are shown in Fig. 7. It can be seen from Fig. 7 that all the composite TPAs can successfully block the simulated fracture. In the initial stage, the slope of the curve is large, which means that the leakage rate is quick. With the increase in experimental time, the leakage rate gradually slows down and even tends to be 0, which demonstrates that the experimental pressure can be maintained, and an effective temporary plugging layer is formed. Figure 7 also shows that the leakage of the composite TPA with a given proportion increases as the pressure increases. 10

35

(a)

(b)

30

8

Leakage/ml

Leakage/ml

25 6 4 2 0

20 15 10 5

0

5

10

15

20

25

0

30

0

5

10

Time/min 20% Granule 60% Granule

40% Granule 80% Granule

50

15

20

25

30

Time/min 50% Granule

20% Granule 60% Granule

40% Granule 80% Granule

50% Granule

(c)

Leakage/ml

40 30 20 10 0

0

5

10

15

20

25

30

Time/min 20% Granule 60% Granule

40% Granule 80% Granule

50% Granule

Fig. 7 Leakage of different composite TPFs. a at 0.4 MPa; b at 0.6 MPa; c at 0.8 MPa

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The final leakage of the composite TPFs at different pressures is shown in Fig. 8. From Fig. 8 we can see that when the granule proportion is 60%, the leakage of composite TPFs all reaches the bottom of the “funnel,” and the value of leakage is all the minimum in each curve. That illustrates that 60 wt% granule and 40 wt% fiber are the best-mixed mode, which can ensure that the plugging capacity of composite TPA is the strongest among all the composite TPAs. 60

0.4MPa 0.6MPa 0.8MPa

Leakage/ml

50 40 30 20 10 0

0

20

40

60

80

100

Proportion of granule/% Fig. 8 Final leakage of different composite TPFs at different pressures

Figure 9 shows the temporary plugging layer of the composite TPA (60 wt% granule and 40 wt% fiber). As we can see from Fig. 9, the fiber, the granule, and the ceramsite have a clear division of labor, and they successfully block the simulated fracture together. The ceramsite in the TPF corresponds to the existing proppant in the fracture and provides flow resistance for TPF throughout the process. When the TPF flows through the simulated fracture, the fiber will bridge and intertwine with each other between the fracture surfaces and the proppant, forming a complex and interlaced network structure, increasing the movement resistance of the TPF. In addition, due to the dilatability, viscosity, and poor fluidity of the granular TPA, the granular TPA will attach to the surface of the fiber and have a compaction effect on the fiber layer. With the accumulation of the granular TPA, the leakage channel of the fiber layer will be filled gradually and finally forming a composite temporary plugging layer. With the experiment going on, the above processes constantly repeat and cycle, and the composite temporary plugging layer will superpose continuously and enhance the ability to decrease leakage. Finally, an effective tight temporary plugging layer is formed.

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Fig. 9 The composite temporary plugging layer in simulated fracture

3.2.4 Pressure-Bearing Experiment The pressure-bearing experimental results of fiber temporary plugging layer, granular temporary plugging layer, and composite temporary plugging layer (60 wt% granule and 40 wt% fiber) are shown in Table 4. It can be seen from Table 4 that the pressurebearing capacity of the fiber temporary plugging layer is the weakest, the maximum can bear the pressure is 3.7 MPa, the pressure-bearing capacity of granular temporary plugging layer is 4.5 MPa, and the pressure-bearing capacity of the composite temporary plugging layer is stronger than fiber and granular temporary plugging layers which can reach 7.1Mpa. The result means that the composite TPA (60 wt% granule and 40 wt% fiber) has excellent plugging performance and can meet the requirements of the blocking and steering of reservoirs. Table 4 Pressure-bearing experimental results of temporary plugging layers TPA Pressure (MPa)

Fiber TPA 3.7

Granular TPA 4.5

Composite TPA 7.1

4 Conclusions With the study of the experiments in this paper, following conclusions can be drawn: (1) According to the results of degradation experiment, both the JRS-1 fiber TPA and QXD-1 granular TPA have appropriate degradability for temporary plugging technology. At ground temperature, the TPAs will not be degraded. They will be degraded less than 5% at construction temperature after 2 h, which does not affect the using effect. And the TPAs can be degraded more than 95% at high temperature condition to recover the flow conductivity of original fracture. (2) According to the results of temporary plugging experiment: JRS-1 fiber TPA, QXD-1 granular TPA, and composite TPAs can block the stimulated fracture. When the ratio of granular TPA is 55–65 wt%, and the ratio of fiber TPA is 35–45 wt%, the composite TPA has better plugging effect than that of the fiber and

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granular TPA used alone. And the plugging effect of the composite TPA with 60 wt% granule and 40 wt% fiber is the best. (3) According to the results of pressure-bearing experiment, composite temporary plugging layer (60 wt% granule and 40 wt% fiber) can withstand the pressure of 7.1 MPa., it is much higher than the fiber or granular temporary plugging layer. It means that the composite TPA (60 wt% granule and 40 wt% fiber) has excellent plugging performance and can meet the requirements of the blocking and steering of the general reservoir. Acknowledgements. This work is partially funded by the National Natural Science Foundation of China (Grant No. 51674278) and the National Science and Technology Major Project of China (Grant No. 2016ZX05034001-007 and 2017ZX005030005).

References 1. Wang H, Zhang S. Numerical calculation method for hydraulic fracturing design. 1st edn. Petroleum Industry Press, 1998. 2. Economides MJ, Nolte KG. Reservoir stimulation. 3rd edn. Wiley & Sons, Inc, 2003. 3. Li S, Zhang D, Li X. A new approach to the modeling of hydraulic-fracturing treatments in naturally fractured reservoirs. SPE J. 2017;22(4):1064–81. 4. Wen Q, Wang S, Duan X, Li Y, Wang F, Jin X. Experimental investigation of proppant settling in complex hydraulic natural fracture system in shale reservoirs. J Nat Gas Sci Eng. 2016;33:70–80. 5. Harrison AL, Jew AD, Dustin MK, Thomas DL, Joe-Wong CM, Bargar JR, Maher K. Element release and reaction-induced porosity alteration during shale-hydraulic fracturing fluid interactions. Appl Geochem. 2017;82:47–62. 6. Li Y, Yao F, Weng D, Yi X, Yu Y, Jiang X. Progress and prospect of repeated fracturing technology. J Oil Gas Technol. 2005;27(5):789–91. 7. Wang D, Zhou F, Ding W, Ge H, Jia X, Shi Y, Wang X, Yan X. A numerical simulation study of fracture reorientation with a degradable fiber-diverting agent. J Nat Gas Sci Eng. 2015;25:215–25. 8. Leal Jauregui JA, Malik AR, Nunez Garcia W, Solares JR, Bukovac T, Sinosic BV, Gurmen MN. Successful application of novel fiber laden self-diverting acid system during fracturing operations of naturally fractured carbonates in Saudi Arabia. In: SPE Middle East oil and gas show and conference. society of petroleum engineers, Manama, Bahrain, 25–28 January 2011. 9. Shi Y, Zhou F, Yang X, Liu X, Lian S, Li X. Laboratory study and filed application of fiberbased fracture reorientation technology. In: International petroleum technology conference. Beijing, China, 26–28 March 2013. 10. Cohen CE, Tardy PMJ, Lesko TM, Lecerf BH, Pavlova S, Voropaev, SV, Mchaweh A. Understanding diversion with a novel fiber-laden acid system for matrix acidizing of carbonate formations. In: SPE annual technical conference and exhibition. society of petroleum engineers, Florence, Italy, 19–22 Sept 2010. 11. Droger N, Eliseeva K, Todd L, Ellis C, Salih O, Silko N, Fu D, Meyer A, Bermudez R, Degradable fiber pill for lost circulation in fractured reservoir sections. In: IADC/SPE drilling conference and exhibition. society of petroleum engineers, Fort Worth, Texas, USA, 4–6 March 2014.

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12. Sau R, Shuchart C, Clancey B, Lecerf B, Pavlova S. Qualification and optimization of degradable fibers for re-stimulation of carbonate reservoirs. In: International petroleum technology conference. Doha, Qatar, 6–9 Dec 2015. 13. Wang D, Zhou F, Ge H, Shi Y, Yi X, Xiong C, Liu X, Wu Y, Li Y. An experimental study on the mechanism of degradable fiber-assisted diverting fracturing and its influencing factors. J. Nat Gas Sci Eng. 2015;27:260–73. 14. Gomaa AM, Nino-Penaloza A, McCartney E, Mayor J. In: Engineering solid particulate diverter to control fracture complexity: experimental study. In: SPE hydraulic fracturing technology conference. Society of Petroleum Engineers, The Woodlands, Texas, USA, 9–11 Feb 2016.

Investigation on Productivity and Affecting Factors of Low Permeability Reservoir Using Radial Water Jet Drilling Xudong Shen(&), Xinwei Liao, Xiaoliang Zhao, Xiongtao Shang, and Weiyun Luo State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum (Beijing), 18 Fuxue Road, Changping, Beijing 102249, People’s Republic of China [email protected]

Abstract. Radial water jet drilling is one of the most important measures to enhance the productivity of low permeability reservoir by enlarging drainage area and reducing seepage resistivity. Present research on radial water jet drilling are summarized, based on pseudo-three dimension cogitation. Firstly, threedimension seepage field is treated as the superposition of seepage fields on XY plane and Y-Z plane. Then, partial seepage resistivities on X-Y plane and YZ plane are calculated to be seen as the external resistivity and internal resistivity of actual seepage field by means of conformal transformation and principle of potential superposition, and production equation is deduced. Finally, the affecting factors of production equation are analysed. The results indicate that: productivity is mainly influenced by number of branches (per section), branch length, branch radius and number of drilling sections. Number of branches (per section), branch length and number of drilling sections have significant impact on productivity. The investigation has great reference value because the production equation is successfully extrapolated from single section to multi sections. The production equation can provide the guidance for prediction for production wells utilizing radial water jet drilling.

Copyright 2018, Shaanxi Petroleum Society. This paper was prepared for presentation at the 2018 International Field Exploration and Development Conference in Xi’an, China, 18–20 September, 2018. This paper was selected for presentation by the IFEDC Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the IFEDC Committee and are subject to correction by the author(s). The material does not necessarily reflect any position of the IFEDC Committee, its members. Papers presented at the Conference are subject to publication review by Professional Committee of Petroleum Engineering of Shaanxi Petroleum Society. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of Shaanxi Petroleum Society is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of IFEDC. Contact email: [email protected]. © Springer Nature Singapore Pte Ltd. 2020 J. Lin (ed.), Proceedings of the International Field Exploration and Development Conference 2018, Springer Series in Geomechanics and Geoengineering, https://doi.org/10.1007/978-981-13-7127-1_11

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Keywords: Low permeability reservoir
Radial water jet drilling
Conformal transformation
Principle of potential superposition
Analysis of affecting factors Nomenclature

k h Pe Pw re0 l L n m a qi q rwh R0e Re Ri

Reservoir permeability, D Reservoir thickness, m Supply boundary pressure, MPa Bottom hole pressure, MPa Supply boundary radius in W5 plane, m Viscosity, mPa
s Branch length, m Number of branches (per drilling section) Number of drilling sections Point sink interval, m Production rate of i-th point sink, m3/s Production rate of point sink, m3/s Branch radius, m External seepage resistance(per drilling section), MPa (m3/s)−1 External seepage resistance, MPa (m3/s)−1 Internal seepage resistance, MPa (m3/s)−1

1 Introduction In china, low permeability reservoirs account for 2/3 of the proven reserves. Low permeability reservoir is vulnerable, besides, it has the characteristics of low permeability, low abundance, insufficient natural energy. At present, many measures are adopted for the development of low permeability reservoir, such as hydraulic fracturing, ultralong horizontal well and branched horizontal well. These measures can obviously improve the productivities of well groups, however, these measures have the disadvantages of large investment, high technical requirement and great difficulty in construction. In addition, the methods mentioned above mainly focus on principal reservoir, interlayer as well as interior layer contradictions can not be solved and equilibrium displacement can not be realized. Compared with the measures mentioned above, radial water jet drilling has the advantage of low investment, simple process and high economic benefit. Thus radial water jet drilling can make significant influence on the development of low permeability reservoirs. Radial water jet drilling is a kind of technique used to enhance well productions. By means of hydraulic energy, holes in different directions and sections are created so that contact area between drainage area and reservoir can be improved and seepage resistivity can be reduced. Radial water jet drilling was first introduced in the 1980s, Dickinson [1] introduced radial water jet drilling system and its first application. Then, Bruni [2] and Adel M. Salem Ragab [3] introduced its application in Argentina

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and Belayim company in Egypt. Harris [4] and Hong [5] analysed affecting factors of radial water jet drilling by means of numerical simulation. These researchers emphasized the technological process and application of radial water jet drilling but did not pay much attention to its mechanism and production calculation. Compared with researchers mentioned above, researchers in China make vast investigation on technological process and the optimization of parameters. By means of numerical simulation, Liu [6] analysed the affecting factors of radial water jet drilling for the development of low permeability reservoir and optimized its parameters. Based on equilibrium displacement theory, Cui [7, 8] deduced the optimization method for number of branches and branch length. Li [9] investigated hydraulic parameters during drilling process. By means of equivalent well diameter method, Jiao [10] converted branches into vertical wells and deduced production equation for single-section radial water jet drilling. Although the investigations on technological process and optimization of parameters are abundant, up till now, production equation for multi-section radial water jet drilling development is still absent. Referring to the deduction process of production equation for branched horizontal well, firstly, according to the characteristics of actual seepage field, reasonable hypotheses are made. Then, on the basis of pseudo-three dimension cogitation, equations for external seepage resistivity and internal seepage resistivity are established, production equation is deduced by means of conformal transformation and principle of potential superposition. Finally, based on the production equation, affecting factors are analysed and optimized. Results indicate that, this equation is precise and practical. Meanwhile, this investigation can provide guidance for the optimization of multi-section radial water jet drilling parameters.

2 Methodology and Hypothesis for Deduction 2.1

Methodology for Deduction

Based on the pseudo-three dimension cogitation [11, 12], three-dimension seepage field is treated as superposition of seepage fields on X-Y plane and Y-Z plane. On the XY plane, branch is seen as fracture well and its cracked height is equal to the reservoir thickness. By means of conformal transformation, the uniformly distributed branches are transformed to circles with a radius of a unit length. Then, using Darcy’s Law, partial seepage resistivity on X-Y plane (external resistivity) is determined. As for YZ plane, branches are seen as point sinks in certain depth, on the basis of image principle, point sinks in closed reservoir are transformed to infinite well array in infinite reservoir [13]. Then, according to the principle of potential superposition, seepage resistivity on Y-Z plane as well as internal seepage resistivity are determined. Finally, based on the equations of external and internal seepage resistivity, the production equation for multi-section radial water jet drilling is deduced. 2.2

Hypothesis

Due to complicated potential distribution and severe interaction among drilling sections, it’s necessary to make hypotheses to simplify the actual seepage field.

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1. Homogeneous reservoir. 2. Single phase, steady state flow. 3. Each drilling section has the same number of branches, length, distribution, production rate of each branch and angle between two branches are identical. 4. The pressure of fracture wells on X-Y plane after conformal transformation is identical. 5. Because of low permeability, the production of vertical section of well is neglected.

3 Deduction of Production Equation for Multi-sectioned Radial Water Jet Drilling 3.1

Solution of Seepage Resistivity on X-Y Plane

From 3th hypothesis it can be seen that, the distribution of potential in seepage field is symmetric and branches can be investigated individually. By means of conformal transformation, uniformly distributed branches can be transformed to production wells with radius of a unit length. The formula [14] and transformation process are shown in Eq. 1 and Fig. 1.

Fig. 1. Sketch map for transformation process (Jiang [14])

ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ffi
z n2 r
z n W¼2 1 þ 2 1 L L L
z n

ð1Þ

Through the transformations mentioned above, the production equation for single branch on W5 plane can be written as:

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Q¼

2pkhðpe  pw Þ ml ln re0

ð2Þ

Substitute the supply boundary radius re into Eq. 1, the supply boundary radius on W5 plane is as follows: 0

Re ¼ 2


r n e

L

ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ffi
r n2 r
re n e 1 þ 2 1 L L

ð3Þ

Substitute Eq. 3 into Eq. 2, the seepage resistivity on X-Y plane for single branch (R′e) is as follows: 0

Re ¼

ml ln½2

re n L

1 þ 2

re n2 qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi r e n L L 1

2npkh

ð4Þ

According to Eq. 4 as well as water and electricity similitude principle, external seepage resistivity for multi-section radial water jet drilling is shown in Eq. 5:

Re ¼

3.2

1 0 R ¼ m e

h    n qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi r e n i n l ln 2 rLe 1 þ 2 rLe 2 L 1 2npkh

ð5Þ

Solution of Seepage Resistivity on Y-Z Plane

Assuming that m-section and n-branch radial water jet drilling is carried out in the reservoir. Branches which are parallel in the vertical direction are selected for the investigation. On Y-Z plane, these branches are treated as uniformly distributed point sinks in the reservoir, and the production rate for each point sink is per unit length production rate for single branch. The distribution of point sinks on Y-Z plane is shown in Fig. 2. On the basis of image principle, point sinks on Y-Z plane are transformed to infinite well array in infinite reservoir. After the transformation, coordinates for each production well are as follows: ð0; 2nh  aÞ; ð0; 2nh  3aÞ; ð0; 2nh  5aÞ. . .ð0; 2nh  ð2m  1ÞaÞðn ¼ 0; 1; 2. . .Þ According to potential superposition principle, potential for each point in the infinite reservoir is shown in Eq. 6: /¼

m þ1 X qi X lnfY 2 þ ½Z  2nh  ð2i  1Þa2 gfY 2 þ ½Z  2nh þ ð2i þ 1Þa2 g þ C 4p 1 i¼1

ð6Þ

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Fig. 2. Distribution of point sinks on Y-Z plane

According to Bessette equation, Eq. 6 can be simplified as follows: /¼

   m X qi pY p½z  ð2i  1Þa pY p½z þ ð2i  1Þa  cos  cos ln ch ch þC h h h h 4p i¼1 ð7Þ

From 3th and 4th hypotheses it can be seen that, after transformation, potential for each production well of the infinite well array is identical. Set Y equal to 0 and Z equal to a−rwh, based on double angle formula and equivalent infinitesimal theorem, potential for each production well in the seepage field is shown in Eq. 8: " # m 1 Y q m1 prwh 2 ip ln 2 /w ¼ sin þC 2p 2m 2ma i¼1

ð8Þ

Substitute coordinate of point Q(Y, Z) which is far enough from the infinite well array into Eq. 7 to calculate its potential as the potential of the supply boundary. Because Y is sufficiently large, ch pY h ii1, thus, the potential of the supply boundary can be written as: /e ¼ /Q ¼



q pY m ln ch þC 2p 2ma

ð9Þ

Subtract Eq. 8 from Eq. 9, the result is as follows:  pY m ch 2ma q ln /e  /w ¼ Qm1 2 ip wh 2p 2m1 pr i¼1 sin 2m 2ma

ð10Þ

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Based on Eq. 10, the production rate for single well of the infinite well array can be written as Eq. 11: Q¼

2npLkðpe  pw Þ pY m ½ch2ma  l ln m1 prwh Q m1 2 ip 2

2ma

i¼1

sin

ð11Þ

2m

Because Y is sufficiently large, Eq. 11 can be transformed to Eq. 12: 2npLkðpe  pw Þ Q¼ ma Qm1 l pY 2a þ ln 2m2 2

prwh

i¼1



ð12Þ

ip sin2 2m

The second part of the denominator is selected to represent the internal seepage resistivity. According to water and electricity similitude principle, internal seepage resistivity for multi-section radial water jet drilling can be written as Eq. 13: Ri ¼

3.3

l ma ln Q 2 ip 2pmnLk 22m2 prwh m1 i¼1 sin 2m

ð13Þ

Establishment of Production Equation

According to water and electricity similitude principle, production equation for multisection radial water jet drilling is as follows: Qt ¼

p e  pw Re þ Ri

ð14Þ

Substitute Eqs 5, 13 into Eq. 14, the production equation is shown in Eq. 15: Qt ¼

2pkhðpe  pw Þ=l qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi h   n   r n i n re re 2 m h e ln 2 1 þ 2 L L L 1 þ mnL ln mn

22m2 prwh

ma Q

ð15Þ m1 i¼1

ip sin2 2m

For the aim of emphasizing the effect of multi-section radial water jet drilling, production ratio is introduced which is the ratio of production rate of the well applying radial water jet drilling to that of bare well. Production ratio can be written as Eq. 16. PR ¼

lnðre =rw Þ qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi h   i n     n re re 2 re n m mn ln 2 L 1 þ 2 L L 1 þ

h mnL ln 22m2 pr

wh

ma Q

ð16Þ m1

ip sin2 2m i¼1

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4 Analysis of Production Affecting Factors The control variate method is used to investigate the influence of number of drilling sections (m), number of branches (per section) (n), branch length and branch radius on production ratio. Referring to relevant literatures, set supply boundary radius (re) equal to 500 m, set wellbore radius (rw) equal to 6.25 cm and set reservoir thickness (h) to 10 m. After the substitution of data above into Eq. 16, new PR equation is written as Eq. 17: PR ¼ m mn ln

8:987 h   500n2 qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 500n ffii 500 n 2 L 1 þ 2 L 1 þ L

10 mn ln 22m2 pr

ma Q wh

ð17Þ m1

ip sin2 2m i¼1

In addition, according to literatures [6, 15–17], it can be seen that at present, the mode of single section, 2–8 branches, 100 m branch length, 0.02–0.05 m branch radius is mainly adopted for radial water jet drilling. Analysis of affecting factors is carried out on the basis of Eq. 17, the results are shown in the following sections. 4.1

Number of Drilling Sections

Based on Eq. 17, keep the other parameters constant to investigate the influence of number of drilling sections on production ratio, the result is shown in Fig. 3.

Fig. 3. Number of drilling sections-PR curve

As shown in Fig. 3, production ratio rises up as the number of drilling sections increases. This is because the increase of number of drilling sections enlarges drainage area and reduces seepage resistivity. However as the number of drilling sections increases, interactions among drilling sections get severe, as a result, the impact of drilling sections on production is weakened. Consequently, it’s necessary to make proper design for number of drilling sections according to actual reservoir thickness.

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Number of Branches (Per Section)

Based on Eq. 17, keep the other parameters constant to investigate the influence of number of branches (per section) on production ratio, the result is shown in Fig. 4.

Fig. 4. Number of branches (per section)-PR curve

As shown in Fig. 4, when the reservoir thickness is fixed, due to the increase of drainage area and the reduction of seepage resistivity, production ratio rises up as the number of branches (per section) increases. Additionally, as the number of branches (per section) gets larger, especially when the single section has more than 5 branches, its influence on production is weakened. Therefore, for the sake of great economic benefit, each drill section should have no more than 5 branches. 4.3

Branch Length

Based on Eq. 17, keep the other parameters constant to investigate the influence of branch length on production ratio, the result is shown in Fig. 5.

Fig. 5. Branch length-PR curve

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As shown in Fig. 5, production ratio increases rapidly as branch length grows. Branch length has great impact on the production ratio. Therefore, it’s benefit to increase branch length as much as possible within the permitted range of technic during the production. 4.4

Branch Radius

Based on Eq. 17, keep the other parameters constant to investigate the influence of branch radius on production ratio, the result is shown in Fig. 6.

Fig. 6. Branch radius-PR curve

As shown in Fig. 6, branch radius has little impact on the production ratio when branch length is fixed. Consequently, it’s unnecessary to optimize the branch radius during the exploitation adopting radial water jet drilling.

5 Conclusions 1. Radial water jet drilling can remarkably enhance the productivity of production wells and improve the economic benefit of the development of low permeability reservoir. 2. Number of drilling sections, number of branches (per section), branch length have prominent impact on the production of wells applying radial water jet drilling. Branch radius has little influence on the productivity. 3. Number of drilling sections has prominent impact on the production rate, it’s necessary to make proper design for the number of drilling sections according to actual reservoir thickness. 4. Branch length has great impact on the production rate, it’s benefit to increase branch length as much as possible within the permitted range of technic during the production.

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5. The number of branches (per section) has positive correlation with production rate, but as the number of branches (per section) increases, its impact on production rate is weakened. For the sake of great benefit, each drill section should have no more than 5 branches. Acknowledgements. This work was supported by National Science and Technology Major Projects (2017ZX05009004-005) and National Natural Science Foundation of China (U1262101). The authors sincerely thank the colleagues at State Key Laboratory of Petroleum Resources and Prospecting for their support towards investigation.

References 1. Dickinson W, Dickinson RW. Horizontal radial drilling system. SPE california regional meeting, Bakersfield, California, 27–29 Mar, 1985. 2. Bruni M, Biasotti J, Salomone G. Radial drilling in Argentina. In: Latin American & Caribbean petroleum engineering conference, Buenos Aires, Argentina, 15–18 Apri1 2007. 3. Salem R, A.M Kamel. Radial drilling technique for improving well productivity in petrobel— Egypt. In: North Africa technical conference and exhibition, Cairo, Egypt, 15–17 April 2013. 4. Harris MH. The effect of perforating on well productivity. J Petrol Technol. 1966;18(4):518–28. 5. Hong KC. Productivity of perforated completions in formations with or without damage. J Petrol Technol. 1975;27(8):1027–38. 6. Liu Y. The research of increasing production mechanistic of radial direction drilling in low permeability reservoir. Daqing: Northeast Petroleum University; 2012. 7. Cui C, Wang X, Yang Y, et al. Optimization of radial drilling branch number and length in low permeability reservoirs during high water cut period. PGRE. 2014;21(5):61–4. 8. Cui C, Wang X. The optimization of the radial drilling techniques aiming at multi-layer equilibrium displacement in the low permeability reservoir. Sci Technol Eng. 2014;14(28): 200–3. 9. Wang B, Li G, Huang Z. et al. Hydraulics calculations and field application of radial jet drilling. SPE Drilling Completion 2016;31(1):71–81. 10. Jiao H. Parameter optimization and application of radial drilling in low permeability reservoirs. Fault-Block Oil Gas Field. 2017;24(06):855–8. 11. Jiang T. Stable productivity study upon multiple hole horizontal well. SOGR. 2000;7(3):14–7. 12. Cheng L, Li C. The productivity study of branch a horizontal well with multiple branched wells. ACTA. PETROLEI SINICA. 1995;16(2):49–55. 13. Zhao H. The research and application of the radial multiple branching drilling technology in the development of reservoir. Qingdao: China University of Petroleum; 2012. 14. Wang D. A study of determining the optimal position of perforated interval in a vertical well and that of a horizontal well. PED. 1995;22(3):69–71. 15. Shi L, Li Y, Guo H, Wang C, Wang F. Radial horizontal drilling techniques with high pressure water jet. Petrol Drilling Tech 2001;(05):21–2. 16. Yin X. Radial direction drilling in heavy oil reservoir of deep and low permeability. Petrol Geol Eng 2013; 27(05):95–97, 149–150. 17. Tang L, Li X, Xue J. Research and application of radial drilling technology in low permeability sandstone and conglomerate reservoir. Nat Gas Geosci. 2014;25(S1):113–7.

Research and Application of Dual Packer Multistage Control Fracturing Technology in Horizontal Wells Jinyou Wang(&) Production Engineering and Research Institute of Daqing, Daqing, China [email protected]

Abstract. There are some difficulties met in the horizontal well fracturing operation, such as difficult tripping the string smoothly in the well, large probability of sand stuck, high risk of operation and hard control in the field operation. In view of the problems mentioned above, the packing element of inflatable packer, the nozzle structure, phase and quantity of jet pores of pressure transmitting sandblaster were simulated with flow pattern optimization by using the ANSYS finite element analysis results and fluent flow pattern analysis software. The dual packer multistage control fracturing technology in horizontal wells was researched centring on repeated set inflatable packer with small diameter and flushable pressure transmitting sandblaster, which featured on highly targeted stimulation, high efficiency, sand stuck preventing and releasing function. The technological parameters of dual packer multistage control fracturing technology in horizontal wells are listed as follows: the temperature rating is 120 °C, the pressure rating is 80 MPa, the maximum sand loading volume in one trip is 245 m3 and the maximum distance between two adjacent packers is 112 m. Up to 15 stages can be treated in one trip. The technology has been applied to 1978 intervals of 349 wells in Daqing oil field by now, with a success rate of 96.7%. The technology basically meets the fracturing stimulation needs of new and developed horizontal wells with different low permeability reservoir, which provides the strong technical support for exploiting the difficult recovered reserves in Daqing oil field.

Copyright 2018, Shaanxi Petroleum Society. This paper was prepared for presentation at the 2018 International Field Exploration and Development Conference in Xi’an, China, September 18–20, 2018. This paper was selected for presentation by the IFEDC Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the IFEDC Committee and are subject to correction by the author(s). The material does not necessarily reflect any position of the IFEDC Committee, its members. Papers presented at the Conference are subject to publication review by Professional Committee of Petroleum Engineering of Shaanxi Petroleum Society. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of Shaanxi Petroleum Society are prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgement of IFEDC. Contact email: [email protected]. © Springer Nature Singapore Pte Ltd. 2020 J. Lin (ed.), Proceedings of the International Field Exploration and Development Conference 2018, Springer Series in Geomechanics and Geoengineering, https://doi.org/10.1007/978-981-13-7127-1_12

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J. Wang Keywords: Horizontal well Fracturing technology


Dual packer
Multistage control


1 Introduction Daqing periphery oil field is heterogeneous, multilayer sandstone oil field featured with low permeability, low abundance and thin reservoirs. It is commonly believed that horizontal well has larger contact area in the thinner reservoirs compared with the vertical wells. Moreover, fracturing is an effective method to increase conductivity near the wellbore and improve the horizontal wells’ performance. There are some difficulties met in the horizontal well fracturing operation, such as difficult tripping the string smoothly in the well, large probability of sand stuck, high risk of operation and hard control in the field operation because of the special structure of horizontal well and reservoir characteristics. In the 1990s, Daqing oil field and Changqing oil field have carried out the exploratory tests of the Limited Entry Fracturing and the Sand Filling Plug Sectional Fracturing, respectively. In Daqing oil field, the accident of pipe stuck happened when the conventional inflatable dual packers were used to fracture the first horizontal well in the exploratory test in 2006. The fished pipe string through the overhaul workover operation showed that the seriously damaged packers were the main reasons to get the pipe string stuck [1]. The dual packer multistage control fracturing technology in horizontal wells was therefore researched centring on repeated set inflatable packer with small diameter and flushable pressure transmitting sandblaster.

2 String Composition of the Dual Packer Multistage Control Fracturing Technology This pipe string is composed of safety joint, centralizer, hydraulic hold-down button, K344 inflatable packers, pressure transmitting sandblaster, centralizing end plug, etc (see Fig. 1).

Fig. 1. Schematic drawing of multistage control Frac technology with dual-retrievable packers

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3 Inflatable Packer with Small Diameter 3.1

Optimization of Steel Structure in Packer

In order to assure the safety of tripping the pipe string in the downhole, not only the outer diameter of the packer should be minimized, but also the packing element should be not scratched to reduce its residual deformation, which could guarantee the high efficiency and multistage fracturing when pulling up the pipe string. The movable steel structure is designed to reduce the residual deformation of the packing element, which improves the force condition of the packing element and provides the maximum free space for the expansion and contraction of packing element. The multiple fatigue tests for repeatedly setting and releasing the packer showed that the residual deformation of packing element decreased from 17 to 2.7%. It solved the problems of large residual deformation for the packing element, such as the phenomena of distortion and deformation beyond the steel structure happened on the assembly test, which improved the overall pressure of the packer and safety performance of tripping the pipe string. 3.2

Inflatable Packing Element with Small Diameter

The accident of pipe stuck happened when the conventional inflatable dual packers were used to fracture the first horizontal well in Daqing oil field. The traditional nylon cord was transformed into the combination of steel wire and the nylon cord when designing the packing element of the inflatable packer with small diameter. The outer diameter of the packing element was reduced from 113 to 105 mm, so the temperature resistance dropped to 70 °C and pressure rating was only 40 MPa, which could not meet the requirements of fracturing. Therefore, further studies were carried out as follows. First, the rubber element was modified from NBR to HNBR, and adding proper amount of nanoscale additives in HNBR. Second, the combination of steel wire and the nylon cord was upgraded to the combination of steel wire and aramid cord with higher strength. The problem of poor bonding property between aramid and rubber was solved by special treatment technology, so that steel wire, rubber, mucilage and aramid cord can be integrated into one piece with no slices when being vulcanized into the packing element. Moreover, exploratory design and test on the arrangement angle of steel wire and cord were carried out (see Fig. 2). The deformation rate of several different materials in the packing element tends to be consistent, so as to solve the steel wire or cord broken problems when the packing element is under working operation. Third, non-imprint mould and the matching vulcanization process were designed. The original imprint mould being replaced by non-imprint mould brings great difficulty to the vulcanization process. Therefore, the special mould pressing vulcanization process has been studied to solve the problem mentioned above, thus avoiding the cracking of the packing element in the longitudinal imprint line and improving the stability of the parameters of the packing element (see Fig. 3). Fourth, through the analysis of ANSYS finite element method on the stress distribution, the maximum stress position of flexible packing element is on the shoulder of element [2] (see Fig. 4). Shoulder protectors were designed for the packing element of the inflatable packer.

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Fig. 2. Structure layout of steel wire and aramid cord

Fig. 3. Comparison between imprint and non-imprint packing element mould

Through the above improvement, a large amount of oil immersion test for inflatable packing element with small diameter was performed to make the packing element resist the temperature increasing from 70 to 120°C and pressure increasing from 40 to 80 MPa (see Table 1) [3]. The improved inflatable packing element with small diameter basically meets the needs of dual packer multistage control fracturing in horizontal wells of Daqing peripheral Putaohua and Fuyu reservoirs.

4 Pressure Transmitting Sandblaster The function of pressure transmitting sandblaster is integrated with the pressure transmitting, sandblasting and throttle together, which is vital in the fracturing technology. First, the pressure transmitting passage is reasonably designed. The conventional pressure transmitting passage is located on the inner wall of the tool that is easily worn by the sand. Serious wear abrasion can affect pressure conduction. Even the unfiltered fracturing fluid flows into the lower packer, which will lead to the invalid zonal isolation of the lower formation or sand plug for the lower packer to make it

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Fig. 4. Stress analysis diagram of inflatable packer Table 1. Oil immersion test for inflatable packing element with small diameter Oil immersion temperature (°C) 120 120

Oil immersion time (h) 4 16

Fatigue test OD before (MPa  min  times) oil immersion (mm) 80  5  5 105 80  5  10 105

Max. OD after Maximum oil immersion distortion (%) (mm) 107.8 108.1

2.67 2.95

difficult to release. Therefore, the structure design of the outer wall is optimized to enhance the sand loading volume and reliability. Second, the nozzle structure of sandblaster is optimized. The conventional nozzle shape of pressure transmitting sandblaster is long slot type. When the sand loading volume reaches 45 m3, severe wear abrasion problem will happen. The flow pattern simulation analysis with the software of Fluent was applied on the nozzle with long slot type and multi-pore type individually. Meanwhile, the material of carbide liner is optimized. The results show that the flow pattern in the multi-pore type is much better than that in the long slot type. The sand carrier can flow through the pores evenly and avoids the serious wear abrasion phenomenon in some parts of the tool. Third, the outlet angle of jet nozzle is optimized and the diagram of the relationship between operation displacement and throttle differential pressure is set up to provide theoretical basis for the selection of nozzle with reasonable size (see Fig. 5). The diagram shows that the differential

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pressure of the nozzle is gradually increased with the decrease in the nozzle diameter under certain operation displacement, and the increasing trend is rather obvious. So the diameter of the nozzle has a great influence on the differential pressure. Pressure loss curve of the original structure is located between D = 23 mm and D = 25 mm of the optimized structure [4]. All the improvement and innovation, such as the pressure transmitting passage, the outlet angle of jet nozzle, the optimization of nozzle structure, the material selection of

Fig. 5. The diagram of the relationship between operation displacement and throttle differential pressure

Fig. 6. Performance comparison chart before and after the improvement on the pressure transmitting sandblaster

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liner and the diagram of the relationship between operation displacement and throttle differential pressure, make the sand loading volume increase from 45 to 160 m3. The pressure transmitting sandblaster is only slightly worn (see Fig. 6), and it can still normally work even when the maximum sand loading volume being increased up to 245 m3.

5 Sand Stuck Preventing, Sand Stuck Releasing Technique For the Frac service, it is no denying that safe Frac operation is the most important thing. The dual packer multistage control fracturing technology is supposed to have functions of the sand stuck preventing, sand stuck releasing which can effectively reduce the risk of operation in the field. For the sand stuck preventing measure, the tools are designed as small diameter and short length. It has a low profile for greater running clearance to help reduce problems that may occur when running in horizontal wells. After fracturing the specific interval, reverse sand flushing can help clean the sand deposit between two adjacent packers to prevent the pipe string stuck when pulling up the string. For the sand stuck releasing measure, stage the steel ball from the well head to depart the safety joint from the other tools. The tubing above the safety joint can be picked up from the wellbore. There is a standard inner passage with 62 mm diameter for the fishing tools to mill or drill the stuck string.

6 Anchoring and Conductively Centralizing Technique It is necessary to have the anchoring and conductively centralizing technique through the mechanical calculation of the pipe string in horizontal well (see Fig. 7) and the analysis of the flow pattern. They can prevent the string from moving upward or downward during the fracturing operation; flush the sand deposit by the reverse circulation; improve the sealing performance of packers; and provide the technical support for the multistage fracturing with long distance between two adjacent packers.

Fig. 7. Displacement contrast of lower packer under different pressure and different stuck distance between adjacent packers

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7 Double-Channel Manometer Monitoring Technique The manometer consists of four parts: sensor, memory, power supply and ground replay equipment. Among them, the first three parts are made up of downhole instruments. The electronic memory stores the data, and then, the sensor transmits the pressure/temperature induction frequency. Before the fracturing operation, the storage temperature manometer is placed inside the manometer protecting carrier (see Fig. 8). Then, the manometer is run into the downhole with the fracturing pipe string to the measured depth and pulled out from the wellbore after fracturing operation, which likes an “electronic eye” to fully record the change of tubing and casing pressure during the fracturing operation. The recorded data in real time can judge the sealing performance of packers. In the fracturing operation, if the casing pressure of the lower manometer changes with the casing pressure of the upper manometer, it is proved that there are interlayer channelling problems or the packer is not sealed. On the contrary, if the casing pressure of the lower manometer does not change with the casing pressure of the upper manometer, it is proved that the packer is under the sealing performance [5]. When replaying the test data, the manometer is connected with the computer. The software converts test data into time, pressure and temperature files and then converts the data into a form or other curve formats (see Fig. 9).

Fig. 8. Structure schematic drawing of manometer

Fig. 9. Monitoring curve of downhole electronic manometer

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8 Field Application and Effect The dual packer multistage control fracturing technology in horizontal wells has been applied to 2004 intervals of 356 wells in the domestic oil fields of China by the end of 2015, among which 1978 intervals of 349 wells in Daqing oil field. Field applications ensure that it has become a mature technology and enjoys a technical success rate up to 96.7%. Taking Well ZF51-P   as an example, at most to 15 stage fracturing could be executed in one trip [6] (see Fig. 10). The maximum working pressure was 60.2 MPa; the circulation rate during operation was 3.4 m3/min; and the total sand loading volume was 110 m3. Packers were set 32 times of 15 stage fracturing (including test fracturing), and the effective operation time was only 34 h. At the early stage after fracturing, the average daily oil production of individual well was 9.7 t, which was 5.5 times higher than that in vertical wells after using the dual packer multistage control fracturing technology according to the statistics of 174 horizontal wells. The technology has also been applied in Yumen, Changqing, Qinghai and other oil fields.

Fig. 10. Frac operation curve in well ZF51-P  

9 Conclusion (1) The dual packer multistage control fracturing technology in horizontal wells successfully executes a wide range of horizontal well Frac service, which basically meets the fracturing stimulation needs of new and developed horizontal wells with different low permeability reservoir and provides the strong technical support for exploiting the difficult recovered reserves in Daqing oil field. (2) The technology features highly targeted stimulation, high efficiency, sand stuck preventing and releasing function, which has become the dominant fracturing and completion technology in the field of horizontal well fracturing. (3) It is suggested that the serialization of tools and the improvement of technical parameters should be carried out so that the technology can be applied in the field of clustered-type large-scale fracturing in horizontal wells.

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References 1. Wang F, Zhang S, Wang W, et al. New development of fracturing technology for low permeability horizontal wells in Daqing Oilfield. Petrol Geol Oilfield Dev Daqing, 2009;28 (5):234–38. 2. Lian Z. Finite element simulation analysis on setting process of packer. China Petrol Mach 2007;35(9):19–21. 3. Wang J, et al. Experiment system for high temperature and high pressure oil immersion test, Oil-Gasfield Surf Eng 2006;25(12):29. 4. Wuqi, LZ. Horizontal well sectional frac technique with dual-retrievable packers. Beijing: Petroleum industry press; 2013:53–3. 5. Zhang Y, Xu G, Wang J, et al. Application of double—channel storage electronic manometer in horizontal well fracturing. Oil Prod Eng 2011;1(2):64–8. 6. Zhang C, Li L, Liu Z, et al. Application of horizontal well sectional fracturing technology in Well Fu 51—Ping 52 in Daqing Oilfield. Oil Prod Eng 2012;2(1):28–31.

Discussion on the Technical Countermeasures of Hechuan Xujiahe Gas Reservoir Development Qinglong Xu(&), Yongzhuo Wang, Xuemin Zhou, and Ping Shu Research Institute of Exploration and Development of Daqing Oilfield Company Ltd., Daqing, China {xuqinglong,wangyongzhuo,zhouxuemin,shup} @petrochina.com.cn

Abstract. The Xu-2 member of the Xujiahe gas reservoir in Hechuan gas field has a typical characteristic which is low porosity and low permeability. It is a condensate reservoir which has low dew point pressure and microcondensate oil. The development plan made in 2009, 2010, and 2011 was the key construction production phase. So far, the gas reservoir did not reach a stable life and production of scheme design. It was in the stage of production decline. The single well in the gas reservoir was affected by low porosity and tight reservoir that has a performance of low productivity. And it has a poor economic benefit by producing oil and water. Its corresponding development countermeasure should be explicit. So, getting geological reinterprets and carrying out gas well productivity analysis and development countermeasure research have great significance in Xu-2 gas reservoir. In this paper, we take Hechuan 1 area in Hechuan gas field as the research object. We use 3D seismic data processing and interpretation to clear the gas reservoir structure, entrapment, and fault. Well seismic combination was applied for sedimentary facies to clear the relationship between favorable sedimentary microfacies and effective reservoir, to realize phased reservoir prediction, and to clear development area of effective reservoir. Then, we established gas layer identification standard of logging and ensure reserves parameters again, calculated proven geological reserves, and confirmed development potential and present corresponding development countermeasures aiming at residual gas reservoir development potential [1–3]. Copyright 2018, Shaanxi Petroleum Society. This paper was prepared for presentation at the 2018 International Field Exploration and Development Conference in Xi’an, China, September 18–20, 2018. This paper was selected for presentation by the IFEDC Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the IFEDC Committee and are subject to correction by the author(s). The material does not necessarily reflect any position of the IFEDC Committee, its members. Papers presented at the Conference are subject to publication review by Professional Committee of Petroleum Engineering of Shaanxi Petroleum Society. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of Shaanxi Petroleum Society are prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of IFEDC. Contact email: [email protected]. © Springer Nature Singapore Pte Ltd. 2020 J. Lin (ed.), Proceedings of the International Field Exploration and Development Conference 2018, Springer Series in Geomechanics and Geoengineering, https://doi.org/10.1007/978-981-13-7127-1_13

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Q. Xu et al. Keywords: Xujiahe gas reservoir technical countermeasures




Low porosity and tight




Development

1 Introduction The Hechuan gas field which crosses the Hechuan District of Chongqing and Wusheng County of Sichuan is located in the central part of the Sichuan basin. Jialing River passes through the southwest part of the gas reservoir. The regional structural position is located in the eastern part of the gentle uplift of the central part of Sichuan. The main development layer is the Xu-2 member tight sandstone reservoir. The Hechuan1 well area is the major production area. In 2009, a preliminary development program was developed. In 2011, the maximum production (2 million 400 thousand cubic meters per day) which was only 72.3% of the output in plan was reached. At present, 259 wells have been put into operation in the well area, 110 wells have been opened, and the output is only 230 million in 2017. The characteristics of the gas field are low production of single well, high water saturation of reservoir, and no stable production period of gas wells. These problems lead to high proportion of low-efficiency wells, common groundwater in gas wells, and rapid production decline. Moreover, three phases of oil, gas, and water produce simultaneously, resulting in poor economic benefits of gas fields. In summary, it is of great significance to further understand the geological needs of the Xu-2 gas reservoir, analyze the productivity of the gas well, and develop the countermeasures.

2 Geological Characteristics of the Xu-2 Gas Reservoir in Hechuan Gas Field 2.1

Characteristics of Geological Structure

The top surface of this gas field is a slow and latent structure with undeveloped faults, whose main structural trap line is −1840 m, and the closure height is 90 m, based on 2D seismic interpretation. The latest 3D seismic data collected in 2015 and reevaluated recently show that there are many faults in the Xu-2 reservoir, making the structures more complex. Therefore, the structural characteristics need to be further studied. According to drilling indication, core observation, and imaging logging analysis, the fractures are mainly located in the high position of Jieziba structure. According to the preliminary analysis of seismic profiles, it is believed that this may be due to some faults breaking to Xu-1 reservoir which contains source rocks, providing an upward migration channel for gas and forming high-quality gas reservoirs at the high point of Xu-2 reservoir [4–6].

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2.2

131

Characteristics of Stratigraphic Sequence

The Xujiahe formation whose overlying strata is Jurassic terrestrial strata and underlying strata is marine facies strata of Triassic Leikoupo formation has a normal stratigraphic sequence. The Xujiahe formation divided into six segments from bottom to top is a set of inland terrigenous clastic rocks. The thickness of Xu-2 formation is from 76.5 to 139.5 m, and the average middle depth is 2200 m. 2.3

Characteristics of Reservoir

Based on the existing results, Xu-2 formation should be divided from bottom to top into Xu-21, Xu-22, and Xu-23. The reservoir of Xu-2 formation has many layers and thin thickness, the largest thickness is 16 m, the average thickness is 2.71 m, and the accumulated thickness is generally larger than 11.63 m. Vertically, the reservoir is mainly distributed in the middle and upper parts. Horizontally, the main reservoir segments are traceable and relatively distributed. The underwater distributary channel and estuary dam microfacies of Xu-2 formation are the most favorable sedimentary microfacies for reservoir development, and their distribution area is reservoir development area. According to the description of exploratory wells and 2D seismic results, it is considered that the thickness of Xu-2 sandstone is thickened from southeast to northwest and the thickness of single well sandstone is 60–135 m. On the plane, the sand body is gradually thinning toward the northwest (Figs. 1 and 2).

Graphic symbol Proved reserve block

micro gas well

Boundary of subfacies

line of sand body thickness（m）

Water well

trying gas well

Fig. 1. Sedimentary facies map of Xu-2 reservoir

Gas well

Low producƟon gas well

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Graphic symbol Proved reserve block

micro gas well

Boundary of subfacies

line of sand body thickness（m）

Water well

trying gas well

Gas well

Low producƟon gas well

Fig. 2. Sandstone thickness map of Xu-2 reservoir

The Xu-2 reservoir rocks are mainly feldspar lithic sandstone and lithic feldspar sandstone. The grain size of the rock is mainly medium grain, followed by medium– fine grains and fine grains, and the separation is medium to good. The grinding circle is sub-rounded to sub-circle, and most of them are pore type cementation. The main pore types are residual intergranular pores, intergranular dissolved pores, and intragranular dissolved pores. The main types of reservoir throat are lamellar throat and tubular larynx, with large displacement pressure, large middle pressure, and small median radius of pore throat. These are characteristics of low porosity and low permeability sandstone reservoirs. The porosity of the reservoir is mainly distributed between 6 and 12%, with an average of 8.36%, and the permeability of the reservoir is mainly distributed between 0.02– and 0.64 mD, with an average of 0.31 mD. From the relation of core porosity and permeability, there is a positive correlation distribution, but the permeability of some samples at the same porosity is very large, which indicates the effect of pore structure and crack. The lower limit of porosity is 6% (Fig. 3). The water saturation of reservoir cores is mainly in the range of 60–90%, accounting for 91.05% of the total samples. The average water saturation of logging reservoir is 38.3%, which is quite different from that of core. The upper limit of water saturation is determined to be 54% by semipermeable baffle air–water capillary pressure method and productivity simulation and relative permeability curve method. Because there is no oil-based closed coring data in the area, preliminary analysis shows that water-based mud affects the measurement of water saturation and makes it higher. We plan to collect oil-based coring data during drilling in the future, combined with conventional logging and NMR logging data, to comprehensively evaluate the water saturation of reservoirs in this area.

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Fig. 3. Relationship diagram of core porosity and permeability

2.4

Stratigraphic Pressure and Temperature Characteristics

The formation pressure of Xu-2 formation is between 29.16 and 32.02 MPa, and the pressure coefficient is between 1.3 and 1.4, which is a gas reservoir with high-pressure coefficient. The gas reservoir temperature is between 75 and 77 °C, and the geothermal increasing temperature is 41.5 m/°C, which is the normal temperature gradient. 2.5

Fluid Properties

The gas of Xu-2 formation mainly composed of methane which is between 88.03 and 93.29% with very low acidic component, and no H2S is the high-quality gas. The Hechuan gas field is a condensate gas system. The critical condensate pressure is 15.296 MPa, and the critical condensate temperature is 110 °C, which indicates that the fluid is a single gas phase under the formation condition. The average condensate content of Xu-2 gas reservoir in Hechuan which belongs to microcondensate reservoir is 28.78 cm3/m3. The water type of Xu-2 gas reservoir in Hechuan is CaCl2, and the salinity is between 167.1 and 218.55 g/l. 2.6

Distribution of Gas and Water

It was believed that the distribution of gas and water was not completely controlled by the structure. In general, the gas was in the upper part, and the water was in the lower part. The high part of the structure and the upper end of the sand body were enriched with natural gas. The aquifers were mainly located in the subsection of the Xu-21 reservoir. The gas reservoir is mainly the lithologic gas reservoir on the basis of the structure. However, according to our preliminary analysis, it is believed that the area of gas well below the tectonic trap line may be an independent fault block with gas cutting, and the height of the actual gas column is greater than the tectonic range, that means the structural trap still needs to be further implemented [7, 8] (Fig. 4).

Fig. 4. Section of connected wells in reservoir

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3 The Dynamic Characteristics of the Xu-2 Member of Xujiahe Gas Reservoir 3.1

Main Controlling Factor of High Production Is Fracture

The gas field own 37 wells which have a cumulative production above 30 million cubic meters, and the number of wells is 16.3% of the total number of production wells. Their total cumulative production is 2.517 billion cubic meters, which is 55.8% of whole cumulative production. Four wells of them had drilled xu32 layer of the Xujiahe gas reservoir founded large-scale fractures when open hole testing. Three wells of them have a cumulative production above 100 million cubic meters. Main production layer of 19 wells is xu32 layer among high production wells, and the number of wells is 51.3%. The reservoir also developed 27 wells which are rich for fractures, and the number of wells is 90%. Main production layer of 4 wells is xu22 layer of Xujiahe gas reservoir, and the number of wells is 10.8%. According to analysis of the dynamic characteristics of single well, we preliminary think that the fractures are the main control factor. About 90% high effective wells developed fractures in xu32 layer of Xujiahe gas reservoir. 3.2

Gas Wells Usually Produce Water

Gas wells usually produce water during testing. There are 182 wells produced water, 51% of the total number of wells, and the water production of well was different widely. There are 294 testing wells, of which the average production of water is 11.5 m3/d, and the highest production of water is 108 m3/d. Producing water causes significant influence on gas well producing. 3.3

Low Permeability and Strong Heterogeneity

Finite diversion interpretation model and half-length of fracture reflect that fracturing has an obvious effect on improving seepage capacity of reservoir; explaining average permeability is (0.03–0.3)  10−3 lm2, reflecting that the reservoir has strong heterogeneity. The permeability of reservoir is low. It reflects that the reservoir has strong heterogeneity according to the log–log curve of A3 well become warped on continued and log–log curve of A103 well concave upward (Figs. 5 and 6). 3.4

Large Difference of Dynamic and Static Reserves

The well control dynamic reserves of Hechuan gas field are 7.12 billion cubic meters calculated by well group, compared with the proven reserves of 100 billion cubic meter and the use of geological reserves of 60 billion cubic meters, the differences are so obvious, and single well control reserves is usually small. This is closely related to the high water saturation and density of reservoir. The dynamic reserve of the average single well is 0.29 billion cubic meters [9–12].

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Fig. 5. Log–log curve of pressure recovery analysis figure of A3 well

Fig. 6. Log–log curve of pressure recovery analysis figure of A103 well

4 Technical Countermeasures for Development (1) Due to the precision of existing structure based on 2D seismic data cannot meet the requirements of fine development deployment and the 3D seismic data (2015) collected in the east of Gaoshi 16 well is aimed at the deep layer, in view of the problems of low interpretation accuracy of Xujiahe formation, the lack of fault interpretation and the poor reliability of the structure, the unified 3D seismic data

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(3)

(4)

(5)

(6)

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processing, fine interpretation, structural distribution features, and reservoir fine prediction are put forward for Xujiahe formation. The existing seismic data are mainly old 2D, and the existing 3D seismic data cannot completely cover the whole research block in Hechuan, which is not conducive to the overall study of this gas field; therefore, it is urgent to put forward the acquisition work of 3D seismic data which cover all areas of proven reserves submitted. In view of the characteristics of low porosity and permeability, contradiction between logging and core water saturation, and complex distribution of gas and water in Hechuan gas field, reservoir logging evaluation is redeveloped to make full use of all well data in the area in order to meet the needs of current development. Besides, the interpretation standard of gas–water reservoir logging and the reservoir interpretation model of pore, permeability, and saturation are reestablished, and the reservoir movable water saturation is evaluated with conventional logging and nuclear magnetic resonance logging data. On the basis of gas–water identification of reservoir, pore permeability model, and dynamic data, the evaluation standards of reservoir classification logging are established. The reservoir in Hechuan gas field is composed of several layers vertically with the thin single layer thickness of 2.71 m on average and Xu-2 member is divided into three subsections, which cannot satisfy the prediction of the distribution scale of thin reservoir. In order to enhance the macroscopic understanding of reservoir distribution, the fine division and reservoir correlation study of three submembers in the Xu-2 member should be carried out with the help of the combination of well and seism. The study on sedimentary facies description and sand distribution characteristics of three submembers in the Xu-2 member is carried out to provide support for reservoir prediction and reservoir classification evaluation. On the basis of fine division of substrata and description of distribution characteristics of sand bodies, the reserves of each submember are recounted. The gas well productivity difference in Hechuan gas field is great, so it is necessary to study the productivity evaluation technology of low permeability sandstone in gas reservoir and to carry out the research on research on reasonable production allocation of gas wells. After determining the reasonable production rate of gas well, the research on productivity evaluation of gas well should be carried out, influence of water production and condensate production on gas well productivity is clarified, and the main control factors of gas well productivity by dynamic and static combination are determined. Besides, the relationship between single well production and open-flow capacity are analyzed to give the reasonable production range of single well, the classification standard of the gas well in production and the early warning mechanism is established in combination with productivity calibration to determine the reasonable dynamic production rate of gas wells [13–17]. The development effect of Hechuan gas field is poor, and the reserves producing degree is low. It is necessary to strengthen the recognition of gas field geology and determine the development potential by combining dynamic and static data. The

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development idea of “the fracture development zone and large-scale fracturing and low pressure differential production” is put forward. Reasonable deployment of horizontal well, vertical well and inclined well reduces the waste of reserves, mixed well pattern of cluster type well group and horizontal well development..

5 Conclusion (1) In view of the characteristics of low porosity and permeability, contradiction between logging and core water saturation, and complex distribution of gas and water in Hechuan gas field, reservoir logging evaluation is redeveloped. Besides, the interpretation standard of gas–water reservoir logging and the reservoir interpretation model of pore, permeability, saturation are reestablished, and the reservoir movable water saturation is evaluated with conventional logging and nuclear magnetic resonance logging data. On the basis of gas–water identification of reservoir, pore permeability model, and dynamic data, the evaluation standards of reservoir classification logging are established. (2) The reservoir in Hechuan gas field is composed of several layers vertically with the thin single layer thickness. In order to enhance the macroscopic understanding of reservoir distribution, the fine division and reservoir correlation study of three submembers in the Xu-2 member should be carried out with the help of the combination of well and seism. The study on sedimentary facies description and sand distribution characteristics of three submembers in the Xu-2 member is carried out to provide support for reservoir prediction and reservoir classification evaluation. (3) The gas well productivity difference in Hechuan gas field is great, so it is necessary to study the productivity evaluation technology of low permeability sandstone in gas reservoir and to carry out the research on reasonable production allocation of gas wells. After determining the reasonable production rate of gas well, the research on productivity evaluation of gas well should be carried out, influence of water production and condensate production on gas well productivity is clarified, and the main control factors of gas well productivity by dynamic and static combination are determined. Besides, the relationship between single well production and open flow capacity is analyzed to give the reasonable production range of single well, and the classification standard of the gas well in production and the early warning mechanism is established in combination with productivity calibration to determine the reasonable dynamic production rate of gas wells. (4) The development effect of Hechuan gas field is poor, and the reserves producing degree is low. It is necessary to strengthen the recognition of gas field geology and determine the development potential by combining dynamic and static data. The development idea of “the fracture control of reservoir permeable sand body and small-scale acidification and low pressure differential production” is put forward.

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References 1. 2. 3. 4. 5. 6. 7. 8.

9. 10. 11. 12.

13. 14.

15. 16.

17.

Luo Z, Wang Y. Pore structure of oil and gas reservoir. Beijing: Science Press; 1986. Qiu Yinan, Chen Ziqi. Reservoir description. Beijing: Petroleum Industry Press; 1996. Tang Zeyao. Gas field development geology. Beijing: Petroleum Industry Press; 1997. Luca C. Study on integration of reservoir evaluation. Beijing: Petroleum Industry Press, 2003. Chen J, et al. Study on reservoir characteristics of Xuer gas reservoir in Hechuan 129 well area of Hechuan fas field. Southwest Petroleum University, 2010. Zhu R, Zhao X, Liu L, et al. Depositional system and favorable reservoir distribution of Xujiahe formation in Sichuan Basin. Petrol Explor Dev 2009;36(1):46–55. Zou C, et al. Formation and distribution of shallow-water deltas and central-basin sandbodies in large open depression lake basins. Acta Geologica Sinica, 2008;82(6):813–25. Zhao W, Wang H, Xu C, et al. Reservoir-forming mechanism and enrichment conditions of the extensive Xujiahe formation gas reservoirs, central Sichuan Basin. Petrol Explor Dev 2010;37(2):146–57. Qiu Yinan. Developments in reservoir sedimentology of continental clastic rocks in China. Acta Sedimentol Sin. 1922;10(3):16–24. Feng Z, Wang Y, Liu H, et al. Chinese Sedimentology. Beijing: Petroleum Industry Press, 1994. Gang Q, Dan G, Ruijie X, Juan G. Accurate geological study on fluvial facies reservior in sulige gas-field area. Xinjiang Oil Gas. 2009;5(4):17–20. Hou F, Jiang Y, Fang S, et al. Sedimentary model of sandstone in second and fourth members of Xiangxi formation in the upper triassic of Sichuan basin. Acta Petrolei Sinica, 2005;26(3):30–7. Sun Z. Comprehensive study and evaluation to behavioral characteristics of difficult-to-produce reserves of Luodai Gas Fieldp. Master thesis of Chengdu University of Technology, 2005, 5. Ye L. Study on percolation mechanism and reservoir evaluation of Xujiahe low permeability sandstone gas reservoirs in central Sichuan Basin. Doctoral dissertation, Graduate School, Chinese Academy of Sciences, 2011, 6. Tian W. Study on the oil-gas-water multi-phase seepage law for tight sandstone condensate gas reservoir. Doctoral Thesis of Beijing University of Science and Technology, 2015, 6. Hongxu Z. The new method for analyzing the production performance of condensate gas wells by using the characteristic curve of unstable well testing. J Yangtze Univ (Natural Science Edition). 2017;14(11):58–63. Tian W, Wang M, Zhu Y, et al. Study on the oil-gas-water three-phase seepage law for tight sandstone. J Shaanxi Univ Sci Technol (Natural Science Edition). 2016;10(5):114–8.

Study on Areal Sweep Coefficient Under Water Flooding in Ultra-Low Permeability Reservoirs He Congge(&), Xu Anzhu, Zhao Lun, and Fan Zifei Research Institute of Petroleum Exploration and Development, PetroChina, Beijing, China [email protected]

Abstract. The objective of this paper is to set up a method to estimate the areal sweep coefficient in view of those characteristics of ultra-low permeability reservoirs in the process of water flooding. The permeability anisotropic reservoirs are firstly equivalent to permeability isotropic reservoirs by coordinate transformation. On this basis, the streamline distribution of five-spot well pattern is derived through solving the stream function equation. Moreover, the areal sweep coefficient formula is derived by streamline integral method with the consideration of the characteristics of non-Darcy flow and non-piston displacement under water flooding in ultra-low permeability reservoirs. Influential factors on areal sweep coefficient are analyzed in detail. Taking an ultra-low permeability reservoir in Ordos basin as an example, the water flooding performance is evaluated and corresponding measures for its adjustment are also proposed. The study shows that when the mobility ratio of oil phase to water phase becomes small and the threshold pressure gradient increases, the width of water sweep zone and the speed of water flooding front reduce, and therefore the areal sweep coefficient decreases at breakthrough time. The areal sweep coefficient and the water flooding effect can be effectively improved by the adjustment of well spacing, injection and production parameters, and well pattern infilling. The uniform displacement can be established when the ratio of well spacing to row spacing equals the square root of the permeability anisotropy degree.

Copyright 2018, Shaanxi Petroleum Society. This paper was prepared for presentation at the 2018 International Field Exploration and Development Conference in Xi’an, China, 18–20 September, 2018. This paper was selected for presentation by the IFEDC Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the IFEDC Committee and are subject to correction by the author(s). The material does not necessarily reflect any position of the IFEDC Committee, its members. Papers presented at the Conference are subject to publication review by Professional Committee of Petroleum Engineering of Shaanxi Petroleum Society. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of Shaanxi Petroleum Society is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of IFEDC. Contact email: [email protected]. © Springer Nature Singapore Pte Ltd. 2020 J. Lin (ed.), Proceedings of the International Field Exploration and Development Conference 2018, Springer Series in Geomechanics and Geoengineering, https://doi.org/10.1007/978-981-13-7127-1_14

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Keywords: Non-piston displacement
Ultra-low permeability reservoir
NonDarcy flow
Water breakthrough time
Five-spot well pattern non-piston displacement Nomenclature

v q L xf k kx ky kro krw lw lo lr Pi Pw k f’w(Swf) u t rw C1, C2 a0 s1 s2 s0 s0 η

Velocity, m/s Flow rate, m3/s The length of streamline, m The front of water, m Permeability, 10−3 lm2 Permeability in x direction, 10−3 lm2 Permeability in y direction, 10−3 lm2 Relative permeability of oil phase, dimensionless Relative permeability of water phase, dimensionless Viscosity of water phase, mPa s Viscosity of oil phase, mPa s Viscosity ratio of oil phase and water phase, dimensionless Injection pressure, MPa Production pressure, MPa The threshold pressure gradient, MPa/m Water cut increasing rate, dimensionless Porosity, dimensionless Time, d Radius of wellbore, m Constant, dimensionless The starting angle The swept areal of unit DABC, m2 The swept areal of unit DADC, m2 The areal of unit DABC, m2 The areal of unitDABC, m2 The areal sweep coefficient, dimensionless

1 Introduction In recent years, more and more ultra-low permeability reservoirs in the Ordos Basin have been put into development, and most of them have been developed by water flooding [1]. The areal sweep efficiency is one of the important indexes for evaluating the development effect of water flooding. Therefore, it is necessary to accurately calculate the areal sweep efficiency under water flooding in ultra-low permeability reservoirs. A large number of physics experiments have shown that the fluid has a threshold pressure gradient when flowing in ultra-low permeability reservoirs. The flow law no

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longer meets Darcy’s law, showing non-Darcy flow characteristics [2–6]. At the same time, natural fractures are usually developed in ultra-low permeability reservoirs, which make the reservoirs have the anisotropic characteristics of permeability. Injected water preferentially protrudes in the direction of high permeability in the water injection process [7–10]. Moreover, in the process of water flooding in ultra-low permeability reservoirs, the difference in viscosity of oil and water has a great influence on the areal sweep coefficient of water flooding [11]. Therefore, it is necessary to consider the influence of non-Darcy flow characteristics, permeability anisotropy characteristics and oil-water viscosity difference when calculating the areal sweep coefficient of ultra-low permeability reservoirs. These factors make it difficult to accurately calculate the areal sweep coefficient of water flooding in ultra-low permeability reservoirs. Former researchers have conducted extensive researches on the areal sweep coefficient. The literature [12–14] used numerical simulation method to calculate the areal sweep coefficient under water flooding, but this method failed to consider the nonDarcy flow characteristics of ultra-low permeability reservoirs. Ji Bingyu [15] used the flow steam-tube method to deduce the production formula of different well patterns considering the non-Darcy flow characteristics of ultra-low permeability reservoirs, and proposed the concepts of starting angle and starting coefficient. Based on this, the literatures [16–22] derived the areal sweep coefficient of different well patterns considering the threshold pressure gradient. The above literatures did not consider the influence of the permeability anisotropy and oil-water viscosity difference. Therefore, they cannot be directly used to calculate the areal sweep coefficient under water flooding in ultra-low permeability reservoirs. In view of the characteristics of non-Darcy flow and permeability anisotropy in extra-low permeability reservoirs under the process of water flooding, we obtained streamlines distribution through solving the stream function based on coordinate transformation, and derived the areal sweep efficiency formula considering oil-water two phases non-piston displacement by streamline integral method. In combination with actual oilfield data, the effects of the ratio of oil to water, the threshold pressure gradient, the permeability anisotropy, pressure difference and well spacing on the areal sweep efficiency were analyzed with this method.

2 Mathematical Model 2.1

Basic Assumptions of the Mathematical Model

The mathematical model is subject to the following basic assumptions: (1) (2) (3) (4) (5)

The fluid is oil-water two-phase and non-piston displacement. Do not consider the compressibility of porous media and fluids. Do not consider the effect of capillary force and gravity. The formation is a homogeneous and uniform single oil layer. The threshold pressure gradient of oil phase and water phase are the same.

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143

Characteristics of Ultra-Low Permeability Reservoirs

Due to the threshold pressure gradient in ultra-low permeability reservoirs, the flow no longer meets the Darcy law. The non-Darcy flow formula is
 k k m ¼  rP 1  l jrPj

ð1Þ

Ultra-low permeability reservoirs often exhibit permeability anisotropy. The anisotropic reservoir can be converted to an equivalent isotropic reservoir based on coordinate transformation, and the coordinate transform formula is pffiffiffiffiffiffiffiffiffi 8 < x ¼ x0 pk=k ffiffiffiffiffiffiffiffiffix y ¼ y0 k=ky pffiffiffiffiffiffiffiffi : k ¼ kx k y

2.3

ð2Þ

Streamline Distribution

In an isotropic reservoir, according to symmetry, an injection-production well group in the five-point well pattern can be divided into four identical seepage units (Fig. 1), and the seepage unit △ABD can be further divided into two similar seepage units (unit △ABC and unit △ACD), A is an injector, B, D are production wells, and C is the midpoint of BD. According to Eq. (1), and by the superposition theory of potentials, the pressure at any point in the seepage unit DABC is

Fig. 1. Schematic of 5-spot well pattern

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" sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi# lq d x2 þ y2 ln Pðx; yÞ ¼ pi  2pk rw ðx  dÞ2 þ y2  pffiffiffiffiffiffiffiffiffiffiffiffiffiffi qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi  k d þ x2 þ y2  ðx  dÞ2 þ y2

ð3Þ

From the above formula, the seepage velocity component vx is mx ¼

q xd ½d  2x þ dðx2 þ y2 Þ h i 2p ðx2 þ y2 Þ ðx  dÞ2 þ y2 2

3

kk 6 xd x 7  4qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi  pffiffiffiffiffiffiffiffiffiffiffiffiffiffi5 2 2 l 2 x þ y 2 ðx  dÞ þ y

ð4Þ

Based on Eq. (4), the steam function can be written as  y 3 q 6 xd 7 wðx; yÞ ¼ vx dy ¼ 4  y 5 2p þ arctan x i kk h ðx  dÞ lnððx  dÞ2 þ y2 Þ  x lnðx2 þ y2 Þ  l 2

Z

arctan

ð5Þ

Therefore, the streamline equation for the seepage unit DABC is  y  yi q h arctan þ arctan 2p x " xd # 2 kk ðx  dÞ lnððx  dÞ þ y2 Þ  ¼ C1 l x lnðx2 þ y2 Þ

ð6Þ

where C1 ¼ w. Near the injection wells, x ! 0, y ! 0, the streamline equation can be approximated as y ¼ tan C2
x  where C2 ¼ 2p q C1 þ

kkd ln d l

ð7Þ

 .

Near the production wells, x ! d, y ! 0, the streamline equation can be approximated as y ¼  tan C2
ðx  dÞ

ð8Þ

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Therefore, for the sake of simple calculation, this article uses the above two intersecting straight lines to approximate the real streamlines (the solid line in Fig. 2 is the real streamline), and the approximate streamline distribution is shown in dotted lines in Fig. 2.

Fig. 2. Streamlines for seepage unit DABC

2.4

The Derivation of Areal Sweep Coefficient

In seepage unit DABC shown as Fig. 2, \CAB ¼ am , \CBA ¼ bm , and am = artanðy=dÞ, bm ¼ am . Take a stream line AEB, and the angle between the injection well and ∠EAB is a, and the angle between the production well and ∠EBA is b. The length of steam line AEB is L. The velocity of oil-water two-phase flow on streamline AEB is m ¼ l Rx f o

pi  pw  kL dx þ lo ðLxf Þ

0 lr krw þ kro

k

ð9Þ

k

Rx x where lko 0 f1 l krwdþ kro is the total flow resistance in oil-water mixing zone, and it can be r rewritten as lo k

Zxf1 0

dx lr krw þ kro

l xf1 ¼ w 0 k fw ðswf Þ

0 fwZ ðswf Þ

ð10Þ fw ðSw Þ 0 l xf1 dfw ðsw Þ ¼ w a krw k

0

R f 0 ðs Þ wÞ dfw0 ðsw Þ, fw0 ðswf Þ is water cut rate. where a ¼ f 0 ðs1wf Þ 0w wf fw ðkS rw w When the pressure difference between injection and production remains unchanged, the position of the water flooding frontier meets

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f 0 ðswf Þ xf ¼ w /

Zt vdt

ð11Þ

pi  pw  kL dt 0 kw xf þ k0o ðL  xf Þ

ð12Þ

0

Combining Eq. 9 and Eq. 10, we can get f 0 ðswf Þ xf ¼ w /

Zt 0

where k0w ¼ lwk a, k0o ¼ lko . After derivation and integral of Eq. 12, we can get ðk0w k0o Þ 2 f 0 ðswf Þðpi  pw  kLÞt xf þ k0o Lxf  w ¼0 2 /

ð13Þ

By solving the above formula, the position distribution of the water flooding frontier at different time points on different streamlines can be obtained. When k0w \k0o , the position is xf ¼ 2k0 L

o where D ¼ ðk0 k 0 , E ¼ Þ w

o

D 

pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi D2 þ 4E 2

ð14Þ

2fw0 ðswf Þðpi pw kLÞt . /ðk0w k0o Þ

When k0w ¼k0o , the position is

xf ¼

fw0 ðswf Þðpi  pw  kLÞt k0o L/

ð15Þ

With Eq. 14, the time when the frontier edge of the main stream AB reaches the inflection point e, t1 , and the time when the frontier edge of the main steam AB reaches production well B, t2 , can be obtained. When t  t1 , the swept area of flow unit DABC is 1 s1 ¼ 2

Za0 x2f da 0

where a0 is the starting angle

ð16Þ

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When t1 \t  t2 , the swept area of flow unit DABC is

s1 ¼

8 Rb0 > 2 1 2 sin a0 sin b0 1 > > d  < 2 sinða þ b Þ 2 ðL  xf Þ db 0

0

> > sin a sin b > : 12 d 2 sinða11 þ b11Þ  12

0 Rb1

2

ðL  xf Þ db þ

0

for a1  a0 1 2

Ra0 a1

ð17Þ x2f da

for a1 \a0

When t [ t2 , the swept area of flow unit DABC is 8 Rb0 > > 1 2 sin a0 sin b0 1 > d  ðL  xf Þ2 db for a1  a0 > 2 2 sinða þ b Þ < 0 0 b2 s1 ¼ > Rb1 Ra0 2 > 2 1 2 sin a1 sin b1 1 1 > d  > : 2 sinða1 þ b Þ 2 ðL  xf Þ db þ 2 xf da for a1 \a0 1

ð18Þ

a1

b2

Similarly, the swept area of flow unitDADC is s2. Based on the symmetry of the five-point well pattern and the area of flow unit ofDABC is s0 ¼ 0:25d
y, and therefore, the areal sweep efficiency of flow unit of DABC is g¼

s1 þ s2 s0

ð19Þ

3 Results and Discussion Taking a typical ultra-low-permeability reservoir in Changqing as an example, the effect of oil-water viscosity ratio, threshold pressure gradient, and injection-production parameters on the areal sweep efficiency under water flooding at five-spot well pattern in ultra-low permeability reservoirs was analyzed. The reservoir parameters are as follows: the porosity is 0.15; the permeability is 2 mD, the degree of permeability anisotropy (kx/ky) is 3; the oil viscosity is 5.0 mPa s; the water viscosity is 1.0 mPa s; threshold pressure gradient is 0.04 MPa/m; Water cut rate is 10 and a ¼ 1:5. 3.1

Effect of Oil-Water Viscosity Ratio

In the case of well spacing of 250  150 m, injection and production pressure difference of 18 MPa, and threshold pressure gradient of 0.04 MPa/m, the effect of oilwater viscosity ratio on areal sweep efficiency of five-spot well pattern is shown in Table 1. It shows that the greater the oil-water viscosity ratio, the smaller the areal sweep efficiency at the time of water breakthrough. This is mainly because the greater the oil-water viscosity ratio, the greater the difference in oil-water two-phase flow ability. Therefore, for ultra-low permeability reservoirs with large differences in oilwater viscosity, the oil-water viscosity ratio can be appropriately reduced through chemical reagents, so as to increase the areal sweep coefficient at the time of water breakthrough.

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Table 1. Results of water breakthrough time and areal sweep efficiency for different viscosity ratio of oil and water lo (mPa
s)

lw (mPa
s)

lo =lw

fw0 ðswf Þ

1 5 20

1 1 1

1 5 20

3 10 50

3.2

Water breakthrough time 42 33 22

Areal sweep coefficient at water breakthrough time 0.76 0.58 0.49

Effect of Threshold Pressure Gradient

In the case of well spacing of 250  150 m, injection and production pressure difference of 18 MPa, the effect of threshold pressure gradient on areal sweep efficiency of five-spot well pattern is shown in Fig. 3. It shows that before the production well water breakthrough, the areal sweep coefficient slowly increases with time and then increases rapidly. The larger the threshold pressure gradient, the longer the time of water breakthrough. This is because with the increase of the threshold pressure gradient, the additional resistance generated during the water flooding process will be greater.

Fig. 3. The effect of threshold pressure gradient on areal sweep efficiency (The asterisk indicates water breakthrough)

3.3

Effect of the Degree of Permeability Anisotropy

In the case of well spacing of 250  150 m, injection and production pressure difference of 18 MPa, the threshold pressure gradient of 0.04 MPa/m and the viscosity ratio of oil and water of 5, the effect of the degree of permeability anisotropy on areal sweep efficiency of five-spot well pattern is shown in Figs. 4 and 5. It shows that in the current well pattern condition, when the degree of permeability anisotropy is 3, the time of water breakthrough is the latest (Fig. 4), and the areal sweep coefficient at the time of water breakthrough is the largest (Fig. 5). The literature [9] also pointed out that the well spacing should be adjusted appropriately for anisotropic reservoirs based on permeability anisotropy in order to achieve an equilibrium displacement. When the

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ratio of well spacing to row spacing is equal to the square root of the degree of permeability anisotropy, the displacement is the most balanced.

Fig. 4. Water breakthrough time at different anisotropy degrees

3.4

Effect of Injection-Production Parameters

In the case of well spacing of 250  150 m, the threshold pressure gradient of 0.04 MPa/m and the viscosity ratio of oil and water of 5, the degree of permeability anisotropy of 5, the effect of injection and production pressure difference on areal sweep efficiency of five-spot well pattern is analyzed. Meanwhile, In the case of injection and production pressure difference of 18 MPa, the threshold pressure gradient of 0.04 MPa/m and the viscosity ratio of oil and water of 5, the degree of permeability anisotropy of 5, the effect of well spacing on areal sweep efficiency of five-spot well pattern is analyzed. The result is shown in Table 2. It shows that the larger the pressure difference between injection and production, the earlier the time of water breakthrough and the larger the areal sweep coefficient at the time of water breakthrough. Under the current well pattern conditions (250  150 m), when the row distance is reduced from 190 m to 150 m, the areal sweep coefficient of seepage unit △A’B’D’at the time of water breakthrough increases significantly. When the row spacing is further reduced, the areal sweep coefficient of the seepage unit △A’B’D’ at the time of water breakthrough is reduced.

Fig. 5. Areal sweep efficiency at different anisotropy degrees

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Table 2. Results of water breakthrough time and areal sweep efficiency for different pressure differences and well spacing Injection-production parameters

Water breakthrough time

Pressure 16 difference 18 (MPa) 20 Well 250 spacing 250 250 250 230 250 270 290

40 33 27 25 33 33 33 26 33 36 36

       

130 150 170 190 150 150 150 150

m m m m m m m m

Areal sweep coefficient of unit △A’B’C’ at water breakthrough time 0.59 0.61 0.63 0.42 0.61 0.55 0.50 0.58 0.61 0.54 0.37

Areal sweep coefficient of unit △A’C’D’ at water breakthrough time 0.52 0.55 0.57 0.59 0.55 0.27 0.13 0.38 0.55 0.60 0.57

Areal sweep coefficient of unit △A’B’D’ at water breakthrough time 0.55 0.58 0.60 0.51 0.58 0.41 0.31 0.48 0.58 0.57 0.47

4 Conclusions In this paper, a new mathematical model for areal sweep coefficient under water flooding in ultra-low permeability reservoir is set up. The following conclusions can be derived as follows: (1) When calculating the sweep coefficient under water flooding in ultra-low permeability reservoirs, it is necessary to consider not only the characteristics of nonlinear flow, but also the influence of permeability anisotropy and oil-water viscosity difference. (2) In view of the characteristics of non-Darcy flow and permeability anisotropy in extra-low permeability reservoirs under the process of water flooding, streamlines distribution was obtained through solving the stream function based on coordinate transformation, and the areal sweep efficiency formula considering oil-water two phases non-piston displacement was derived by streamline integral method. Example calculations show that the derived formula can be reasonably calculated areal sweep coefficient of ultra-low permeability reservoir. (3) The larger the oil-water viscosity ratio or the smaller the injection pressure difference, the smaller the areal sweep coefficient at the time of water breakthrough. Adjusting the well spacing is an effective method to improve the areal sweep coefficient of water flooding, and the balanced displacement can be achieved when the ratio of well spacing to row spacing is equal to the square root of permeability anisotropy intensity.

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References 1. Wang D, FU J, Qihong LEI, et al. Exploration technology and prospect of low permeability oil-gas field in Ordos Basin. Lith Ologic Reserv. 2007;19(3):126–30. 2. Jianhong XU, Linsong CHENG, Yin ZHOU, et al. A new method for calculating kickoff pressure gradient in low permeability reservoirs. Petr Explor Dev. 2007;3(5):594–7. 3. Li S, Cheng L, Li X, et al. Non-linear seepage flow models of ultra-low permeability reservoirs. Petr Explor Dev. 2008;35(5):606–12. 4. Xiong E, Lei Q, Liu X, et al. Pseudo threshold pressure gradient to flow for low permeability reservoirs. Petrol Explor Dev. 2009;36(2):232–6. 5. Yang Z, Yu R, Su Z, et al. Numerical simulation of the nonlinear flow in ultra-low permeability reservoirs. Petrol Explor Dev. 2010;37(1):94–8. 6. Zhao Y, Cheng Y, Liu Y, et al. Study on influence of start-up pressure gradient to microseepage in low permeability reservoirs and development trends. Petr Geol Recovery Effi. 2013;20(1):67–73. 7. Hidayati DT, Chen HY. The reliability of permeability-anisotropy estimation from interference testing of naturally fractured reservoirs. SPE 59011,2000. 8. Ding Y, Chen Z, Zeng B, et al. The development well-pattern of low and anisotropic permeability reservoir. Acta Petroleum Sinica. 2002;23(2):64–7. 9. Li Y, Wang D, Li C. Vectorial well arrangement in anisotropic reservoirs. Petrol Explor Dev. 2006;33(2):225–7. 10. Liu Y,Xu M,Peng D,et al. Numerical simulation of petroleum reservoir with anisotropic permeability. Chin J Comput Phys 2007;24(3):295–300. 11. Cheng L. Advanced fluid flow in porous media. Beijing: Petroleum Industry Press,2011:287–299. 12. Zhang L, Lang Z. Determination of areal sweep efficiency of pattern flooding by use of simulation. J Univ Petrol China. 1988;12(3):86–97. 13. Wu B, Yao J, Lv A. Research on sweep efficiency in horizontal-vertical combined well pattern. Acta Petroleum Sinica. 2006;27(4):85–8. 14. Yao K, Jiang H, Wu B, et al. Research on sweep efficiency in five spot horizontal-vertical combined well pattern. J Yangtze Univ (Nat Sci Edit)Sci Eng V. 2007;4(2):187–9. 15. Ji B, Li L, Wang C, et al. Oil production calculation for areal well pattern of lowpermeability reservoir with non-Darcy seepage flow. ACTA Petroleum Sinica. 2008;29 (2):256–61. 16. Guo F, Tang H, LV D, et al. Effects of seepage threshold pressure gradient on areal sweep efficiency for 4-spot pattern of low permeability reservoir. J Daqing Petrol Inst. 2010;34 (1):33–8. 17. Guo F, Tang H, Lv D, et al. Effects of seepage threshold pressure gradient on areal sweep efficiency for five-spot pattern of low permeability reservoir. J Daqing Petrol Inst. 2010;34 (3):65–8. 18. Lv D, Tang H, Guo F, et al. Study of areal sweep efficiency for invert 9-spot pattern of low permeability reservoir. J Southwest Petrol Univ (Sci Technol Edition). 2012;34(1):147–53. 19. Zhu S, Zhu J, An X, et al. Research on areal sweep efficiency for rhombus invert 9-spot areal well pattern of low-permeability reservoir. J Chongqing Univ Sci Technol (Natural Science Edition). 2013;15(2):80–3.

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20. Yadong QI, Qun LEI, Zhengming YANG, et al. Calculation and application of effective development coefficient for irregular triangular patterns in extra-low permeability fault block oil reservoirs. J Centr South Univer (Science and Technology). 2012;43(3):1065–71. 21. Yang P,Xu S,Luo Y,et al. Evaluation of effective development coefficient for triangle well patterns in extra-low permeability fault-block reservoirs of Jiangsu Oilfield. Complex Hydrocarbon Reserv 2011;4(2):52–5. 22. Zhou Y, Tang H, Lv D, et al. Areal sweep efficiency of staggered well pattern of horizontal wells in low permeability reservoirs. Lith Ologic Reserv. 2012;24(5):124–8.

Dynamic Fracture and Matrix Heterogeneity and Remaining Oil Models of Ultra-Low Permeability Reservoir Li Liu(&), Youjing Wang, and Jiahong Li Research Institute of Petroleum Exploration and Development, Beijing, China {Liuli85,wangyoujing,lijia-hong}@petrochina.com.cn

Abstract. The ultra-low permeability reservoir is rich in resource, but with the development of oilfield water flooding, contradictions are becoming more and more obvious, resulting from heterogeneity of thick sandstones and dynamic fractures. In order to solve the above problems, this paper takes HuaQing B153 block as an example, based on the study of sedimentary facies and reservoir architecture, the origin type, geometry, size of a single sandbody and the spatial superimposed styles, with its effects on the reservoir connectivity, are determined, and matrix heterogeneity is figured out. In combination with the characteristics and distribution of dynamic fractures and nature fractures, the relationship between dynamic fractures with natural fractures, single sandbody configurations, and reservoir heterogeneity parameters is clearly pointed out. In the following, four remaining oil distribution patterns are established controlled by the dynamic fracture and reservoir matrix heterogeneity, including (1) model integrating dynamic fracture—natural fracture(siltstone)—composite single sandbody—siltstone; (2) model integrating dynamic fracture—natural fracture (top calcite)—siltstone—composite single sandbody; (3) model integrating dynamic fracture—natural fracture (base calcite)—siltstone—composite single sandbody; and (4) model integrating dynamic fracture—natural fracture (siltstone)—siltstone—single sandbody. These models will instruct well pattern adjustment and the remaining oil potential prediction. Keywords: Ultra-low permeability reservoir
Sandy debris flow fracture
Matrix heterogeneity
Remaining oil model




Dynamic

Copyright 2018, Shaanxi Petroleum Society. This paper was prepared for presentation at the 2018 International Field Exploration and Development Conference in Xi’an, China, 18–20 September, 2018. This paper was selected for presentation by the IFEDC Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the IFEDC Committee and are subject to correction by the author(s). The material does not necessarily reflect any position of the IFEDC Committee, its members. Papers presented at the Conference are subject to publication review by Professional Committee of Petroleum Engineering of Shaanxi Petroleum Society. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of Shaanxi Petroleum Society is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of IFEDC. Contact email: [email protected]. © Springer Nature Singapore Pte Ltd. 2020 J. Lin (ed.), Proceedings of the International Field Exploration and Development Conference 2018, Springer Series in Geomechanics and Geoengineering, https://doi.org/10.1007/978-981-13-7127-1_15

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1 Introduction The low-permeability reservoirs in the Ordos Basin are rich in resources and have great potential for development. In this basin, they are expected to have proven reserves of 3.54 billion tons and proven reserves of 820 million tons. Chang 63 reservoir in Huaqing B153 block is a typical ultra-low permeability reservoir, and it has been developed effectively. However, after a period of production, some development conflicts have become increasingly prominent, mainly in the following two aspects: (1) water flooding occurs in multiple directions, and the water content is greater than 95%. In some wells, water injection is not effective, which leads to a reduction of plane sweep efficiency; (2) affected by dynamic fractures and the heterogeneity of the matrix reservoir, the injecting water runs along the fractures or high-permeability zones, resulting in water flooding and non-uniform development in thick sandy debris flow reservoirs. In order to solve these problems, this paper focuses on the geometry, scale and spatial configuration of single sandbody of gravity flow, and its influence on reservoir heterogeneity, discuss the heterogeneity of dynamic fractures and matrix reservoirs, establish bins of dynamic fractures and matrix reservoirs and the remaining oil distribution model under different control factors. This paper will provide basis for well pattern adjustment.

2 Geology and Development The B153 block is located in the Yishan slope of eastern part of Ordos Basin [1]. The tectonic structure is a simple monocline, gently dipping to west, with a dip angel less than 1° (Fig. 1). The Chang 63 reservoir in this area is a typical ultra-low permeability reservoir with normal ground temperature (3.2 °C/100 m) and low formation pressure (initial pressure coefficient = 0.79). Chang 63 reservoir is sandy debris flow or turbidity 12 21 sediment and is divided into six layers, including Chang 611 3 , Chang 63 , Chang 63 , 22 31 32 Chang 63 , Chang 63 and Chang 63 , all of which are divided into two sub-layers. The rock type is mainly feldspar sandstone or lithic feldspathic sandstone, fine grained, with a grain size range of 0.07–0.16 mm; the average porosity is 9.47%, and the average permeability is 0.34  10−3 lm2, with strong reservoir heterogeneity. In addition, natural fractures along EW or NE develop in upper Chang 63 reservoir, enhancing the heterogeneity of the reservoir. The B153 block takes inverted nine spot injection pattern to develop and has undergone four development stages, including the exploratory well production phase, the comprehensive production construction phase, the water flooding phase and the production plateau stage.

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Fig. 1. Tectonic units and location of B153 block

3 Dynamic Fracture Characteristics and Heterogeneity Characterization 3.1

Definition

Dynamic fracture is a new development geological property of ultra-low permeability reservoirs [2]. It was closed at the original state, but with the increase of injection pressure and formation pressure, the formation at the bottoms of injection cracked and formed fractures [3–5], which can extend and communicate with each other. Both the geometric parameters and permeability of these fractures behave dynamic changes. The formation of dynamic fractures leads to a step shaped increase of water content between major oil wells, but the sweep effect of lateral oil wells is not obvious. Therefore, the dynamic fracture is the most import heterogeneity parameter in the late development stage of ultra-low permeability reservoir. The prediction of the remaining oil distribution is of great significance.

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Identification of Dynamic Fractures

The dynamic fractures can be identified comprehensively by using well loggings, interwell interference well test, tracer analysis, water injection profiles, and production performances of production and injection wells [2–5]. Specifically for the following aspects: (1) The production wells with dynamic fractures have a stepwise increase in water content, with liquid increases and oil production rate dropping rapidly. The injection volume and apparent index of the connected injection wells also increase rapidly, but the oil pressure remains basically unchanged; (2) the water injection profile is characterized by a peak shape water intake volume, the API of isotope for water injection profile is larger than 500, the peak value and intensity of the isotope are more than three times of the average value; the water injection index curves often exhibit break points when dynamic fracture occurs and the water intake capacity at the point changes significantly (Fig. 2); (3) the well test analysis shows the characteristics of fracture seepage; time-lapse well indicates that during the water injection process, the fracture half-length is increasing and is more than 200 m. The effective permeability of well test interpretation twice as large as the core permeability; and (4) tracer monitoring has obvious orientation.

Fig. 2. Injection profile and index curve used to identify dynamic fractures

3.3

Spatial Distribution

In Bai 153 block, there are 43 dynamic fractures identified, and the dynamic fractures are multi-directional, mainly in NE85°, NE105° and NE45°, but with some fractures in other directions. Vertically, dynamic fractures develop differently in different sand layers. The fractures in Chang 612−1 layer are the most developed, with 14 dynamic fractures, 3 followed by Chang 611−1 and 611−2 layers, and the corresponding number of fractures 3 3 are eight and six, respectively (Fig. 3). The multi-directional dynamic fractures are

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different in lithology section. The dynamic fractures in the direction of NE85° are most developed in calcareous interlayers of the sand debris flow, and some of them are developed in the oil-bearing siltstones, other fractures are multi-directional and generally distributed in the main part of sand debris flow with oil patch.

Fig. 3. Distribution of dynamic fractures

In plane, the distribution of dynamic fractures also shows obvious heterogeneity, mostly concentrated in the northern part of the project area, mainly in the direction of NE85° or 105° in northeast, and fractures in NE45° direction in northeast part are rarely developed; the development degree of dynamic fracture is low in south part of B153 block (Fig. 4), and the fractures are only distributed Chang 611−1 and Chang 611−2 , and 3 3 the orientation is mostly NE45° and NE150°. The multi-dirsectional dynamic fractures in the non-NE85° direction are mainly developed in the same single sandbody, and the fracture length is not more than one well spacing, about 200 m; the dynamic fractures length in the direction of NE85° is about 900–1000 m, and communicates 2–3 sandy debris flow single sandbodies or turbidity single sandbodies. 3.4

Controlling Factors of Dynamic Fractures Heterogeneity

In the process of water injection in ultra-low permeability reservoirs, the bottom pressure of injection well increases and exceeds the fracture pressure of rocks, dynamic fracture form and continue to extend towards to production wells; besides, the detonation fracturing and compound perforating form fractures of small scale, which are not controlled by the stress. These fractures extend along the direction of the maximum principal stress today to form dynamic cracks [2]. In B153 block, the formation of dynamic fractures is related to the opening of natural fractures. In vertical, the vertical dynamic fracture develops in the layer where natural fractures developed, or the distance from the natural fracture interval to dynamic fracture zone is less than 10 m. In plane, dynamic fractures are mostly located in areas where the natural fracture density is relatively large (Fig. 5). Therefore, the development degree and opening pressure of natural fracture are the main controlling factors affecting the development of dynamic fractures.

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Fig. 4. Distribution of dynamic fractures in C612−1 3

Fig. 5. Natural fracture density in C612−1 3

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Based on core observations and imaging log interpretation results, natural fractures in the B153 block are shear fractures with high angles, small fracture heights and infilling. The dominant fracture orientations are NE-NEE and EW-NWW, followed by NW-NNW. Natural fractures are most developed in calcareous siltstones, followed by siltstones and argillaceous siltstones. They are basically not developed in mudstones. The natural fractures are most developed at the top and bottom of the main part of sandy debris flow body or at the edge part, and the fracture development degree in the turbidity and lacustrine sedimentation is significantly low. Based on the observation of natural fractures in the core, in application of conventional logging curves, natural fractures were identified and predicted by the multi-fractal and neural network quantitative method [6]. The results indicate that natural fractures are mainly distributed in the northern part of the study area and dotted scattered in the south area. The opening pressure of natural fractures is related to the direction of the natural fracture, the orientation of the maximum principal stress and the angle between these two factors, and the smaller the angle between the fracture strike and the maximum horizontal principal stress, the easier it is to open [7]. Zeng Lianbo (2009) [8] proposed a formula to calculate the pressure required to open natural fractures in different strike orientations, which is applied in Chang 63 reservoir in B153 block (Table 1). When calculated, the fracture dip (h), Poisson’s ratio (l), buried depth, recent minimum (fr3) and maximum principal stress (fr1), water density (qW = 1.13) and rock density(qS = 2.52) is defined to be a constant, but the angle (b) between fracture trend and recent maximum principal pressure is different. Table 1. Opening pressure of natural fracture h (°) 90 90 90 90 90 90

l 0.1989 0.1989 0.1989 0.1989 0.1989 0.1989

fr1 (MPa/km) 26 26 26 26 26 26

fr3 (MPa/km) 15 15 15 15 15 15

b (°)

Open pressure (MPa)

5 10 15 20 25 30

26.1 30.6 34.7 38.5 41.9 45.0

According to the calculation results, natural fractures with angle less than 15° from the direction of the maximum principal stress can be opened to form dynamic cracks. Therefore, natural fractures in the direction of NE75°-85° can be preferentially opened to form dynamic fractures with a bottom pressure of 35 MPa. Afterwards, as the bottom pressure of the injection well increases, dynamic fractures in other directions are opened one after another, forming the current multi-directional dynamic fractures. In addition, it is necessary to further explain that the opening pressure of natural fractures is directly proportional to the depth of burial. With the increase of burial

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depth, the pressure required for the opening of natural fractures increases. Therefore, under the precondition that other geological conditions are consistent, and the upper part of Chang 63 is more likely to develop dynamic fractures in multiple directions than the lower part.

4 Heterogeneity Characterizations of Matrix Reservoirs 4.1

Reservoir Architecture of Chang 63 Thick Sand

Chang63 reservoirs of Bai 153 block are mainly deep gravity flow deposits. Based on sedimentary facies research, it is possible to identify sandy debris flow and turbidity sand bodies. Sandy debris flow reservoirs are further divided into the main part of sand debris flow and the edge of sandy debris flow deposition (Fig. 4). The average thickness of Chang 63 reservoir is 25.3 m, which is widely distributed within the whole study area. The single sandbody of sandy debris flow and turbidity are vertically overlapped and laterally assembled, and the reservoir complex extends from the northeast to southwest. The barrier lithology is mainly mudstone and argillaceous siltstone; the interlayer lithology is argillaceous siltstone and calcareous siltstone. Controlled by fluctuation of lake level, the complex sand bodies are spatially superposed and distributed in three ways: isolated, assembled and superposed. At the stage of lake level rising (Chang 633), the A/S is relatively large, sand debris flow and turbidity sand bodies are isolated from each other, and there is no connectivity between them; after the lake level falling (Chang623), the A/S decreases, and the spatial superposition pattern is assemble, that is, part of sandy debris flow and turbidity reservoir are pieced together, and the connectivity is weak. As the lake level continues to fall down (Chang 613), the A/S decreases rapidly and the source supply is abundant enough, the single sand bodies are stacked in multiple stages of sand debris flow, and the turbidity flow is basically not developed. At this time, the space superposition pattern is the main type, and the sand bodies are connected to each other. Different types of spatial distribution of complex sandbodies reflect differences in the connectivity, which provides a geological basis for water injection in spatial. 4.2

Connectivity of Sandbodies

There are three types of vertical communication models of sand bodies, including disconnected, weakly connected and well connected. For disconnected type, the sandy debris flow of different phases or single sandbody of turbidity is separated by a mudstone interlayer and does not communicate with each other; For weak-connected type, single sandbody of sandy debris flow is in direct contact with the turbidity flow, or the contact area of the two-stage sandy debris flow sandbodies is very limited. The connected type refers to the superimposition or lateral overlap of single sand bodies in two stages of sand debris flow. The contact area is large, and the degree of communication between them is high (Fig. 6).

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Fig. 6. Connectivity of single sandbodies in Chang 63

4.3

Heterogeneity within a Single Sandbody

The lithology of the main part of sandy debris flow is dominated by grey-brown massive oil trace siltstones, with a homogeneous rhythm or a positive composite rhythm. The average porosity is 10.7%, and the average permeability is 0.2  10−3 lm2. The average permeability ratio is 14.61, and the heterogeneity coefficient of permeability is 2.5. Its heterogeneity is weak. The lithology at the edge of the sandy debris flow is dominated by grey-brown oil trace siltstone, with a positive rhythm. The grain size becomes finer upward, and the mud content increases. The average porosity of that is 9.54%, the average permeability is 0.16  10−3lm2, the permeability ratio is 24.99 and the coefficient of permeability is 3, its heterogeneity degree is stronger than the main body. The turbidity current flow deposits mainly develop positive rhythms, and the lithology is greyish brown siltstone or muddy siltstone with argillaceous stripes at the top. The average porosity is 7.79%, the permeability is 0.08  10−3lm2, the permeability ratio is 29.66, the permeability coefficient is 4.05, and the heterogeneity is stronger than the sandy debris flow. 4.4

Heterogeneity of Interlayers

The interlayers in B153 block mainly include argillaceous and calcareous interlayers. The argillaceous interlayers develop between two stages of single sandbody (Fig. 6), which correspond to the fourth-order interface of reservoir configurations, and divide the sandy debris flow or turbidity current sedimentation of different stages. The average single layer thickness of this type of muddy interlayer is 0.84 m; besides that, it can be observed within single sandbody of the edge of sandy debris flow, with an average single layer thickness of 0.22 m, which is relatively thinner. In plane, the argillaceous interlayer thickness is generally less than 4 m, with a lenticular distribution. It is widely distributed in Chang 611−1 , Chang 622−1 and Chang 622−2 . 3 3 3 On the top of the sandy debris flow sandbody or the bottom of the turbidity current deposits, there can develop 1–2 layers of calcareous interlayers with an average thickness of 0.39 m. The distribution of calcareous interlayers is discontinuous and random and extends in 1–2 well spaces, about 400 metres. In plane, it is scattered distributed, like a patch, and the development degree of calcareous interlayers is relatively low in Chang 622−1 and Chang 622−2 . 3 3

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5 Dynamic Fracture-Matrix Comprehensive Heterogeneity and Remaining Oil Model 5.1

Remaining Oil Distribution Control Factors

5.1.1 Permeability Heterogeneity Due to the variance of permeability in different single sand bodies, in the process of waterflood injection, the injected water penetrates along the high-permeability layer, like the main part of sandy debris flow sandbody, while the low-permeability layer has relatively poor waterflood effect, such as the edge of sandy debris flow and the turbidity sandbody and the remaining oil is retained in there. In plane, the injected water enters the main part of the sandy debris flow with relatively high permeability, and the injection velocity is 24–28 m/d, resulting in water flooding of the wells along the direction of the source, and perpendicular to the source, reservoirs have poor water flood effect and remaining oil was kept in there. The rhythm of the main part of the sandy debris flow is characterized by uniform rhythm, there is no significant difference in permeability, and with a uniform water injection; the edge of sandy debris flow is positive rhythm, permeability on the top is larger than that of the bottom, so the volume of injected water is bigger than that of the bottom, and the upper reservoir is not fully displaced, remaining oil can be found there (Fig. 7). 5.1.2 Reservoir Configurations The superposition pattern of single sand bodies has a significant control over the remaining oil distribution. (1) Spatial superposition pattern In plane, the single sand bodies of different origin, which deposited at the same time, are overlapped between each other (Fig. 8a, b, and c), and the remaining oil is mainly distributed in the fringe zone where the sand debris flow is converting to the mudstone (Fig. 8c); in vertical, the stacking patterns of different periods of sandy debris flow sandbodies are mainly superposed style, followed by isolated style, the remaining oil may be located on one side of the sandy debris flow single sandbody or fringe zone of both sides (Fig. 8d). (2) Spatial assembled pattern In this model, the single sandbody of debris flow and the turbidity are pieced together in plane and in vertical. Due to the difference of permeability between these two bodies, the injection water preferentially runs in sandy debris flow single sandbody. So, the remaining oil is enriched in turbidite sand bodies that are in contact with the sandy debris flow (Fig. 8e, f). (3) Spatial isolated pattern Single sandbodies of sandy debris flow or turbidity current are isolated from each other, surrounded by lacustrine mudstone. Under the premise of good well network configuration, each sand debris flow reservoir will be effectively developed with water

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Fig. 7. Effect of the permeability heterogeneity on the remaining oil distribution

injection, and the remaining oil may be enriched in the lateral edge of the sandy debris flow tongue (Fig. 8g); while in the case of an imperfect well pattern, due to the disconnection of sandbodies, the injected well maybe penetrate one single sandbody, but the production well maybe drill another one, so, this will cause the entire hydrocarbon in sandy debris flow reservoir is not exploited. 5.1.3 Interlayers The argillaceous interlayer in Chang 63 reservoir develops at the top or bottom of a single sandbody of sandy debris flow and the calcareous interlayer often develops at the top and bottom of a single sandbody of sandy debris flow. In multilayer water flooding

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Fig. 8. Effect of the reservoir architectures on the remaining oil distribution

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process, if the water injection interval is located in the upper part, and there is a thin layer of calcareous interlayer or argillaceous interlayer between the upper and lower part of single sand bodies, the injection water will be blocked to moving downward. Remaining oil is formed inside the lower part of a single sandbody of sandy debris flow. 5.1.4 Dynamic Fractures The permeability of dynamic fracture is ten or even times more than that of the matrix reservoir and shows a strong heterogeneity compared with the surrounding matrix reservoir. During the stage of water injection, the injected water runs along the strike direction of the dynamic fracture, forming a linear high-water flooding zone. The matrix reservoir on both sides of the dynamic fracture has poor waterflood efficiency, where the remaining oil is rich (Fig. 9). In the profile, dynamic fractures and matrix permeability differ greatly, and interlayer interference is serious. From the injection profile, it can be seen that the dynamic fracture zones behave as peak shape and with serious water flooding, however, the efficiency of water injection in matrix reservoir is bad. So, the remaining oil stays in the matrix reservoir above and below the dynamic fracture.

Fig. 9. Effect of the dynamic fracture on the remaining oil distribution

5.2

Combination Model of Dynamic Fracture and Matrix Reservoir and Remaining Oil Distribution

The formation of dynamic fractures is closely related to the opening of natural fractures and is controlled by the scale and development of natural fractures, the current maximum horizontal principal stress, and the injection pressure. The development degree of natural fractures in the area is relevant to reservoir sedimentary facies, lithology and rock brittleness. Therefore, based on the study of the distribution of dynamic fractures, with reservoir performance dynamic analysis, this study discussed the relationship between dynamic fracture positions and natural fractures and matrix reservoir parameters. There are four types of combination of dynamic fractures and matrix reservoirs, with four relevant remaining oil distribution models (Fig. 10).

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Fig. 10. Comprehensive remaining oil models of dynamic fracture and reservoir matrix heterogeneity

5.2.1 Dynamic Fracture—Natural Fracture (Siltstone)—Siltstone— Composite Sand Bodies Remaining Oil Model In plane, the extension direction of dynamic fractures is mainly NE85°, and the fracture length is relatively large. Usually, it cuts through 2–3 sandy debris flow sand bodies; in vertical, the dynamic fracture develops in the upper siltstone of the main part of sandy debris flow, and the lithology of the upper and lower matrix reservoirs is a relatively high permeability siltstone (Fig. 11). In this model, the wells along the strike direction of the dynamic fracture suffer serious water flooding, and the wells perpendicular to the strike direction are not swept or ineffectively swept, resulting in the enrichment of the remaining oil. From water injection profile, the water absorption capacity of the dynamic fracture zone is significantly higher than that of the matrix reservoir, and the interlayer interference phenomenon is serious. Therefore, in vertical, affected by the rapid flooding and gravity effects of dynamic fractures, the reservoir above dynamic fractures is full of remaining oils.

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Fig. 11. Remaining oil model integrating dynamic fracture, natural fracture (located in siltstone), siltstone and composite sand bodies, well G132-151

5.2.2 Dynamic Fracture—Natural Fracture (Top Calcareous Siltstone)— (Argillaceous) Siltstone—Composite Sand Bodies Remaining Oil Model The strike direction of dynamic fractures is NE85°, which intersect 2–3 sandy debris flow single sand bodies; in section profile, natural fractures develop in the dynamic fractures zone, and dynamic fractures are found in calcareous siltstone, at the top or middle part of the sandy debris flow reservoir; the lithology of the matrix reservoir around the dynamic fracture is mainly siltstone or argillaceous siltstone, and its physical properties are relatively good (Fig. 12).

Fig. 12. Remaining oil model integrating dynamic fracture, natural fracture (located in top calcareous siltstone), siltstone and composite sand bodies, well G134-147

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In this model, the whole sandy debris flow reservoir may be watered out, and the remaining oil mainly accumulates in both sides of the sandy debris flow reservoir, which is close to the mudstone; however, if the matrix reservoir below dynamic fractures is argillaceous siltstone, with relatively poor physical properties, the injected water is preferentially runs along dynamic fractures, and it is difficult to enter into the lower matrix reservoir. The remaining oil is mainly distributed in argillaceous siltstone where dynamic fractures are not developed. Among them, the plane remaining oil is still distributed in both sides of the fracture. 5.2.3 Dynamic Fracture—Natural Fracture (Bottom Calcareous Siltstone)—(Argillaceous) Siltstone—Composite Sandstones Remaining Oil Model In plane, the strike direction of the dynamic fracture is still NE85°, which intersects 2– 3 sandy debris single sand bodies; in vertical, the dynamic fractures occur in the zone where natural fractures are developed and located in calcareous siltstone at the bottom or the lower part of single sand bodies of sandy debris flow; the lithology of the upper matrix reservoir above dynamic fracture is dominated by argillaceous siltstone, followed by siltstone. In this model, directional water flooding occurs along the dynamic fractures at the bottom of sandy debris flow, while the sweep efficiency of matrix reservoir above the dynamic fracture is very low, and a large amount of remaining oil is abundant in it. In plane, the remaining oil mainly distributes on both sides of the dynamic fractures. 5.2.4 Dynamic Fracture—Natural Fracture (Siltstone)—Siltstone— Single Sandbody Remaining Oil Model The dynamic fractures in this model are multi-directional, mainly including NE85° and NE45°, and the latter is dominant. In plane, the dynamic fractures have a short fracture length and generally only develop within a single sandy debris flow reservoir. Dynamic fractures develop in siltstones of the main part of the sandy debris flow, which have relatively good physical properties. The lithology of the matrix reservoir around dynamic fractures is siltstone, and in some wells it is calcareous siltstone (Fig. 13).

Fig. 13. Remaining oil model integrating dynamic fracture, natural fracture (located in siltstone), siltstone and single sandbody, well G126-155

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In this model, the remaining oil is mainly distributed in the sandy debris flow reservoir above the dynamic fracture. In addition, if a thin layer of calcareous or argillaceous interlayer develops within the sandy debris flow, the remaining oil is more likely to develop in the zone close to interbred and the dynamic fractures; in plane, the remaining oil mainly distributed on both sides of the fractures or the cross area of two sets of fractures.

6 Conclusions (1) The dynamic fractures are developed in north part of project area, with is closely related to the opening of natural fractures. Affected by the dynamic fractures, the injected water runs along the fracture zones, which leads to the low plane sweep efficiency of two sides perpendicular to the fracture, resulting in the accumulation of oil. (2) Chang 63 thick reservoir is composed of complex sandbodies of sandy debris flow and turbidity current, and the permeability variations of different genesis sandbodies and the architecture of the reservoir lead to strong reservoir heterogeneity. (3) Based on the characteristics and distribution of dynamic fractures and nature fractures, the relationship between the dynamic fracture and the sedimentary facies, single sandbody configurations, and the reservoir heterogeneity parameters is clearly pointed out and establishes four complex remaining oil distribution models of dynamic fractures and matrix heterogeneity. Acknowledgements. This work was completed under the Department of Development in Research institute of petroleum exploration and development. The authors wish to acknowledge Yingcheng Zhao, Chang Liu and Zhengdong Lei and Tao Yu for their contributions.

References 1. Zhang FL. Relation of multicycles to oil and natural gas in the Ordos basin. Petrol Geol Exp. 2004;26(2):138–42. 2. Wang YJ, Song XM, Tian CB, Shi CF, Li JH, Hui G, Hou JF, Gao CN, Wang XJ, Liu P. Dynamic fractures are an emerging new development geological attribute in waterflooding development of ultra-low permeability reservoirs. Petrol Explor Dev. 2015;42 (02):222–8. 3. Gadde PB, Sharma MM. Growing injection well fractures and their impact on waterflood performance. In: SPE annual technical conference and exhibition, 2001. 4. Perkins TK, Gonzalez JA. The effect of thermoelastic stresses on injection well fracturing SPE 11332-PA, 1985. 5. Van den Hoek PJ, Hustedt B, Sobera M. Dynamic induced fractures in waterfloods and EOR, SPE 115204, 2008. 6. Prioul R, Jocker J. Fracture characterization at multiple scales using borehole images, sonic logs, and walk around vertical seismic profile. AAPG Bull. 2009;93(11):1503–16.

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7. Zeng LB, Gao CY, Qi JF. The distribution rule and seepage effect of the fractures in the ultralow permeability sandstone reservoir in east Gansu Province, Ordos Basin. Sci China Ser D Earth Sci. 2008;51:44–52. 8. Zeng LB, Li XY. Fractures in sandstone reservoirs with ultra-low permeability: a case study of the Upper Triassic Yanchang formation in the Ordos Basin, China. AAPG Bull. 2009;93 (4):461–77.

Production Analysis Method Based on Material Balance Pseudo-time for Water Production Gas Wells Jianning Luo1,2(&), Yanyan Sun1,2, Bo Zhang1,2, Jun Yue1,2, and Minghui Huo1,2 1

2

Research Institute of Exploration and Development, Changqing Oilfield Company, PetroChina, Xi’an 710018, China {luojn_cq,sunyanyan_cq,zhangbo1_cq,yuejun_cq, hmh02_cq}@petrochina.com.cn State Engineering Laboratory for Exploration and Development of Low Permeability Oil and Gas Fields, Xi’an 710018, China

Abstract. Material balance pseudo-time has the characteristics of both pseudotime and material balance time; it can not only realize the linearization of gas flow equation, but also establish equivalent relation of gas wells between variable rate and constant rate, it becomes one of the most important parameters in modern production analysis. In addition, due to the complicated mechanism of gas and water flow and the difficulty in describing the gas and water relationship, the production analysis method for the water production gas well is still in the exploratory stage, and there is no effective method which is widely adopted. Therefore, this paper starts from the material balance equation of gas-water reservoir, builds the expression of material balance pseudo-time, and acquires water content in gas reservoir by the use of production index curves method. In further, it is possible to calculate permeability (K), drainage radius (Re), gas well reserve (G), and so on. Consequently, a production analysis method which provides effective guidance for water production gas wells is built. Keywords: Material balance pseudo-time Gas-water reservoir
Production analysis


Water production gas well


Nomenclatures

Bw Cti Cgi G Gp pi p psc pp qg T

Formation volume factor of water [m3/m3] Total system compressibility at initial reservoir pressure [1/MPa] Gas compressibility at initial reservoir pressure [1/MPa] Original gas in place [108m3] Cumulative gas production [104m3] Initial reservoir pressure [MPa] Currently reservoir pressure [MPa] 0.101[MPa] Pseudo-pressure at currently reservoir pressure [MPa2/(mPa s)] Production rate [104m3/d] Reservoir temperature [K]

© Springer Nature Singapore Pte Ltd. 2020 J. Lin (ed.), Proceedings of the International Field Exploration and Development Conference 2018, Springer Series in Geomechanics and Geoengineering, https://doi.org/10.1007/978-981-13-7127-1_16

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293.15 [K] Material balance pseudo-time[d] Water volume in gas reservoir [108m3] Cumulative water production [104m3] Gas compressibility factor at initial reservoir pressure Gas compressibility factor at currently reservoir pressure Total system compressibility at average reservoir pressure [1/MPa] Gas viscosity at initial reservoir pressure [mPa s] Gas viscosity at average reservoir pressure [mPa s]

1 Introduction At present, the widely used pseudo-time in production analysis is based on pure gas wells; it does not apply to water production gas wells. Because of producing water, pure gas flow in reservoir gradually becomes gaswater flow that greatly reduces gas relative permeability. Gas and water flow together may cause a water-blocking effect which will lead to gas seepage channels blocked and reduce effective porosity of the gas formation [1]. For these above, gas productivity will be decreased greatly. At this time, the inflow performance relationship is totally different with pure gas well, and the relationship between production and bottom hole pressure will no longer be the same with pure gas drive reservoir, but gas-water reservoir which considers not only gas production and pressure changes but also gas well water rate. Then on the basis of gas-water reservoir model, one will acquire the new method for computing pseudo-time for water production gas wells. Nowadays, the main research results on material balance pseudo-time are presented as follows: Based on gas drive reservoir, Blasingame introduced pseudo-time into production analysis [2], from then on, pseudo-time was used in almost all of the production analysis methods. Afterward, N. M. Anisur Rahman revised this method and proposed a pseudo-time computation method for real gas [3]. Then D. M. Anderson and L. Matter developed a method to calculate pseudo-time for transient flow which considered characteristics of different flowing stages [4]. Further, Shahab Gerami et al. proposed a new way for nature fracture gas reservoir [5]. However, all these methods above are normal methods [6], and it has been demonstrated that they are just applied to pure gas wells but not apply to water production gas wells [7]. These methods could not solve problems in production analysis for water production gas wells. In this paper, a new method for computing pseudo-time for water production gas wells is presented. This method is based on gas-water reservoir material balance equation that considers transient water influx, water production rate, and water PVT properties.

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2 Gas-water Reservoir Material Balance Equation According to gas reservoir classification by drive type [8], there are pure gas drive reservoir and water drive gas reservoir. The latter one can be further classified into edge-water reservoir and bottom-water reservoir by connection types of gas and water boundary, they are traditional water drive reservoir. While in this study, it is realized that there is the third type of water drive reservoir which is defined as gas-water reservoir. This kind of reservoir is normally tight gas and has very gentle structure. During the process of hydrocarbon accumulation, its gas-water separation is not completely done and water preserves in formation as isolated lenticel water, gas and water layer overlap in profile. For these reasons, usually, there is no clearly gas and water boundary in gaswater reservoir. So it cannot be classified into either edge-water or bottom-water reservoir; thus, it is the third type of water drive reservoir. There is a typical gas-water reservoir in the northwest of china, the west part of Sulige gas field (Fig. 1).

Fig. 1. Gas-water reservoir stratigraphic section in the west of Sulige gas field: this is the lenticel water isolated by tight dry layer

Comparing with traditional water drive reservoir, gas-water reservoir has much smaller water volume and is hard to happen mass water invasion, its well produced water all comes from the lentical water itself without any surrounding supplement. Therefore, it is realized that the main characteristics of gas-water reservoir are the following three points: • There is no clearly gas and water boundary, gas and water layer overlap in profile. • Most formation water is isolated lenticel water or the water in the bottom of the structure. • The scale of the water is small and the connectivity of the water is poor each other.

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Based on the three points, it is possible to deduce gas-water reservoir material balance equation. When reservoir pressure drop is Dp, the main volume changes of the reservoir are the following four parts:
 • Cumulative gas production and cumulative water production Gp Bg þ Wp Bw ;
 • Expansion volume of gas in the reservoir: GBg  GBgi ; • The volume reduction of pore with that caused  gas   byexpansion of immobile water and reduction of reservoir pore: GBgi

Cw Swi þ cp 1Swi

Dp

• Transient water influx (W(p)); Among them, the last one (W(p)) is associated with bottom hole pressure and working rules of gas well. The variation of transient water influx has three stages. In the early time of production, for the pressure drawdown has not come to gas-water transition zone, the well products without water, W (p) equals zero; after that, pressure drawdown comes to gas-water transition zone, formation water flows to wellbore through high-permeability zone from every direction, gas well begins to product a large number of water, W(p) increases rapidly; at last, when pressure drawdown gradually becomes steady, W(p) maintains a certain level and water production keeps steady or get down slowly. In conclusion, gas-water reservoir material balance equation can be presented as Eq. (1) GBg  GBgi þ GBgi

  Cw Swi þ cp Dp þ WðpÞ ¼ Gp Bg þ Wp Bw 1  Swi

ð1Þ

For a normal pressure reservoir, the equation can be simplified into:  
 pTsc p=z : G 1 ¼ Gp  WðpÞ  Wp Bw pi =zi psc zT

ð2Þ

3 Pseudo-time for Water Production Gas Wells Pseudo-time is an equivalent time which is derived from material balance equation, and it makes analysis modeling more accurate through bringing in pseudo-pressure and considering PVT changes of fluid during production. In addition, pseudo time makes different production manners in constant pressure or production have the same analysis curves [9]. Therefore, gas well production manners will have no interference to rate transient analysis. For these advantages, most of the modern production analysis methods take use of pseudo-time, such as Blasingame, Agarwal-Garder [10], and normalized pressure integral [11]. Based on the gas-water reservoir material balance equation, it is possible to acquire pseudo-time formulation for water production gas wells. Firstly, take the derivative of Eq. (2) with respect to time, one will get Eq. (3), where p=Z is the function of time.

Production Analysis Method Based on Material Balance …

   
 Tsc @ p G @ p  ¼ qg  WðpÞ  Wp Bw pi =Zi @t z psc T @t z   1 @ p Cg ¼ p=z @p z

175

ð3Þ ð4Þ

Then combining with Eq. (4) [12], Eq. (3) becomes qg ¼ Cg

  Tsc p
G @p WðpÞ  Wp Bw  z psc T pi =zi @t l cti ta ¼ i q

Zt 0

q dt  Ct l

ð5Þ

ð6Þ

For gas reservoir, it is known that Cg  Ct, then substituting Eqs. (5) into (6), it follows Eq. (7) ta ¼

 Z p  Tsc lgi cti
G p  dp WðpÞ  Wp Bw qg Psc T pi =Zi pi lg z

ð7Þ

Combining the definition of pseudo-pressure Eq. (8) [13], finally, pseudo-time for water production gas wells is expressed as Eq. (9): Zp Pp ¼ 2 pi

p dp lg z



 Tsc lgi Cti Ppi  Pp G ta ¼  WðpÞ  Wp Bw 2qg pi =zi psc T

ð8Þ

ð9Þ

4 Computation of Transient Water Influx In Eq. (9), the transient water influx changes with formation pressure drawdown and variations of gas product rate. In this paper, water influx will be calculated by the method of production index curves [14]. This method considers that both pure gas drive reservoir and water drive reservoir have the same linear characteristic in initial part of pressure drawdown curves (p⁄Z − Gp), that is because gas production has not been affected by water influx. Afterward, with increasing of water influx, pure gas drive reservoir and water drive reservoir become different. It is realized that the difference (D(p⁄z)) between the extension of the initial line in pressure drawdown curve is obviously caused by water influx (Fig. 2). Based on this theory, one will get the

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Fig. 2. Pressure drawdown curves for pure gas drive reservoir (the red line) and water drive gas reservoir (the blue line)

formulation for calculating volume of transient water influx in gas-water reservoir. There is another expression for gas-water reservoir material balance equation as   p pi 1  Gp =G ¼ z zi 1x

ð10Þ

WðpÞ  Wp Bw G

ð11Þ

where x¼ Or expresses as  p pi
ð1  xÞ ¼ 1  Gp =G z zi

ð12Þ

The corresponding form of material balance equation for gas drive reservoir is Eq. (13)  p pi
¼ 1  Gp =G z zi

ð13Þ

Combining with Eqs. (12) and (13), one gets Dðp=zÞ ¼ x


p z

ð14Þ

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So x ¼ Dðp=zÞ


p z

ð15Þ

Thus, integrating Eqs. (11) and (15), one gets Eq. (16) which is the formulation for calculating transient water influx in gas-water reservoir. W ¼ Wp Bw þ GBgi
Dðp=zÞ
z=p

ð16Þ

This new method makes calculating of transient water influx simplified greatly, it is allowed one to acquire transient water influx only by gas well production data, and there is no more need to evaluate water shape and size through a series of complicated computation. The accuracy of this method is closely associated with production data which is in accordance with production analysis; therefore, errors will have no propagation and growth in the process of calculating transient water influx and the following production analysis.

5 Results Combining Eqs. 2, 9 and 16, it is possible to calculate material balance pseudo-time of water production gas wells and then plot Blasingame type curves for production analysis. More than 50 water production gas wells in Sulige gas field are selected to calculate pseudo-time by use of the normal method and the new method, respectively.

Fig. 3. Production rate versus time for Su#3

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Through a large number of calculations, it is found that the new method obviously reduces production data divergence and fluctuation and improves their fitting rate. Su#3 is a water production gas well which has produced for 679 days, its average water–gas ratio is 2.52 m3/104 m3, and cumulative production is 2000  104 m3. Its production data is very scattered (Fig. 3). The reason is that water production makes relationship of gas production and bottom hole pressure changed and leads to normal method no longer apply to water production gas wells. Therefore, it is necessary to take use of the new method to adapt water production wells. SU#3 Blasingame curves by the new method and normal method are shown in Figs. 4 and 5 and the result is shown in Table 1.

Fig. 4. Blasingame plot by normal method for Su#3

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Fig. 5. Blasingame plot by new method for Su#3

Table 1. Production analysis result for Su#3 Permeability (K) 0.23 mD

Fracture half-length (Xf) 109.6 m

Drainage radius (Re) 497 m

Reserve (G) 4854.5  104 m3

6 Conclusions This study presents the following conclusions: • Gas-water reservoir is the third type of water drive reservoir, this paper states its balance relationship between gas and water and presents material balance equation for it. • Based on gas-water reservoir material balance equation, this paper constructs a new method for computing material balance pseudo-time for water production gas wells. • The new method provides a potent theoretical support for production analysis of water production gas wells and makes water production analysis more accurate.

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References 1. Li X. Oil and gas flow in underground porous media. Bei Jing: Petroleum Industry Press; 2007. 2. Blasingame TA, Lee WJ. Variable rate reservoir limits testing. In: SPE 15028 presented at the Permian Basin Oil and Gas Recovery Conference, Midland, TX; 1986 Mar. 3. Anisur Rahman NM, Mattar L, Zaoral K. A new method for computing pseudo-time for real gas flow using the material balance equation. In: PETOC 2004–182 presented at the Petroleum Society’s 5th Canadian international petroleum conference (55th Annual Technical Meeting), Calgary, Alberta, Canada; 2004 June 8–10. 4. Anderson DM, Matter L. An improved pseudo-time for gas reservoirs with significant transient flow. In: PETOC 2005–114 presented at the petroleum society’s 6th Canadian international petroleum conference (56th Annual Technical Meeting), Calgary, Alberta, Canada; 2005 June 7–9. 5. Gerami S, Pooladi-Darvish M, Hong H. Decline curve analysis for naturally fractured gas reservoirs: a study on the applicability of “pseudo-time” and “material balance pseudo-time”. In: IPTC 11278 presented at the international petroleum technology conference held in Dubai, U.A.E.; 2007 Dec 4–6. 6. Yuan B, Wood DA. Production analysis and performance forecasting for natural gas reservoirs: theory and practice (2011–2015). J Nat Gas Sci Eng. 2015;26:1433–8. 7. IIk D, Jenkins CD, Blasingame TA. Production analysis in unconventional reservoirs— diagnostics, challenges, and methodologies. In: SPE 144376 presented at the SPE North American unconventional gas conference and exhibition held in the woodlands, Texas, USA; 2011 June 14–16. 8. GB/T 26979. The Classification of Natural Gas Pool; 2011. 9. Blasingame TA, Mc Cray TL, Lee WJ. Decline curve analysis for variable pressure drop/variable flowrate systems. In: SPE 21513; 1991. 10. Agarwal RG, Gardner DC, Kleinsteiber SW, Fussell DD. Analyzing well production data using combined-type-curve and decline-curve analysis concepts. In: SPE 49222; 1998. 11. Blasingame TA, Johnston JL, Lee WJ. Type-curve analysis using the pressure integral method. In: SPE 18799-MS; 1989. 12. Cox SA, Sutton RP, Blasingame TA. Errors introduced by multiphase flow correlations on production analysis. In: SPE 102488 presented at the 2006 SPE annual technical conference and exhibition held in San Antonio, Texas, U.S.A; 2006 Sep 24–27. 13. Al-Hussainy R, Ramyey HJ, Crawford PB. The flow of real gases through porous media. JPT. 1966; p. 625–36. 14. Li C. Determination of water influx in gas reservoirs. Xinjiang Petrol Geol. 2003;24(5):430–1.

A Drilling Rate Model for Roller Cone Bit with Experimental Verification 2018 IFEDC Li Wei, Li Bing(&), Sun Wenfeng, Li Siqi, and Zhao Huan Department of Petroleum Engineering, Northeast Petroleum University, Daqing, Heilongjiang, China [email protected]

Abstract. Roller cone bit is one of the main rock-breaking tools in oil and gas well engineering, and its performance could directly affect well drilling speed and cost. The particular structure of roller cone bit and the random breakage in heterogeneity rock make it difficult to study the problem of rock-breaking mechanism of roller cone bit under bottom-hole condition. Although, research on this topic has been carried out and drilling speed models under down hole conditions have been proposed. The research was based on rock intrusion theory and included the condition of bottom-hole pressure. Theoretical analysis shows that during the transient process of strata changing from soft form and mediumhard form to hard form, the drilling rate model is able to explain the influence of various ways of rock breakage on the drilling rate or the rate of penetration (ROP) of roller cone bit. The test results also show that the invasion depth of conical insert and chisel teeth both decreases exponentially with the increase in bit angle and fluid column pressure, where conical insert has greater decreasing rate than chisel teeth. In addition, the present study demonstrates that the intrusive coefficient is essential to quantify the intrusive-resistance capacity of bottom-hole rock. Keywords: Oil and gas well engineering
Drilling rate model bit
Rock-breaking mechanism
Formation pressure


Roller cone

Copyright 2018, Shaanxi Petroleum Society. This paper was prepared for presentation at the 2018 International Field Exploration and Development Conference in Xi’an, China, September 18–20, 2018. This paper was selected for presentation by the IFEDC Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the IFEDC Committee and are subject to correction by the author(s). The material does not necessarily reflect any position of the IFEDC Committee, its members. Papers presented at the Conference are subject to publication review by Professional Committee of Petroleum Engineering of Shaanxi Petroleum Society. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of Shaanxi Petroleum Society are prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of IFEDC. Contact email: [email protected]. © Springer Nature Singapore Pte Ltd. 2020 J. Lin (ed.), Proceedings of the International Field Exploration and Development Conference 2018, Springer Series in Geomechanics and Geoengineering, https://doi.org/10.1007/978-981-13-7127-1_17

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List of Symbols

PP Pm DPw ren reHh r s P h u C / K x Lh m db nb CH CP dc nc Z

Pore pressure Fluid pressure Additional pressure generated by drilling fluid circulation Effective normal principal stress Effective horizontal stress Normal stress Shear stress generated by axial load Axial load Bit angle Angle between sheer failure surface and the horizontal bottom Cohesive force Angle of internal friction Intrusive coefficient of bottom-hole rock Half length of crater, x ¼ h tan u Width of chisel teeth Number of teeth on each cone in contact with rock in bottom at some point Diameter of bit Rotation speed of bit Hydraulic purification coefficient Differential pressure influence coefficient Diameter of cone Rotation speed of cone around the cone axis Number of teeth in outward ring on cone, similarly

1 Introduction Roller cone bit, drag bit, and diamond bit constitute three common categories of bits extensively applied in oil and gas well engineering. Of these three categories, the number of roller cone bit takes up to 80–90% of the total bits being used in China. The drilling speed and cost are directly related to the performance of roller cone bit [1]. The drilling rate or the rate of penetration (ROP) of roller cone bit is influenced by several factors, such as multiple pressure (including overlying formation pressure, horizontal stress, pore pressure, and fluid column pressure), bit structure, and various ways of rock breaking [2–5]. Currently, the common ROP models applied to well drilling include Bingham drilling rate equation, Yangge drilling rate equation, and Armco equation. These drilling rate equations are proposed by analyzing the mechanical and hydraulic parameters. In these equations, the formation drillability coefficient has been included, but the characteristics of rock-breaking mechanism of roller cone bit are not considered [6–10]. This makes the equations unable to analyze effectively the distinction of ROP between different types of insert and between different conditions of formation. In view of the problem mentioned above, a new ROP model of roller cone bit is proposed by

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considering the pressure environment in the deep strata and rock-breaking characteristics of the teeth on roller cone bit. The new ROP model is based on single-tooth intrusion theory, and it lays foundation for real-time analysis of ROP of roller cone bit.

2 Bottom-Hole Force Analysis of Teeth on Roller Cone Bit When roller cone bit crushes rock information and forms borehole, the crustal stress at wall and bottom changes accordingly. Besides the effects of crustal stress and pore pressure PP , the bottom-hole rock is exposed to the fluid pressure Pm in borehole and additional pressure DPw generated by drilling fluid circulation. Assuming equal horizontal stresses in two directions, the effective normal principal stress ren and effective horizontal stress reHh , which act at certain point on the bottom face, can be expressed as: ren ¼ Pm  PP þ DPw

ð1aÞ

reHh ¼ rHh  Pp

ð1bÞ

The process of teeth invading rock on the bottom face with 2h angle under the action of axial load P can be simplified in Fig. 1.

Fig. 1. The force analysis in the process of single-tooth intrusion

By considering the bottom-hole pressure environment with rock shear breakage, the normal stress r and shear stress s generated by axial load P are related through: r¼

P sin u ðre þ ren Þ ðreHh  ren Þ sinðu þ hÞ þ Hh  cos 2u 2h sin h 2 2

ð2aÞ

P sin u ðre  ren Þ cosðu þ hÞ þ Hh sin 2u 2h sin h 2

ð2bÞ

s¼

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3 The Intrusive Coefficient of Teeth According to Mohr-Coulomb criteria, when the bottom-hole rock has shear failure, the condition of rock breakage on blade side satisfies the following equation: s  r tan / ¼ C

ð3Þ

From Eqs. (2a), (2b), and (3), it is possible to obtain pi þ 1 sin u cosðu þ h þ /Þ ðrHh  Pm Þ þ sin h cos / 2 2hi þ 1
 ðrHh þ Pm Þ  Pp tan / ðsin 2u þ cos 2u tan /Þ  2

s  lr ¼

ð4Þ

s  lr is a function of u. s  lr reaches its maximum value when the derivation of Eq. (4) is equal to zero. Now we can get P K

ð5Þ

4C sin h cos /  ðreHh  ren Þ sin 2h þ 2ðreHh þ ren Þ sin h sin / 1  sinðh þ /Þ

ð6Þ

h¼ K¼

It is shown that if the horizontal crustal stress, the pore pressure and the fluid column pressure remain unchanged, the ratio of load and invasion depth of teeth in every forward movement is a constant K, namely the intrusive coefficient of teeth under bottom-hole condition. Equation (5) is the intrusive equation at the under-balanced bottom. In addition, if the condition of the environmental effect of under-balanced bottom-hole pressure is removed, then the intrusive equation is under the atmospheric condition. In the case of no axial load, invasion depth, or bit angle, the intrusive coefficient becomes essential to describe the intrusive-resistance capacity of bottomhole rock.

4 The ROP Model of Roller Cone Bit The shapes of teeth on roller bit are mainly conical. To improve its rock-breaking efficiency, several designs including overhanging, axis-shifting, and complex cones have been adopted to enable the teeth to cut into and crush rocks by rotation and shear.

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The shape of teeth on indoor microcone bit is chiseled, so the formed craters can be described by triangular prism. According to the triangle relation, the volume of crater next to a single tooth is: Zhp V¼

1 tan u 2xLh dh ¼ Lh h2p 2 2

ð7Þ

0

Considering the uneven working face at the bottom during the crushing process and the effect of adjacent teeth, a factor C is introduced to better describe the process. Then, the ROP of microcone bit in unit time is expressed as: vR ¼


 2Cmnb Lh tan u P 2 K pdb2

ð8Þ

With the form of pure rolling motion, the shape of crater is conical. The volume of bottom-hole rock crushed by single insert is: Zhp V¼

1 2 p tan2 u 3 px dh ¼ hp 3 9

ð9Þ

0

Considering the hydraulic purification coefficient CH and differential pressure influence coefficient CP , the ROP equation for roller cone bit with conical insert is expressed as: vR ¼


 CCp CH mnb Z tan2 u P 3 K 45db dc

ð10Þ

Similarly, the ROP equation of roller cone bit with chisel teeth in pure rolling motion is:
 CCp CH mnb Z tan uLh P 2 vR ¼ K 10pdb dc

ð11Þ

If the rock breakage is under the joint action of rolling invasion and sliding shear, then the crater by conical insert invading rocks can be described by triangular prism. The ROP equation is: vR ¼


 CCp CH nb amðm þ 1ÞZLh tan u P 2 K 20pdb dc

ð12Þ

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From the above mentioned, the ROP equations are given by Eqs. (10), (11), and (12) for different motion patterns and different shapes of teeth. The equations take into account the effects of bottom-hole pressure and the teeth structure on ROP.

5 The Model for Indoor Experiments and Result Analysis Xushen Oil Field is a typically deep and hard-drilling block across Daqing Oil Field. Its hard formation and high value of formation drillability significantly reduce the ROP of the whole block. Research has been carried out to analyze the invasion depth and intrusive coefficient of teeth and ROP. The tests include the intrusion generated by microroller cone bit and confining pressure. 5.1

Test by Using Microroller Cone Bit

The experimental device is a rock drillability tester. The microroller cone bit, with a diameter of 31.75 mm, is composed of eight tips of hard alloy with a thickness of 2.5 mm. Sandstone is selected as the sample. The physical and mechanical parameters are as follows: volume density = 2.31 g/cm3, elastic modulus = 1.32  104 MPa, cohesive force = 8.6 MPa, and angle of internal friction = 25°. The size of the sample is determined by specific experimental requirements. Test results are shown in Figs. 2 and 3. The result indicates that the ROP of microroller cone bit represents a linear increase with the increase in rotation speed and shows exponential increase with the increase in axial load. Theoretical calculation Experiment

0.14

vR (mm/s)

0.12 0.10 0.08 0.06 0.04 20

30

40

50

n (rpm)

60

70

80

90

Fig. 2. ROP as a function of rotation speed

5.2

Test in Balanced Pressure

The condition of bottom-hole is represented by rHh ¼ 42 MPa, Pm ¼ 20 MPa The test results of single-tooth intrusion are shown in Figs. 4 and 5. The results show that the invasion depth of both conical insert and chisel teeth experiences exponential decreases with the increase in bit angle, the bluntness of teeth, and the decrease in invasion depth. This is consistent with the known rules. The invasion depth also represents exponential

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Fig. 5. The invasion depth of teeth versus fluid column pressure

decrease with the increase in fluid column pressure in borehole, the increase in rock compaction effect in working face, and the increase in rock hardness. The decreasing rate of conical insert is greater than that of chisel teeth. The invasion of conical insert is deeper than chisel teeth under the same level of fluid column pressure.

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The physical and mechanical parameters of the rock core sample are as follows: volume density = 2.63 g/cm3, elastic modulus = 1.32  104 MPa, compressing strength = 75.39 MPa, cohesive force = 30.06 MPa, angle of internal friction = 31.7°, and three values of bit angle: 10°, 15°, and 20°. With the bit angle equal to 10°, the horizontal stress equal to 25.4 MPa, the fluid column pressure equal to 11.5 Mpa, and the pore pressure equal to 10 MPa, the theoretical curve between the intrusive coefficient and the angle of internal friction can be drawn according to Eqs. (5) and (7). As shown in Fig. 6, the intrusive coefficient decreases exponentially with the increase in angle of internal friction over different values of effective normal stress. The values of intrusive coefficient also change by choosing different values of effective normal stress, and a larger value of effective normal stress corresponds to a larger value of intrusive coefficient. Due to the fact that intrusive coefficient in under-balanced pressure is obviously smaller than that in overbalanced pressure, it is thus easier for teeth to invade and crush bottom-hole rock with the same mechanical parameters.

Fig. 6. The intrusive coefficient versus the angle of internal friction

Fig. 7. ROP as a function of the angle of internal friction

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Fig. 8. The intrusive coefficient as a function of bit angle

Fig. 9. The relation between ROP and bit angle

Figure 7 shows the effect of angle of internal friction on ROP. It can be noted that the ROP increases and reaches a maximum value at the angle of approximately 25° and then it decreases. The ROP in under-balanced pressure is obviously greater than that in over-balanced pressure. In order to analyze the effect of sharpness degree of teeth on intrusive coefficient and ROP, single-tooth intrusion experiment is carried out under the condition of both bottom-hole and NPT, as shown in Figs. 8 and 9, respectively. From the figures, it is evident that the capacity of invading rock becomes weaker and the intrusive coefficient becomes greater with bigger bit angle and blunter teeth. The theoretical and experimental values in Figs. 8 and 9 show that the intrusive coefficient increases exponentially while ROP represents decreases exponentially with the increase in bit angle. The effective normal stress has a significant impact on the intrusive coefficient and ROP.

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6 Conclusions The ROP equation is proposed by different types of teeth on roller cone bit under the bottom-hole condition. Theoretical analysis shows that during the transient process of strata changing from the soft, medium-hard to hard form, the ROP model can explain the ROP of roller cone bit in different ways of rock breakage and under bottom-hole condition. The test result shows that the invasion depth of both conical insert and chisel teeth exhibits exponential decrease with the increase in bit angle. The invasion depth decreases exponentially with the increase in fluid column pressure in borehole. The invasion of conical insert is deeper than that of chisel teeth under the same level of fluid column pressure. The intrusive coefficient, as a significant parameter of the intrusive equation, is essential to describe the intrusive-resistance capacity of bottom-hole rock. The research has been done to analyze the effects of the angle of internal friction and bit angle on the intrusive coefficient and ROP. The result verifies that the main reason for the improvement in ROP by the under-balanced well drilling lies in the reduction in the intrusive coefficient of bottom-hole rock.

References 1. Chen TP, Hu JB. Petroleum Engineering. Beijing: Petroleum Industry Press; 2000. 2. Li SB, Dou TW, Dong DR, et al. Stress state of bottom-hole rocks in underbalanced drilling. Acta Petrolel Sin. 2011;32(2):329–35. 3. Yan T, Li W, Bi XL, et al. A new evaluation method of rock crushing efficiency base on the crushing work ratio. Fractal representation of rock drillability. Acta Petrol Sin. 2009; 30(2): 291–293. 4. Jin Yang. Correlation model of rock strength and formation pore pressure and application of the modle. J Univ Pet Ed Nat Sci. 2001;25(2):1–5. 5. Zheng DS, Feng JP. Mechanism of effect of down hole pressures on rock failure and its applications. Rock Soil Mech. 2011;32(1):205–8. 6. Liu YG, Wang HY. Initial research on rock-breaking mechanism for gas drilling in Xushen Gas Field. Acta Petrolei Sin. 2008;29(5):773–6. 7. Yan T, Li SB. Deep wellbore rock mechanics theory and practice. Petroleum Industry Press, Beijing; 2002. 8. Yan T, Li W, Bi XL, et al. Fractal analysis of energy consumption of rock fragmentation in rotary drilling. Chin J Rock Mechan Eng. 2008;27(2):3649–54. 9. Young FS. Computerized drilling control. JPT. 1969; 483–496. 10. Zhang H, Gao DL. A new method for predicting drillability of un-drilled formation. Acta Petrolel Sin. 2006;27(1):97–100.

Analysis of Inversion Structure and Trap Diversity in a Block of Western Qaidam Basin Wang Guihong1(&), Chen Zhiyong1, Zhou Chuanmin1, Lv Jietang2, Zhang Ming1, and Wang Dianao3 1

Institute of Petroleum Exploration and Development, Beijing, China {wanggh,chenzyqh,zhouchuanmin,zhmlv}@petrochina.com. cn 2 China Geological Environment Monitoring Institute, Beijing, China [email protected] 3 Research School of Earth Sciences, Australian National University, Canberra, Australia [email protected]

Abstract. Western Qaidam basin which was confined by two boundary zones of Eastern Kunlun and Altin zones endured two phases of tectonic movement during the Cenozoic. Complex in depositional fillings and structure deformations hinders the judgment for early Himalayan effective traps, which lead to troubles in choosing for exploration targets. To solve these problems, regional sequence stratigraphy correlations on seismic and logs data were performed. Then, based on core, logs, and cuttings of wells, lithology and sedimentary facies were identified. In the region of non-well, two dimensions (2D) seismic facies interpretation and well-to-seismic integration method were used to depict the sedimentary systems and their distributions on the plane. Two tectonostratigraphies of Early Himalayan cycle with pan-lake facies and late Himalayan cycle with alluvial-braided river facies were, respectively, recognized by the faces variance sharply and basins superimposition characters. And then by backstrip technique in assistance of 2D fault combination, thickness variance, and seismic facies, two kinds of reversion structures can be identified. One is the reversion in fault dip direction of large boundary faults when geotectonic setting varied. Another is the reversion of basement by warping and plastic flow of deep geological structure during later Himalayan movement, and the deposition centers shifted from west to the east parallel to strike-slip faults of East Kunlun Copyright 2018, Shaanxi Petroleum Society. This paper was prepared for presentation at the 2018 International Field Exploration and Development Conference in Xi’an, China, September 18-20, 2018. This paper was selected for presentation by the IFEDC Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the IFEDC Committee and are subject to correction by the author(s). The material does not necessarily reflect any position of the IFEDC Committee, its members. Papers presented at the Conference are subject to publication review by Professional Committee of Petroleum Engineering of Shaanxi Petroleum Society. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of Shaanxi Petroleum Society are prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of IFEDC. Contact email: [email protected]. © Springer Nature Singapore Pte Ltd. 2020 J. Lin (ed.), Proceedings of the International Field Exploration and Development Conference 2018, Springer Series in Geomechanics and Geoengineering, https://doi.org/10.1007/978-981-13-7127-1_19

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Western Qaidam superimposition basin polarity reversal
Basement inversion
Trap diversity


Fault plane

1 Introduction The study area of western Qaidam basin is shown in Fig. 1. There were two boundary zones named Eastern Kunlun and Altyn zones in western Qaidam basin which confined two phases of tectonic movement during the Cenozoic [1]. Two phases of tectonic movement resulted in complex depositional fillings and structure deformations that hindered the judgment for early Himalayan effective traps. So it leads to troubles in choosing for exploration targets. Shallow large folds like Nanyishan anticline have not been accumulated enough while faulted anticlines at depth such as Yuejin-1 and Yuejin-2 have been filling very well. The well-accumulated structures were formed during early Himalayan stage and continued to develop in later period with the character

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of syn-depositional drape anticline. However, Qie 6 located on the Kunbei faulted block seemed similar to these structures in deformation, but was not filled up with oil [2] (Fig. 1). There could be other factors affecting oil migration and filling. Reversed traps which were situated at lower strata but were high at early Himalayan stage discovered on Kunbei faulted blocks. It is necessary to discern which traps were reversed and which were not. Unlike traditional reverse structures which develop along low dip faults [3], two new kinds of inversions, including dip direction inversion or polarity reversal and basement inversion, were developed in western Qaidam basin through late Himalayan movement.

2 New Definition of Early and Later Himalaya in Qaidam Basin and the Significance of Petroleum Geology The Himalayan movement referred to the orogenesis of Himalaya during Cenozoic was put forward and was divided into four periods based on piled-up molasse distributions at the foothill of Himalayan mountains [4]. Afterward, more work about the topic over Tibet plateau, its neighbor, and eastern of China has being investigated by many geologists, and finally, three stages of Himalayan movement have been suggested with first stage from end of Eocene to the start of Oligocene, second stage at the beginning of Miocene, and third stage from Pleistocene to present. And two sections of Himalayan movement were also divided with the beginning of Miocene as interphase [5]. As an interior basin within Tibet plateau, the sedimentary responses of Himalayan movement in Qaidam basin have been discussed in detail obtaining similar conclusion above. Specifically, faulted depression developed in Paleogene, depression appeared in Miocene, and inversion with compression started from Pliocene [6–8]. Inversion basin shaped by the strike-slip tectonics with sedimentation centers migrating from west to east has been emphasized [9]. Based on the logging, seismic data, and geology data, stratigraphy correlations of study area were performed. On seismic profiles, T2’ can be identified by the angular unconformity, parallel unconformity reflectors in contrast to other reflector boundaries representing Himalayan different stages (Figs. 2 and 3). Combining sedimentary cycles, stratigraphy, and sequence boundary of Cenozoic [1, 6, 7, 10, 11], T2’, the parting line of lower and upper Youshashan group, was used as the divided surface of early and later Himalayan movement of Qaidam basin. In other words, T2’ was the dividing line of lower tectonostratigraphy and upper tectonostratigraphy of Cenozoic group of the basin. The migration of deposition center began during later Himalayan period while sedimentary depressions in early Himalayan stage were almost fixed in sedimentary center in western Qaidam, and subsidence center was in northern Qaidam. Early Himalayan basin was incomplete as its boundary tectonostratigraphy was cut off as marginal tectonic belts uplifted, and later Himalayan basin with folding deformation and marginal sediment facies distributed well might be regarded as a completely new basin. The new definition of two basins of Cenozoic can produce new insights about stratigraphic sequence, sedimentary evolution, and structural evolutions. Thereby, the lithological traps of lower tectonostratigraphy could be predicted when paleo-structures were recovered.

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onlap

T0 truncation T1 onlap T2’ unconformity T2 T3

T4 T5 onlap, downlap TR truncation T6

Fig. 2. Strata and tectonic evolution of western Qaidam basin. After referring to [1, 6, 7, 10]

Fig. 3. Interpreted profile of study area (see Fig. 1 for the position)

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3 Comparison of Early and Later Himalayan Basins (1) early Himalayan basin More faults activating at early Himalayan period illustrates that extension tectonics and faulted depressions appeared in Paleogene basin (Figs. 3 and 4). The superposition sites of early Himalayan basin and Jurassic-Cretaceous basin in Northern part of Qaidam basin demonstrated that it was the basement faults reactivation that leads to the significant subsidence in most of the period during early Himalayan movement.

Fig. 4. Architecture of minor graben in a core sample of Gasi depression (E13)

Some ideas about this incomplete basin tectonics may be induced from thickness and facies of early Himalayan tectonostratigraphy (Figs. 5 and 6). First, the general outline of Qaidam basin during this period appeared as a parallelogram with three marginal mountain belts surrounded and a slope break zone parallel to Altyn zone. The east side which was parallel to Altyn fault implies early Himalayan Qaidam basin was mostly controlled by the tectonic impact of Altyn zone. Second, during early Himalayan period sedimentation centers were situated in western Qaidam basin, but the subsidence center was located in northern part between Altyn and south Qilian zone. And this part was the superstition area of early Himalayan basin and Yanshan basin which indicated Altyn and Qilian zone constituted the early Himalayan basin boundary. Third, parts of early Himalayan basin expanding outward to marginal zones implicates that boundary mountains did not rise out of water fully and were with depressions along them. Early Himalayan basin could extend to Kunzhong belt as the southern margin [12]. Early Himalayan basin had a relatively complete sedimentary cycle and basin evolution course. There might be a faulted depression developed at the beginning and then a quite short compression stage at the end of N21. Areas with no inversion or mild deformations had normal faults on the seismic profiles(Fig. 3), and core sample showed minor graben architecture(Fig. 6). Paleogene volcanic rock was found at Altyn

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mountain suggested the extensional tectonic setting [10]. It was possible that the extensional basin of Paleogene developed with the right lateral strike-slip of Altyn belt [13]. The depression at N12 was the sign of shrink and fading of early Himalayan basin. (2) later Himalayan basin Three marginal mountains uplifted rapidly since the start of N22 while basin basement subsided with flexure folding. Up to 5000 m thickness of later Himalayan tectonostratigraphy lied in basin interior which was much larger than in peripheral areas (Fig. 7). Through strike-slip deformation, east Kunlun mountains have been rising from west to east and Altyn mountain began to build which resulted in the basement bulging of western Qaidam basin. Sedimentary centers appeared to be oblate and migrated to east from the beginning of later Himalayan stage [1, 14, 15]. Major deposition centers

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of upper tectonostratigraphy shifted from west to east through N22 to Q which was clearly controlled by strike-slip tectonic setting [9, 15].

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4 Two Kinds of Inversion Structures Adjacent to Altyn zone, basin basement uplifting and sediment strata folding happened during later Himalayan stage. Yingxiongling (Hero ridge) became hills after it reversed from early Himalayan depression. Many large folds lied in northern block of Yingxiongling zone, like Xiaoliangshan, Nanyishan, Jiandingshan, and so on, but for the south of Yingxiongling, the tectonic feature was completely different, which seemed to subside steadily at later Himalayan period [16] (Fig. 1). Western Qaidam basin was an ideal tectonic block to be studied and contrasted for the deformation and structure reversions during Himalayan movement. General structure reversions, positive and negative inversions, occurred along low dip faults with displacement direction of footwall and hanging wall inverted when the geotectonics setting varied. Positive inversion structures like Jiandingshan and Nanyishan have been studied [17, 18]. Two new inversions need to pay more attention in western Qaidam basin. Fault dip direction reversion (polarity reversion) [19] and basement inversion are two vivid structural deformations distributed over this block. Fault dip direction inversion happened when boundary faults turned into compressive strike-slip from stretching high angle faults while boundary mountains uplifted and squeezed into the basin at later Himalayan movement (Fig. 8). Basement inversions occurred where depressions of large thickness strata uplifted, domed, and folded. And basement inversion was controlled by plastic flow and bending of material at depth in the crust. Both mechanisms were subjected to the intensive squeeze and strike-slip tectonics of Tibet at later Himalayan stage [20–24]. Anticlines and some structure traps probably were negative structural units in early Himalayan period. The folds of western Qaidam basin with high structural amplitude at

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Fig. 8. Models for dip direction reverse of Kunbei fault

shallow level, and low structural amplitude at depth could contribute to dip direction reversion of marginal faults, basin shrinks, and basement folding. Upthrusting of boundary faults caused the upper part of strata shrinks much more than lower section such as Nanyishan and Youquanzi anticlines.

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Basement of western Qaidam basin underwent strong inversion of rise vs subsidence. Paleogene depression and sag turned into rise during later Himalayan period, such as structure Qie 4 (Fig. 9). This well was drilled at the early Himalayan sag which was shown on obviously backstripping profiles. Siltstones and shales of E13 and E23 were drilled at Qie 4 which was testified as a dry well. Commercial oil was found on the slope of early Himalayan sag, just west of Qie 4 [2]. After the later Himalayan movement, slope was reversed to lower level and sag center became a positive structure with basement bending and basin compression. This kind of inversion also occurred in other parts of western Qaidam basin like Yingxiongling, Nanyishan, and so on.

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In conclusion, anticlines and doming zones of western Qaidam basin probably were low-lying or deposit depression during early Himalayan period, and present sags might be previous rises or slopes on strong deformed areas. As a result of reverse of marginal faults dip, Qaidam basin turned into shrinking and subsidened with extensive folding, bedding-plane slip, and structural fractures developed very well (Fig. 6). Major faults reactivated and developed, which were favorable for oil migration during early Himalayan stage [25]. Folding became the major patterns at later Himalayan stage, principle faults reactivated as compressive strike-slip faulting which were mostly sealing inhibiting oil flowing up through. Then, the important migration pathways might be the interlaminar fractures, tension cracks and permeable channels.

5 Oil Enrichment of the Area According to the development of paleotectonic and the relationship between the accumulation time of oil, N12 and its lower Cenozoic strata are the primary layers of the oil enrichment. The formation of N22 and formation above only accepted late accumulation since N32, and the time of oil filling is relatively short. The exploration shows the paleotectonic traps or traps having paleotectonic background, lithologic-structures, and lithologic reservoirs are common in the western Qaidam area, such as Hongliuquan, Gasi oil field (Yuejin-1), and so on [2]. The structures located on Kunbei block formed in the early period and were injected with oil mainly prior to the tectonic inversion (Fig. 8). The lithologic reservoirs were developed at the slope of the paleotectonic background like Hongliuquan oil field. It is necessary to recognize basin features prior to inversions and to identify the potential structural and lithologic traps of early Himalayan stage. It is essential to restore the paleo-structure through the study of unconformities and sedimentary compaction and also to integrate with transporting capacity variations of the faults prior to and after the tectonic inversions, which can help to implement and evaluate the exploration targets. Therefore, oil and gas exploration in western Qaidam basin should be carried out considering early Himalayan tectonic effects for slope zones, synclines, and footwall of Kunbei fault and so on would be very promising areas for exploration.

6 Conclusions (1) Two different prototype basins of Cenozoic were recognized which could be separated by sequence boundary T2’. The lower basin, also called early Himalayan basin or lower tectonostratigraphy of Cenozoic, was characterized with more faults and incomplete in shape. Lower tectonostratigraphy composed Paleogene, Miocene, and lower part of N2 whose deposition and subsidence centers were relatively fixed. The upper basin was termed as the later Himalayan basin or upper tectonostratigraphy of Cenozoic. Basement flexure and sedimentary centers migration were the vivid features comparing with early Himalayan basin.

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(2) There were two types of inversion structures in the western Qaidam basin; one is the dip reversal of the fault planes (polarity reversal), the other is the basement inversion. Both were caused by the changes in the direction of regional stress and deep plastic tectonics of the earth. Faulted anticlines, faulted noses, paleo-high, and paleo-clinoforms of early Himalayan stage and compressive anticlines of late Himalayan period constituted hydrocarbon trap diversity of this area. (3) Discerning two types of inversion structures and paleo-traps could contribute to recover the direction and paths of oil migration and enhance the evaluation of favorable targets. Acknowledgements. This research was supported by a grant from PetroChina Company Limited. Qinhai oil field company was appreciated for providing research data for the study. We are grateful to Lingshan Liu and Zhiye Zhang for taking part in groundwork like mapping. The authors also thank Shuichang Zhang, Mengjun Zhao, Rukai Zhu, Aiguo Su, and Dade Ma for stimulating discussions.

References 1. Gu S et al. Qinghai-Tibet, petroleum geology of China. In: Zhai G editor. Petroleum Industry Press; 1987. vol 14, p. 259–79. 2. Fu S. Key controlling factors of reservoir forming and favorable exploration targets in the western Qaidam Basin. Acta Sedimentol Sin. 2010;28(2):373–6. 3. Wang T, Wang G, Zhao Z. Basin inversion structure and petroleum accumulation of China. Mar Orig Petrol Geol. 2001;6(3):27–37. 4. Huang J, Cheng G, Chen B. Preliminary analysis of the tethys himalayan tectonic domain. Acta Geol Sin. 1984;1:1–17. 5. Jia C. The characteristics of intra-continental deformation and hydrocarbon distribution controlled by the Himalayan tectonic movements in China. Earth Sci Front. 2007;14(4): 96–104. 6. Wu G, Ge X, Liu Y, et al. Mesozoic Cenozoic structural evolution in Qaidam Basin and its control on hydrocarbon occurrence. Glob Geol. 2006;25(4):411–7. 7. Xu F, Yin C, Gong Q. Mesozoic-Cenozoic structural evolution in Qaidam Basin and its control over oil and gas, Chin Petrol Explor. 2006; 6: 9–16. 8. Wang Y, Fang X, Gao J, et al. The fault types and the implication of petrolium prospect in the west of the Qaidam Basin. Chin J Geol. 2009;44(3):957–65. 9. Fu S, Ma D, Guo Z, et al. Strike-slip superimposed Qaidam Basin and its control on oil and gas accumulation. NW China Petrol Explor Dev. 2015;42(6):712–22. 10. Xia W, Zhang N, Li Y, et al. Cenozoic Qaidam basin, China: a stronger tectonic inversed, extensional rifted basin. Am Assoc Petrol Geol AAPG Bllutin. 2001;85(4):715–36. 11. Xiao A, Wu L, Li H, et al. Tectonic processes of the Cenozoic Altyn Tagh Fault and its coupling with the Qaidam Basin NW China. Acta Petrol Sin. 2013;29(8):2826–36. 12. Liu C, Zhao H, Zhang C, et al. The important turning period of evolution in the TibetHimalayan tectonic domain. Earth Sci Front. 2009;16(4):1–12. 13. Zheng M, Li M, Cao C, et al. Characteristics of structures of various levels in the Qaidam Cenozoic basin. Acta Geol Sin. 2004;78(1):26–35.

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14. Ni J, Wang J, Zhou L et al. Study on the Tectonic Events of East Kunlun Orogenic Belt and Prototype about West-South Qaidam Basin during Mesozoic and Cenozoic. Geoscience, 2007; 2l(3): 505–17. 15. Reading HG. Characteristics and recognition of strike-slip systems. In: Sedimentation in oblique-slip mobile zones Balance PF, Reading HG editors. Int Ass Sediment Spec Publ. 1980; 4:7–26. 16. Wang G, Li Y, Zhang M, et al. Cenozoic dynamics characteristics of tectonic evolution in Yingxiongling (YL) area in Qaidam basin. Earth Sci Front. 2004;11(4):417–23. 17. Liu Z, Wang P, Liu Y, et al. Features and determination of deformation time in the Nanyishan -Jiandingshan area of Qaidam Basin. J Jilin Univ Earth Sci Ed. 2009;39(5):796– 802. 18. Yu D, Zhang Y, Hou X, et al. Formation and evolution of Nanyishan structure and its control on hydrocarbon accumulation in western Qaidam Basin. Fault-Block Oil Gas Field. 2017;24 (6):740–4. 19. Macdonald DIM. Controls on sedimentation at Convergent Plate Margins. Spec Publs Int Ass Sediment. Frostick LE, Steel RJ, editors. 1993; 20: 225–57. 20. Zeng R, Wu Q, Ding Z. India-Eurasian collision vs. ocean-continent collision. Acta Seismol Sin Engl Ed. 2007;20(1):1–10. 21. Xu Z, L Wang, Qin Z, et al. Indo-Asian collision: tectonic transition from compression to strike slip. Acta Geol Sin. 2016;90(1):1–23. 22. Li H, Yang J, Shi R et al. Identifying strike slip faulted basin and the relationship with the mountains. Chin Sci Bulletin. 2002; 47(1): 63–67(in Chinese with English abstract). 23. Liu Y, Ge X, Ye H et al. Strike-slip model for altyn tagh fault developed since late mesozoic. Acta Geosci Sin. 2001; 22(1): 23–28 (in Chinese with English abstract). 24. Wang G, Tan Y, Chen X et al. Cenozoic tectonic evolution and oil/gas exploration field in Qaidam Basin. Chin Petrol Explor. 2006; 11(1): 80–84 (in Chinese with English abstract). 25. Zhang N, Zhao R, Wang H, et al. The characteristics of the fluid inclusions in the reservoir and hydrocarbon accumulation history for the Qie 6 Well. Bulletin Mineral Petrol Geochem. 2009;28(1):65–70.

Rock Fracture Analysis Method in Drilling Operation Zhaomei Xue(&) College of Electrical Engineering, Xi’an Shiyou University, No. 18 of Electronic Road Two, Yanta District, 710065 Xi’an, Shanxi, China [email protected]

Abstract. In the course of drilling operation, the failure of fracture pressure prediction often leads to accidents such as blowout accident, well leakage accident, well deviation accident, wellbore collapse accident, pipe sticking accident, and so on. For deep well drilling operation, the prediction of fracture pressure is very important to the selection of drilling fluid and the stability of the wellbore. A rock fracture analysis method is presented in this paper, which can be used to improve the safety of drilling operations. Firstly, the prediction model of fracture pressure is established. Secondly, the fracture process of carbonate rocks in east Sichuan area is simulated and analyzed by using RFPA-2D software. Finally, on the basis of the above experiments and analysis, the measures to improve the safety of drilling operation are put forward. This method provides a basis for the selection of crushing mode and the rational combination of crushing parameters in the drilling operation and has a good guiding significance for improving the safety of drilling operation. Keywords: Drilling operation
Rock fracture analysis Rock fracture experiment
Safety measures


RFPA-2D software


Copyright 2018, Shaanxi Petroleum Society. This paper was prepared for presentation at the 2018 International Field Exploration and Development Conference in Xi’an, China, 18–20 September, 2018. This paper was selected for presentation by the IFEDC Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the IFEDC Committee and are subject to correction by the author(s). The material does not necessarily reflect any position of the IFEDC Committee, its members. Papers presented at the Conference are subject to publication review by Professional Committee of Petroleum Engineering of Shaanxi Petroleum Society. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of Shaanxi Petroleum Society is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of IFEDC. Contact email: [email protected]. © Springer Nature Singapore Pte Ltd. 2020 J. Lin (ed.), Proceedings of the International Field Exploration and Development Conference 2018, Springer Series in Geomechanics and Geoengineering, https://doi.org/10.1007/978-981-13-7127-1_20

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1 Introduction In the process of drilling operation, accidents which threaten the safety of drilling operation was easy happened, such as gas blowout accident, well leakage accident, well slope accident, hole collapse accident, pipe sticking accident, and so on. All of these accidents are often associated with the failure to predict rupture pressure. For deep well drilling operation, the prediction of fracture pressure is very important to the selection of drilling fluid and the stability of borehole wall. The key of drilling safety is the selection of drilling fluid and the prediction of fracture pressure, the prediction of formation fracture pressure is inaccurate, which will affect the selection of drilling fluid. If the drilling fluid pressure is too high, it is easy to have a well leakage accident. If the drilling fluid pressure is too low, it is easy to have a blowout accident. These accidents will cause unestimated losses. In the aspects of the stability of the well wall, the greater difference between the maximum principal stress and the minimum principal stress, the more likely an accident will occur. So it is very important to predict and analyze the fracture scale and the degree of fracture of rock in drilling operation.

2 Analysis of Rock Fracture In this paper, the fracture process of carbonate rocks in east Sichuan is analyzed. According to the three dimensional in situ stress model, mechanism of strata fracture and the combination of carbonate formation of low hole, anisotropy and heterogeneity, rock mechanics characteristics and so on, the formation of fracture pressure which is suitable for carbonate section is: pf ¼ aPp þ lb


l P0  aPp þ C1 C2 St 1l

ð1Þ

The first item in Eq. (1) reflects the influence of formation pore pressure on fracture pressure, the second part in Eq. (1) reflects the contribution of vertical skeleton which caused by the combination of overlying strata pressure and formation pore pressure stress to fracture pressure, the third part in Eq. (1) reflects the influence of tensile strength of rock on fracture pressure, and the coefficients in front of the Pp , ðP0  aPp Þ, St reflects the magnitude of their effect on the fracture pressure. In Eq. (1): Pf Pp P0 lb l a St

formation fracture pressure, MPa; formation pore pressure, MPa; overburden pressure, MPa; the non-equilibrium factor of the formation in skeleton stress (dimensionless); rock Poisson ratio; Biot coefficient; rock tensile strength;

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C1 = 1 indicates non-crack resistance formation or porous reservoir, otherwise C1 = 0; C2 = 1 indicates that the fracturing pressure is calculated for fracturing construction. C2 = 0 indicates that the tensile strength of the formation should be neglected in order to prevent the leakage in the drilling from causing by excessive gravity mud.

3 The Prediction Model of Fracture Pressure Now we establish the fracture pressure prediction model: In the drilling process, the underground rock is subjected to the x-direction confining pressure and the y-direction load. In combination with the actual loading method, both the lower boundary and the right boundary are fixed constraints, the upper boundary is fixed and loaded, the left boundary is controlled by the confining pressure variables. Establishing a grid 100  100, an area of 1000  1000ðmm2 Þ, then, control the size of the pressure variable in the x-direction, the fixed y-direction load is 10 MPa and observes the maximum principal stress changes. Because the profile of the model is horizontal, it will be subjected to the confining pressure. Then the increment of confining pressure in X-direction is 0.001 MPa and the initial value is 5 MPa, the maximum principal stress is used to simulating the minimum pressure of fracture. The model is shown in Fig. 1. The rock parameters are shown in Table 1.

Fig. 1. Schematic diagram of the model

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Parameter name Elastic modulus(E/GPa) Homogeneous degree Tensile strength(MPa) Friction angle(°) Passion ratio Permeability coefficient Solid-liquid coupling coefficient Pore pressure coefficient Porosity

Rock 2,6,8 2 50 30 0.25 0.01 0.2 0.5 0.1

4 The Simulation Experiment of the Process of the Rock Burst RFPA software is a rock fracture process analysis system based on elastic mechanics as stress analysis tool, elastic damage theory and modified Coulomb failure criterion as medium deformation and failure analysis module. In this paper, based on the characteristics of oil and gas reservoirs in east Sichuan and related mechanical parameters of carbonate rocks, the rock fracture process is simulated by RFPA-2D software. 4.1

The Characteristics of Oil and Gas Reservoirs in Eastern Sichuan

The rocks in the east of Sichuan are mostly carbonate rocks. It is mainly composed of dolomite and limestone and complicated with stratigraphical structure, these characteristics make it difficult to predict the pressure and accidents such as well leakage and wall collapse often occurred in the course of drilling. 4.2

The Simulation Experiment

The followings apply the RFPA-2D software to simulate the fracture scale, maximum principal stress and acoustic emission of the carbonate rock fracture process in east Sichuan region, the maximum principal stress is approximately equal to the formation fracture pressure. In the six experiments we did, the y-direction load is 10 MPa, in the x-direction, the confining pressure is 5, 10, 15, 20, 25, 30 MPa, and the confining pressure increment is 0.001 MPa. Experimental results: the maximum principal stress of the six experiments is shown in Fig. 2, the acoustic emission is shown in Fig. 3, and the elastic modulus is shown in Fig. 4. The experimental data are shown in Table 2.

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Fig. 2. Maximum principal stress

The maximum principal stress of experiment 6 exceeds the limit stress of rock fracture, macro-damage occurred, sound emission is obvious, and it is very dangerous. When the drilling operation continues, the maximum principal stress reaches 184 MPa, the acoustic emission is obvious, and the rock appears macro-damage. 4.3

The Analysis of Experimental Results

(1) The analysis of maximum principal stress The figure of the maximum principal shows that when load is fixed and the confining pressure is increased, a slight macrofracture occurred near the initial borehole,then the surrounding stress field is changed, and the minor fissures are constantly produced, expanded and formed into fissures. With the increase of

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Fig. 3. Acoustic emission

confining pressure, the macro-damage was formed at the upper right. The above simulation experiment shows that in the process of drilling especially in the process of deep drilling, with the increase of confining pressure, the rock probably experienced three processes: the appearance of microcracks, the expansion of cracks and the appearance of macrocracks, the breaking form of rock is changed from brittle failure to plastic fracture. (2) The analysis of acoustic emission The figure of the acoustic emission shows that when the maximum principal stress reaches a certain value, the microfracture will occur inside the rock, and the strain energy accumulated in the rock mass is released, and the energy is spread out in the form of transient elastic wave. Acoustic emission is caused by the generation

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Fig. 4. Elastic modulus

Table 2. Experimental data table Experiment 1 2 3 4 5

Maximum principal tress (MPa) 21.8 31.0 41.7 72.8 90.6

Measured formation pore pressure (MPa) 30.595 30.595 45.409 66.22 77.57

and development of internal cracks and friction between internal particles. In the initial stage of loading, due to the large porosity of the rock, the loading process is compacted; the acoustic emission generated is serious. With the further loading and increasing stress, the acoustic emission intensifies again until the macrofracture occurs, so experiment 3 can be used as a turning point. After the experiment 3, the rock will have macro-damage, it is very dangerous.

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5 The Conclusion of Experiment The above experiments have shown that the soft rock is continuously compacted, the hole is shrunk and the difference between the minimum stress and the maximum stress is increasing in the continuous process of drilling. When the difference between the minimum stress and the maximum stress of the borehole rock is bigger, the problem such as the collapse of the well and the collapse sticking are more prominent. If the drilling fluid density is too small, some soft rock will produce shear stress and collapse; if the drilling fluid density is too big, it will rupture the bottom layer, and the fracture pressure at the bottom will depend on the stress state on the borehole wall.

6 The Safety Measures for Drilling Operations (1) In the process of going down, if it is found that the wellhead does not return to the mud or the reverse mud is sprayed in the drill pipe, it should stop drilling immediately; open the pump circulates well or draw the eye, until the downhole is normal resume the drill. (2) In the process of pulling out, if it is found that the wellhead drops or the drill pipe is in reverse, the pulling out should be stopped immediately. Open the pump cycle, when the pump pressure is normal, the well is unobstructed, and the pressure inside and outside the pipe is balanced, then the pulling out is resumed. If the recovery cycle is hopeless, the drilling tool is still active; it should be pulled out immediately. Although there is a lot of resistance at this time, the drill rod is still spraying; we cannot wait at all. As long as the safety load of the equipment and drilling tools is within, it should be pulling out as far as possible. (3) After the well collapse, the circulating cuttings cannot be taken out, and the following measures can be adopted: using high yield drilling fluid to keep the annular laminar flow state; using high concentration sand carrying liquid to wash well; enlarging the drill hole to increase the displacement; the high viscous cut drilling fluid is injected into the collapse well before pulling out.

7 Conclusion Rocks show the anisotropy during the fracture process. In the actual drilling process, choosing the right drilling fluid density is very important. The prediction and analysis of the formation pressure and the possible rupture scale provide the basis for the selection of the crushing mode and the reasonable combination of the crushing parameters in the drilling process and also provide a guarantee for the safety and efficiency of the drilling process.

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Acknowledgements. I wish to express my sincere appreciations to those who have made valuable comments for the writing of this paper.

Author Biography Zhaomei Xue (1969–), female, Master of Engineering, associate professor, mainly engaged in teaching and research work on oil and gas safety engineering.

Analysis of the Influence Factors of Casing Damage Based on Data Mining Shujuan Zhang1(&), Xueqing Zhang2, Wenchang Fu1, Jin Zhang3, Liqiu Zhang1, Qinghong Liu1, and Lihong Zhu1 1

The Exploration and Development Research Institute of Daqing Oilfield, Daqing City, Heilongjiang Province, China [email protected] 2 The Planning and Design Institute, The Second Production Plant of Daqing Oilfield, Daqing City, Heilongjiang Province, China 3 Natural Gas Company of Daqing Oilfield Limited Company, Daqing City, Heilongjiang Province, China

Abstract. The prolonged period of waterflooding development on the oilfield has considerably increased the risk of casing damage, which would affect the regular production of wells, decrease the oil production rate as well as increase the costing of productive maintenance. Considering the in-depth analysis of casing damage and the selection of main effecting factors, a targeted countermeasure is needed in order to prevent casing damage. The causing factors of well casing damage include three types: geological (i.e., fault, formation dip, and mudstone interlayer), developmental (i.e., water injection pressure, injection-producing intensity, and volume replacement ratio), and engineering (i.e., cementing quality, material of the casing pipe). Data of influencing factors as described various in type and are big in volume, especially the data of developing dynamic history. The article focuses on the optimization of maincontrolling developing factors and risk prediction of casing damage based on big data analysis technology. To derive the pattern in which exploiting factors affect on casing damage from mass data using big data analysis technology, the first step is to establish the relations between individual influencing factors with their corresponding casing damage rate, therefore identify the main controlling factor; In the second step, casing damage forewarning parameters system is established while the hysteresis phenomenon of the casing damage time is eliminated both by the computation of the correlation coefficient between parameters and casing damage rate. The last step is to establish the casing damage risk prediction model achieved by the application of principal component analysis and support vector machine, which make prediction of casing damage risk in advance feasible and provide the technical support for the prevention and control of casing damage. Keywords: Casing damage machine (SVM)




Risk prediction




Big data

© Springer Nature Singapore Pte Ltd. 2020 J. Lin (ed.), Proceedings of the International Field Exploration and Development Conference 2018, Springer Series in Geomechanics and Geoengineering, https://doi.org/10.1007/978-981-13-7127-1_21




Support vector

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1 Introduction Ever since the year of 2009, 1000 wells casing damage are discovered every year in Daqing oilfield. In some blocks, concentrated casing damage had appeared in the marker bed of member II of the Nenjiang Fm, causing the ratio of start-up well number to producing well number in these blocks to fall below 70%. There is a clearly out-ofbalance for the injection-production system. The results lead to oil production rate dropped sharply [1]. Because of the casing failure, the cost for monitor, maintain, and update has greatly increased. Currently, a new technique is desperately needed to forecast casing damage risk quickly and efficiently according to production abnormalities, so that casing damage risk can be discovered as quick as possible and being dealt with timely, therefore casing damage well number can be reduced. All around the world, casing damage is one of the biggest issues in impeding oilfield development. Experts around the world have done tremendous investigations on the main reason for the frequent occurrence of casing damage. They believe there are many complex factors that contribute to the cause of casing damage, include: geographical structure, the balance between injection and production, the overloading pressure on the oil formation, the overall well cement job quality, and the overall quality of operate execution [2, 3]. Many researchers have developed investigations using geomechanics models as a way to figure out the mechanical theory behind the casing damage therefore being able to predict potential risks of future casing damage [4–6]. But this method is time-consuming, which means that it will have low efficiency when it comes to the monitoring of a large area therefore causing the inability to quickly discover and prevent the risks of casing damage. Currently, big data analysis has been used in a variety of fields around the world, due to the fact that predictions and prevention of casing damage refer to many professional areas, such as geology, development, perforating technology, monitoring technique. So it has very complex data including the structured data of everyday production and unstructured data of injection profile and other graphics. The information amount is huge and the process involved is also super complex. Making big data analysis useful in terms of predicting the trend of casing damage. Different from the normal traditional data analysis, big data analysis is different in three ways: the first is “Maximize the importance of the whole, minimize the importance of singulars”, the second is “Maximize the importance of correlation, minimize the importance of cause and effect”, the third is “Maximize the importance of rate and efficiency, minimize the importance of accuracy”. Big data analysis successfully deals with the problems regarding the difficulty to obtain and analyze qualitative data from casing damage and makes it easier to discover hidden pattern among complex data with high efficiency therefore establishing the foundation for predictions and prevention of casing damage. This paper provides a detailed description of all the process involved in the big data analysis. The first step is to discover the main influencing factors that cause casing damage and design parameter calculation expression. The next step is to find out the relationship between parameter and the casing damage rate and select the ones with the highest degree of correlation and eliminate the hysteresis phenomenon of casing damage time and the correlations between parameters one by one. The last step is to

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establish a forewarning model by using these parameters as a way to analyze the development factors data of the oilfield and predict the potential risks therefore being able to quickly establish prevention methods.

2 Main Influence Factors of Casing Damage Analysis and Parameters Optimization Big data analysis can be summarized in four steps: data collection, standardization and pretreatment, statistics analysis, and excavation [7]. First, data related to casing damage has to be collected. According to the discoveries of researchers in the past, the process of oilfield development has close relationship with the casing damage [8, 9]. These factors can be roughly divided into three groups: geological factor, development factor, and engineering factor. Geological factors are the basic conditions, some geological factors that can potentially increase the risk of casing damage, include dip angle, fault, reservoir development situation, special lithological interface, etc. On the other hand, engineering factors are the casing tube condition, include: the type of casing tube, cement job quality, perforation condition, and operation construction influence. Development factor is the external cause of casing damage and is the most important factor related to casing damage. As a controlled factor, development factor is the most important focus of the investigation. Development factors include: the injectionproduction relationship, formation pressure, water injection pressure, volume replacement ratio, etc. This article introduces the method and the process of development factor analysis as an example. According to analysis, formation pressure, water injection pressure, level and variation of injection-production parameters are the main factors influencing casing damage. 2.1

Formation Pressure Is the Main Development Factor that Causes Casing Damage

Here using differential pressure to represent the difference of current formation pressure and the original formation pressure. According to the curve between annual differential pressure and annual casing damage well number of typical blocks, there is a distinct correlation exists between total pressure difference and casing damage well number. When there are drastic changes of differential pressure or when there is a huge amount of debt, the amount of casing damage well increases. From the time of the significant drop of differential pressure to the significant increase of casing damage wells, there is a time hysteresis. Based on the graph shown below (Fig. 1), casing damage well number increases when the differential pressure is below −0.5 MPa.

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casing damage Wells cumulative percentage (%)

Number of casing damage Wells

differential pressure classification

Fig. 1. Histogram of casing damage wells numbers with differential pressure

2.2

High Water Injection Pressure Is a Main Development Factor that Causes Casing Damage

Based on the collected data, back in the 1980s when the water injection pressure is higher, there are more number of casing damages [10]. And then an upper limit is being set on water injection pressure based on the pressure required to break the formation.

top water injection pressure wells

the number of casing damage wells the number of top water injection pressure wells

the number of casing damage wells

time (year)

Fig. 2. Relation curve between the number of casing damage wells and top water injection pressure wells

The presence of top water injection pressure wells is also another factor that causes the increasing amount of casing damage wells. To have a more thorough understanding regarding the relationship between high water injection pressure and the amount of casing damage wells, a graph is designed regarding the relationship between top water injection pressure wells and the number of casing damage wells (Fig. 2). The graph shows that a distinct correlation exists between water injection pressure and the number of casing damage wells. Also, keeping high-pressure water injection in a period of time and too much pressure fluctuation will also increase the number of casing damage wells.

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The Injection-Production Parameter Is also a Main Development Factor that Affects Casing Damage

Formation pressure is the main development factor that causes casing damage, but not every well is monitored the formation pressure. So the injection-production parameter, the factor that causes formation pressure changed being selected as representative. Based on the data collected, it can be seen that a positive correlation exists between “Annual Water Injection Change”, “Annual Production Quantity Change”, and the “Rate of Annual Casing Damage” [11] (Fig. 3).

3 Casing Damage Forewarning Parameter Optimization 3.1

The Design of Casing Damage Forewarning Parameter

Due to the complexity of the factors of casing damage, a variety of changes of development factors may cause casing damage. The intensity, the magnitude of change, the peripheral difference, and the cumulative change can all cause casing damage. That is why factors regarding the action to deal especially with the effect of intensity, magnitude, the cumulation, the structure, and the hysteresis. Based on the characteristics of the development factors above, 5 category (Formation Pressure, Injected Pressure, Water Injection, Overall Production, Volume Replacement Ratio) and 39 parameters are designed (Tables 1 and 2). 3.2

Correlation Analysis of Development Parameters and Casing Damage Rate

In order to select the more accurate and the most relatable parameters relating to casing damage, the calculation using correlation coefficient to determine the relationship between the parameter and the casing damage rate. For every parameter(X-Axis) and the casing damage rate(Y-Axis). The formula is shown below. cov ðX; YÞ q x; y ¼ qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi pffiffiffiffiffiffiffiffiffiffiffiffi DðXÞ DðYÞ

ð1Þ

In the equation: q x, y represents the correlation coefficient. Covariance: covðX; YÞ ¼ Ef½X  EðXÞ½Y  EðYÞg Variance: DðXÞ ¼ Ef½X  EðXÞ2g D(X) is the standard deviation E is a mathematical expectation of random variables, reflecting the average value of random variables. Correlation coefficient greater than or equal to 0.4 is a medium correlation. Greater than or equal to 0.7 is a strong correlation. Hysteresis had eliminated by calculating the correlation coefficient of different lag years of the two column data, the corresponding

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15 12

rate of annual

9

casing

6

damage 3

0

0

20

40

60

80 100 120 140

Annual water injection change

10 rate of annual

8 6

casing damage

4 2 0

0

20

40

60

Annual production quantity change

20 rate of

16

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8 4 0

0

0.5

1

annual volume replacement ratio Fig. 3. Annual water injection change, annual production quantity change, annual volume replacement ratio relation with the rate of annual casing damage

time of the maximum correlation coefficient can be determined to be the lag time. Then

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Development factor Parameter Formation pressure Average differential pressure Percent of wells with absolute value of differential pressure above 1 MPa Yearly change of differential pressure Change of differential pressure in the past three years Differential pressure between water flooding development wells and EOR wells Average differential pressure between adjacent blocks Water injection Average water injection pressure pressure Percent of wells with pressure within 0.3 MPa under upper limit Pressure fluctuation Percent of wells with abnormal high pressure Percent of wells with abnormal high fluctuations in a year Magnitude of change of water injection pressure in a year

Unit MPa % MPa MPa MPa MPa MPa % MPa % % %

move the parameter column data backward the lag time to obtain new parameter data. Based on the above 1/2 blocks’ parameter has medium or strong correlation with the rate of annual casing damage, 16 Parameters were selected. 3.3

Dealing with Correlation Between Parameter

Due to the fact that relativity does exist between the development parameters, the relativity has to be eliminated using the correlation coefficient before the warning model can be established. Only one among all the parameters with high relativity will be kept. At last, nine parameters be selected which are: average differential pressure, yearly change of differential pressure, change of differential pressure in the past three years, differential pressure between waterflooding development wells and EOR wells, average differential pressure between adjacent blocks, percent of wells with pressure within 0.3 MPa under upper limit, magnitude of yearly change of water injection, magnitude of yearly change in liquid production, volume replacement ratio of waterflooding development wells. It will be difficult to establish a model with too many parameters being present, that is why the number of parameters needs to be reduced with the method of principal component analysis. In this kind of analysis, the parameter groups will be broken into new parameters with no relativity in attempt to have a more general reflection on the collected information. Then nine new parameters will be created with the first three data being kept as the foundation of the casing damage forewarning model.

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Table 2. Development parameters based on injection-production parameter Development factor Water injection rate

Parameter

Injection intensity Standard deviation of injection intensity Magnitude of yearly change of water injection Magnitude of change of water injection in the past three years Percent of wells with annual magnitude of change above 10% Percent of wells with annual magnitude of change above 20% Magnitude of change of water injection in the past year Percent of wells with magnitude of change above 20% in the past year Percent of wells with magnitude of change above 30% in the past year Liquid Production intensity production rate Standard deviation of production intensity Magnitude of yearly change in fluid production Change in liquid production in the past three years Percent of wells with annual production fluctuation above 10% Percent of wells with annual production fluctuation above 20% Magnitude of change of annual production in the past year Percent of wells with production fluctuation above 20% in the past year Percent of wells with production change fluctuation 30% in the past year Volume Absolute difference between the parameter and the desired value replacement ratio Annual change of volume replacement ratio Volume replacement ratio of water flooding development wells Volume replacement ratio of EOR wells Total parameter fluctuation in the past year Total parameter fluctuation in the past year (water drive) Absolute difference between the parameter of water flooding development wells and the EOR wells Absolute difference between the fluctuation of water flooding development wells and the fluctuation of EOR wells in the past year Total parameter fluctuation in the past year (EOR)

Unit m3/d.m m3/d.m % % % % % % % t/d.m t/d.m % % % % % % %

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4 Comprehensive Evaluation on the Casing Damage Forewarning Parameters After the parameters are being selected, a comprehensive evaluation is required for all of the parameters. Data mining method will be selected to establish mathematical model, while the historical data of parameters will be used as samples of evaluation in terms of the prediction of the risk of casing damage in the present year [12]. Due to the fact that casing damage is a complicated problem involving many factors, there is a time delay between the factors and the time when the damage happens, and there is complex internal relationship between factors. Based on the

Table 3. Matching rate of high casing damage rate of the casing damage forewarning model Geology level Total number of samples Matching samples Matching rate

1st 23 16 69.6

2nd 25 17 68

3rd 31 25 80.6

4th 13 8 61.5

5th 2 2 100

Total 94 68 72.3

patterns discovered among the casing damage data flow, the method of support vector machine (SVM) is being used in the overall research of the casing damage risk forecast. SVM is a small sample statistical learning theory based on the principle of structural risk minimization and the concept of VC dimension. The aim is to obtain the global optimal solution under the existing information, not only the optimal value when the sample tends to infinity, but also ingeniously solves the dimension question. The complexity of the algorithm is independent of the sample size and is suitable for solving complex problems of multiple influencing factors. Based on the annual production data of the blocks’ development forewarning parameters, different forewarning model is established based on different degree of geological factors of casing damage potential risk. The main focus of this system is to deal with the group of blocks in the category of “High Risk(Casing rate above 3%)”. The accuracy of the model is approximately 72.3% (Table 3).

5 Conclusions In this paper, the big data analysis method is used to predict the casing damage trend, and the basic data of Daqing Changyuan oilfield is used to establish the prediction model and used in verification and interpretation. 1. There are many factors that cause casing damage. The development factor is the primary focus of the research as it is controllable. While evaluating the primary parameters, the hysteresis has to be eliminated. 2. The method of correlation coefficient and principal component analysis is used to establish the forewarning parameters system of casing damage.

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3. Support vector machine is being used to finalize the casing damage warning model. The model realizes the prediction of block’s casing damage risk which enables high casing damage risk blocks to be detect earlier therefore adjust and control high-risk parameters in advance and prevent casing damage. Acknowledgements. This project was subordinate to China Petroleum and Natural gas co., LTD., a major science and technology projects “Daqing oil and gas sustainable development effective key technology research and application”(2016E-0205), and this work was support by exploration and development research institute of Daqing oilfield, we thank Yanming Pang, Qinglong Du, Qing Li, for their helpful comments, we are grateful to Chunyu Zhao, Xueyan Jiang for their significant technical contributions to this project.

References 1. Fredrich T, Arguello JG. Geomechanical modeling of reservoir compaction, surface subsidence, and casing damage at the Belridge Diatomite Field. SPE. 2. Guo Y, Blanford M, Candella JD. Evaluating the risk of casing failure caused by highdensity perforation: a 3D finite-element-method study of compaction-induced casing deformation in a deepwater reservoir, Gulf of Mexico, SPE. 3. Bozhong H, Zhiliang X. Casing failure mechanisms and protection measures of oil and water wells in Daqing Oilfield. Oil Drill Prod Technol. 1998; 05. 4. Lian Z, Luo Z, Yu H, Bu H, Caixiong, Changping LI, Finite element analysis and control measures on casing failure in sand shale interbeds. Oil Drill Prod Technol. 2016; 38: 887–892. 5. Wu E, T Yan. The fossil layers in Nen2 marker bed of Daqing oilfield cause casing damage mechanism analysis. J Northeast Petrol Univ. 2007;31(2):38–41. 6. Liu H, Liu J, Zhou S, Jin Y. Geological controlling factors of the piece of casing damage in the Nen2 marker bed of Daqing oilfield. Acta Petrol Sin. 2006;27(5):135–8. 7. Du B, Shi Z, Zhu W, Feng C. Integration prevention technique of tubing damage in ShengLi oilfield. Oil Drill Prod Technol. 2004;26(06165):66. 8. Li Z, Song J, Zhou G. Casing damage causes and microscopic mechanism in Sandstone reservoirs. Energy Conserv Petrol Petrochem Ind. 2005;21(8):40–2. 9. Li S, Sun X, Zhao L. Analyse of casing failure and its preventive measure of Gaotaizi fault in Daqing Oilfield. Oil Drill Prod Technol. 2001;23(62–65):84. 10. Liu C, Liu Y, Mingsheng et al. Method and application of regional warninWeng for geohazards in China. Beijing, Geolojical Publishing, 2009; 12. 11. Liu C. Discussion on the causes of casing damage and prevention measures in Pubei 1 fault block. China Petrol Chem Eng Stand Qual. 2012; 32(7): 166–166. 12. Gu R. Research on large data processing technology and system, study for a period. Nanjing University, Internet Publishing; 2017. 13. Yang L, Wang X, Cui Z, Sun S, Chen W. The casing destruction Mechani sm and prevention measures in Jidong Oilfield. Petrol Eng Constr. 2005;31(z1):72–6. 14. Gang Lu. Casing failure mechanism study and control in Gudao Oilfield. Special Oil Gas Reservoir. 2004;11(6):71–3.

Application of Geostatistical Inversion to Thin Reservoir Prediction in the Indonesian Project C. L. Li1, D. M. Li2, and H. Q. Zhu1(&) 1

2

CNPC Research Institute of Petroleum Exploration & Development (RIPED), Beijing, P. R. China {lichunlei,zhuhouqin}@petrochina.com.cn CNPC PetroChina International Companies (Indonesia), Beijing, P. R. China [email protected]

Abstract. Geostatistical inversion method can effectively improve the predictive accuracy of thin reservoir, the application of which in WB&SB oilfield obtained very good effect and the longitudinal resolution reach to 6 ft. Based on Geostatistical inversion, the favourable targets were optimized, laying the foundation for further potential tapping and mitigation of a decline in the well’s yield, and thus enhancing the recovery ratio and overall economic efficiency. Keywords: Thin reservoir Petrophysical analysis




Statistical inversion




Seismic-well tie




1 Introduction The WB/SB oil and gas field is the main oil and gas field in the Jubang block of the Indonesian project, and it is characterized by complex geological conditions. The main producing layer, the LTAF layer, can be divided into two smaller layers, i.e. layers LTAF-A and LTAF-B, which are widely distributed throughout the entire area. Layer LTAF-A is a sand-shale interbed of variable thickness, which is due to the influence of the structural effect of the basement. The central part of the layer is thinner, while the edges are thicker. The minimum thickness is only 1 m. Layer LTAF-B is a Copyright 2018, Shaanxi Petroleum Society. This paper was prepared for presentation at the 2018 International Field Exploration and Development Conference in Xi’an, China, 18–20 September, 2018. This paper was selected for presentation by the IFEDC Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the IFEDC Committee and are subject to correction by the author(s). The material does not necessarily reflect any position of the IFEDC Committee, its members. Papers presented at the Conference are subject to publication review by Professional Committee of Petroleum Engineering of Shaanxi Petroleum Society. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of Shaanxi Petroleum Society is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of IFEDC. Contact email: [email protected]. © Springer Nature Singapore Pte Ltd. 2020 J. Lin (ed.), Proceedings of the International Field Exploration and Development Conference 2018, Springer Series in Geomechanics and Geoengineering, https://doi.org/10.1007/978-981-13-7127-1_22

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conglomerate bed that was formed by the in situ accumulation of debris from the weathered and crushed granite basement. Since this layer is highly radioactive, it is difficult to carry out reservoir prediction. Seismic inversion is one of the main techniques for reservoir prediction. In this study, the Markov Chain Monte Carlo (MCMC) algorithm was used to combine the constrained sparse pulse inversion with a stochastic simulation to conduct a stochastic inversion. Since it integrates seismic facies lithologic data, well log data, probability density functions, and variation functions, the vertical resolution of the reservoir prediction is improved to some extent. The method used is as follows: 1. Fine log-seismic calibration and wavelet estimation. Events with stable sedimentation were selected and finely calibrated by repeatedly comparing the synthetic records and the wave group features of the seismic reflection axis. In this way, the wave group changes of each oil deposit in the target stratum are consistent with the seismic events, which allows for the consistent calibration of the synthetic records throughout the study area. 2. Rock physics analysis. The rock physics analysis aims to characterize the physical properties of the rock units, e.g. the longitudinal wave velocity, shear wave velocity, and density of the sandstone, and the variation of these properties. In general, different rocks units have different physical properties. Since the physical properties of each rock unit are directly related to its seismic characteristics, the well log data can be used to obtain the mineral composition of the reservoir and to estimate the transverse wave of the multi-mineral model. In addition, several well logs can be combined to conduct a petrophysical sensitivity analysis in order to obtain the petrophysical forward analysis results, which can be used in a later geostatistical inversion for the reservoir prediction. Therefore, petrophysics serves as a bridge between the seismic characteristics and the stratigraphic characteristics. Its purpose is to determine the physical characteristics of the various rock units and their corresponding seismic characteristics through petrophysical analysis in order to guide the seismic inversion, to explain the inversion results, and to evaluate the quality of the inversion results. 3. Geostatistical inversion. Based on the characteristics of the thin sandstone and the highly radioactive conglomerate in layer LTAF of the study area, the MCMC algorithm was used to combine the constrained sparse pulse inversion, and the stochastic simulation was used to conduct the stochastic inversion. By integrating the seismic lithologic data, well log data, probability density function, and variation function, a rigorous probability distribution model was defined to predict the reservoir’s location within layer LTAF. Compared with the conventional wave impedance inversion, the geostatistical inversion has gradually been optimized with increasing lithologic and vertical resolution, but a lower multiplicity of solutions, which have effectively solved technical difficulties, e.g. rapid changes in lithology and thin reservoirs, providing a reliable basis for subsequent 3D geological modelling, favourable area evaluation, and well deployment. Using geostatistical inversion, the location of the thin sandstone reservoir in layer LTAF-A and the porous conglomerate reservoir in layer LTAF-B was effectively

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predicted. Based on the tectonic characteristics and dynamic production data, a plan for the deployment of the new wells was developed. In addition, the favourable targets were optimized, laying the foundation for further potential tapping and mitigation of a decline in the well’s yield, and thus enhancing the recovery ratio and overall economic efficiency. Our reservoir prediction results show that the thin sandstone (layer LTAF-A) is mainly located in the western and southern parts of the study area, while the porous conglomerate (layer LTAF-B) is located in the western, southern, and north-eastern parts of the study area. However, since the overall thickness of the stratum in the upper part of the structure is relatively small, the sandstone and porous conglomerate reservoirs are comparatively thin in the upper part of the structure. file.

2 Preprocessing of Well Data Since well log data is inevitably affected by various environmental factors, it is necessary to apply the proper environmental impact corrections to the original well log data before using the well log data for inversion so that it reflects the nature of the strata and its pore fluids as realistic as possible. Since density logging is conducted against the wall of a well, borehole expansion or collapse seriously impacts the density log data, while sonic logging is generally less affected by these occurrences. During analysis of the quality of the well log data, the neutron vs density plot was superimposed over the rock skeleton mineral distribution plate and the density vs sound speed plot was superimposed over the classic lithophysical model boundary plate (Fig. 1) to examine the characteristics of the well log data in the target stratum and to determine whether the sound wave curve and the density curve were abnormal.

Fig. 1. Neutron versus density plot superimposed over the rock skeleton mineral distribution

As shown in Fig. 1, the density curve was seriously distorted and exhibited anomalies, whereas the sound wave curve was of relatively good quality. Due to the serious distortion of the density curve of the target stratum, the sections of the curve

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that were of comparatively good quality and whose lithology and physical properties were similar to those of the section to be corrected were selected as a reference. The multiple regression method was used to correct the abnormal parts of the density curve. The reference curve should have a relatively large measurement depth, not be easily affected by the wellbore environment, and correlate strongly with the target curve (Fig. 2).

Fig. 2. Neutron versus density plots before and after multi-well curve correction

3 Compaction Trend Correction The interval transit time, density, and resistivity of the stratum are related to the depth of the stratum. For normal compaction conditions, the resistivity, density, and Pimpedance value increase linearly in a semi-logarithmic coordinate system as the burial depth increases, while the interval transit time linearly decreases as the burial depth increases. When the target stratum changes rapidly in the horizontal direction and the burial depth of the target stratum varies greatly between different locations, the Pimpedance values are also quite different even in the same stratum with the same lithology. Therefore, to ensure the horizontal consistency of the study, it is necessary to eliminate variations in the P-impedance caused by variations in burial depths. This process is called decompaction. The concrete realization process is as follows. According to the time vs P-impedance plots of multiple wells, a compaction trend line was obtained by fitting the variation of the P-impedance over time (Fig. 3). Then, the P-impedance was subtracted from the compaction trend line to obtain the decompaction P-impedance curve (Fig. 4).

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Fig. 3. Compaction trend line calculated versus P-impedance plots

4 Analysis of Sensitive Parameters The well log data was analysed to investigate the variation of well log data for the target stratum and to explore the petrophysical characteristics of the reservoir by comparing the well logs from multiple wells. According to the mudstone content, the lower limit of the porosity, and interpretation of the well log data obtained by log interpretation, the target reservoir in layer LTAF-A was predicted to be sandstone, and that in layer LTAF-B was predicted to be conglomerate with a porosity greater than 10%. The well logs shown in the lithographic histograms (Figs. 5 and 6) indicate that the natural gamma rays are sensitive to the sandstone in layer LTAF-A, and the longitudinal wave impedance and density are relatively sensitive to porosity and to the dense conglomerate in layer LTAF-B, which can effectively help us distinguish between reservoir and non-reservoir sections.

5 Variation Function The variation function describes the structural and characteristic scales of the horizontal and vertical geological features. In other words, it describes the size and shape of the different lithofacies and their properties throughout the study area. It is a threedimensional function that describes the spatial variability of the different lithofacies.

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Fig. 4. Decompaction P-impedance curve obtained by subtracting P-impedance from the compaction trend line

Through uphole statistics and test analysis, the codomains and fitting parameters in three directions, i.e. the Z, X, and Y, can be obtained (Figs. 7 and 8). 5.1

Lithographic Ratio and Signal-to-Noise Ratio

As it is based on the geology of a specific area, the lithographic ratio is an important soft constraint for the geostatistical inversion, in which allows for the integration of more geological data into the results. Since it is a weighted value of the seismic data, the signal-to-noise ratio (SNR) is based on the evaluation of the quality of the seismic

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Fig. 5. Statistical lithographic histogram of layer LTAF-A

Fig. 6. Statistical lithographic histogram of layer LTAF-B

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Fig. 7. Lithographic variation function of layer LTAF-A

data. The larger the SNR, the greater the proportion of effective seismic signals will be. If the data is relatively poor and the SNR is low, the residual between the longitudinal wave impedance model and the seismic data will be relatively larger, which means a greater number of relatively weak signals will be classified as noise. The parameters used in the geostatistical inversion need to be selected based on the actual geological conditions and objective data evaluation. By using multiple combinatorial tests, the most reasonable combination of parameters can be selected as the final parameters for the inversion. The lithographic ratios are shown in Figs. 9 and 10. The SNR was 9 db.

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Fig. 8. Lithographic variation function of layer LTAF-B

Fig. 9. Statistical lithographic ratio of layer LTAF-A

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Fig. 10. Statistical lithographic ratio of layer LTAF-B

6 Quality Control of the Inversion Results After the inversion was performed, it was necessary to perform a quality control check on the results to ensure that they were reliable. The quality control was conducted by comparing the forward modelling synthetic record and the actual seismic trace and analysing the correlation and SNR between them. Using this process, we verified the reliability of the inversion results (Figs. 11, 12 and 13).

Fig. 11. Comparison of the forward modelling synthetic record (red) and the actual seismic trace (green)

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Fig. 12. Correlation between the forward modelling synthetic record and the actual seismic trace

7 Analysis of the Inversion Results According to the predicted thickness maps of layers LTAF-A and LTAF-B (Figs. 14 and 15), the sandstone is located in the western and southern parts of layer LTAF-A, the porous conglomerate is located in the western, southern, and northeastern parts of layer LTAF-B as well as in the upper part of the structure. However, due to denudation,

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Fig. 13. SNR of the forward modelling synthetic record compared to the actual seismic trace

the strata in the upper part of the structure are generally thinner, resulting in a relatively thin layer of porous conglomerate. The final prediction results were compared with the logging interpretation results, and the error between them is relatively small.

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Fig. 14. Sandstone thickness map of layer LTAF-A

Fig. 15. Porous conglomerate thickness map of layer LTAF-B

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8 Conclusions In this study, a high-resolution quantitative inversion technique based on geostatistics was used to effectively overcome problems in this area, e.g. thin reservoirs, large horizontal variations, strong concealment, and difficulty in identification. This allowed for the high-resolution prediction of thin reservoirs. By comparing our prediction results to the logging interpretation results, we conclude that our reservoir prediction results are highly reliable and provide a basis for favourable area evaluation and well deployment.

The Research on Teeth Invade Bottom-Hole Rock Basing on Unified Strength Theory Li Wei, Zhao Huan(&), Li Siqi, and Ling Xin Department of Petroleum Engineering, Northeast Petroleum University, Daqing, Heilongjiang, China [email protected], {zhaohuan7696,lisiqi448}@163.com, [email protected]

Abstract. In order to understand the rock breaking mechanism of cone bit under complex drilling conditions in the deep strata, the problem of teeth intrusion into rock bottom was studied. Under the condition of bottom-hole pressure, the mechanical process of tooth intrusion was analysed based on the unified strength theory. The bottom-hole rock intrusion equation and the conerod drilling rate equation with uniform strength parameters were established and the intrusive coefficient without the impact of axial load, invasion depth and bit angle was given. The equation considers the impacts of intermediate stress on intrusive coefficient. The results of the equation and Mohr–Coulomb strength theory are identical when b equals 0. Analyse the impact of angle of internal friction, fluid column pressure, pore pressure and bit angle on intrusive coefficient. The results show that with b, angle of internal friction and bit angle, fluid column pressure and pore pressure increasing, the intrusive coefficient increases, increases exponentially, increases linearly and decreases linearly, respectively. Keywords: Rotary drilling
Rock crushing Crushing work ratio
Poor drillability


Fractal dimension


Copyright 2018 Shaanxi Petroleum Society. This paper was prepared for presentation at the 2018 International Field Exploration and Development Conference in Xi’an, China 18–20 September, 2018. This paper was selected for presentation by the IFEDC Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the IFEDC Committee and are subject to correction by the author(s). The material does not necessarily reflect any position of the IFEDC Committee, its members. Papers presented at the Conference are subject to publication review by Professional Committee of Petroleum Engineering of Shaanxi Petroleum Society. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of Shaanxi Petroleum Society is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of IFEDC. Contact email: [email protected]. © Springer Nature Singapore Pte Ltd. 2020 J. Lin (ed.), Proceedings of the International Field Exploration and Development Conference 2018, Springer Series in Geomechanics and Geoengineering, https://doi.org/10.1007/978-981-13-7127-1_23

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1 Introduction The teeth of cone bit impact bottom-hole rock under drill pressure are one of the basic characteristics in its rock breaking mechanism [1, 2]. Physical and mechanical properties of bottom-hole rock change significantly under joint action of overlying formation pressure, horizontal stress, pore pressure, fluid column pressure and so on. The mechanism which the teeth of cone bit invade bottom-hole rock is still not very clear [3, 4]. At present, the research at home and abroad is mainly about its invasive process by single-shear strength theory (Mohr–Coulomb formula) under atmospheric conditions in door, they lack of the analysis under high-pressure conditions in bottom [5–7]. Mohr– Coulomb formula ignored the influence of intermediate principal stress; it is bound to make the calculation results of invasion deep of bottom rock deviate from the actual value. Professor Yu Maohong started to study the strength theory systematically in the 1960s and finally proposed a new unified strength theory [8, 9]. The unified strength theory covers single-shear and double-shear strength theory, forms a set of complete theoretical system and has many successful application examples in domestic and foreign [10–12]. In this paper, based on unified strength theory, study the teeth invade bottom-hole rock problem. The study has important significance to rich mechanical rock breaking theory and to promote the researches on rock breaking mechanism of cone bit under complex drilling conditions in deep formation.

2 The Unified Strength Theory in Form of Mohr–Coulomb 2.1

The Unified Strength Theory

Based on the double-shear unit, Professor Yu Maohong has established a new theory which is suitable for geotechnical material. It is defined as when the influence function reaches a certain limit value, the material begins to be damaged. The influencing function is about two large shear stress and normal stress which act on double-shear cell cube. The expressions in principal stress form of unified strength theory are F ¼ r1  F¼

aðbr2 þ r3 Þ ¼ rt ; 1þb

r1 þ br2  ar3 ¼ rt ; 1þb

r2  r2 

r1 þ ar3 1þa

r1 þ ar3 1þa

ð1aÞ ð1bÞ

where: b is the effect coefficient of intermediate principal shear stress, ais tensile and compressive intensity ratio of rock material and rt is uniaxial tensile strength, MPa. c0 is the cohesive force. u0 is the angle of internal friction. They are strength indexes which are determined by Mohr–Coulomb test. The relationship of a, rt and c0, u0 is as follows.

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a¼

1 þ sin /0 1  sin /0

ð2aÞ

rt ¼

2c0 cos /0 1  sin /0

ð2bÞ

By Eqs. (1) and (2), we can get principal stress expressions which represented by rock strength parameters. br2 þ r3 1 þ sin /0 2c0 cos /0 ¼ ; 1 þ b 1  sin /0 1  sin /0 r1 þ r3 r1  r3  sin /0 r2  2 2

ð3aÞ

r1 þ br2 1 þ sin /0 2c cos /0  r3 ¼ ; 1þb 1  sin /0 1  sin /0 r1 þ r3 r1  r3  sin /0 r2  2 2

ð3bÞ

F ¼ r1 

F¼

2.2

Mohr–Coulomb Form

Introduce the factor m, r2 ¼

m ðr1 þ r3 Þ 2

ð4Þ

From Eqs. (3) and (4), we can get as follows. r1  r3 ¼ ðr1 þ r3 Þ sin /1 þ 2c1 cos /1 ;

m1

ð5aÞ

r1  r3 ¼ ðr1 þ r3 Þ sin /2 þ 2c2 cos /2 ;

m1

ð5bÞ

where bð1  mÞ þ ð2 þ b þ bmÞ sin /0 ; 2 þ b þ b sin /0 2ð1 þ bÞc0 cos /0 c1 ¼ ð2 þ b þ b sin /0 Þ cos /1 bðm  1Þ þ ð2 þ b þ bmÞ sin /0 sin /2 ¼ 2 þ b  b sin /0 2ð1 þ bÞc0 cos /0 c2 ¼ ð2 þ b  b sin /0 Þ cos /1 sin /1 ¼

u1 ; c1 ; u2 ; c2 are unified strength parameters.

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Then get the unified strength theory formula. It is consistent with strength criterion in form. Equation (5) has considered the impact of the middle shear stress on rock strength.

3 The Intrusion Equation in the Process of Teeth Invading Bottom-Hole Rock 3.1

Mechanics Analysis in the Process of Teeth Invading Bottom-Hole Rock

The process of teeth invading rock under drill pressure in drilling engineering can be simplified as Fig. 1. The teeth with 2h angle invades rock under the effect of axial load P and bottom-hole rock is under the effect of horizontal crustal stress rHh , drilling fluid column pressure Pm and pore pressure Pp . Load P on teeth blade surface forms shear force s1 and normal force r1 . When the load increases to a certain critical value, the rock on the side of the blade surface represents a shear failure. The included angle of shear failure surface and bottom surface is u.

Fig. 1. Force analysis of a single tooth invading bottom-hole rock

The normal stress r1 and shear stress s1 which tooth blade surface acts on shear surface of rock are: r1 ¼

Pi þ 1 sin u sinðu þ hÞ 2hi þ 1 sin h

ð6Þ

s1 ¼

Pi þ 1 sin u cosðu þ hÞ 2hi þ 1 sin h

ð7Þ

The normal stress r2 and shear stress s2 which all kinds of pressure in bottom act on shear failure surface of rock are:

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r2 ¼

ðrHh þ Pm Þ ðrHh  Pm Þ  cos 2u  Pp 2 2

ð8Þ

ðrHh  Pm Þ sin 2u 2

ð9Þ

s2 ¼

Then the total normal stress r and the total shear stress s on shear failure surface of bottom-hole rock are:

3.2

r ¼ r1 þ r 2

ð10Þ

s ¼ s1 þ s2

ð11Þ

Intrusion Equation

From Eq. (5), we can get failure condition of rock on blade side is, s  r tan / ¼ C

ð12Þ

where c, u are unified strength parameters of bottom-hole rock on blade side. From Eqs. (10), (11) and (12), we can get, s  lr ¼

pi þ 1 sin u cosðu þ h þ /Þ sin h cos / 2hi þ 1 ðrHh  Pm Þ þ ðsin 2u þ cos 2u tan /Þ  2  ðrHh þ Pm Þ   Pp tan / 2

ð13Þ

s  lr is the function of u. Derive Eq. (13) and let it equal to zero. We can get: u¼

p hþ/  4 2

ð14Þ

s  lr is maximum value now. By analysing Eq. (14), we can know shear failure surface of bottom-hole rock appears on the surface with the dip angle p4  h þ2 u first. When h þ u is less than 90°, the rock can occur shear crushing; When h þ u is greater than 90° , rock is in a state of comprehensive compression, leap forward type intrusion doesn’t occur. From Eqs. (13) and (14), we can get pi þ 1 4C sin h cos /  ðrHh  Pm Þ sin 2h þ ð2rHh þ 2Pm  4Pp Þ sin h sin / K ¼ 1  sinðh þ /Þ hi þ 1 ð15Þ

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It is shown that if the horizontal stress of formation, fluid column pressure and pore pressure are constant, the ratio of load and invasion depth of teeth in every leap forward is a constant K. It is the invasion coefficient in bottom. From Eqs. (5) and (15), we can get: pi þ 1 ¼ Khi þ 1

ð16Þ

where 4c1 sin h cos /1  ðrHh  Pm Þ sin 2h þ ð2rHh þ 2Pm  4Pp Þ sin h sin /1 ; 1  sinðh þ /1 Þ 4c2 sin h cos /2  ðrHh  Pm Þ sin 2h þ ð2rHh þ 2Pm  4Pp Þ sin h sin /2 K¼ ; 1  sinðh þ /2 Þ K¼

m1 m1

Equation (16) is the intrusion equation of teeth invading rock in bottom. It is also the intrusion equation of atmospheric condition if remove the environmental impact of bottom-hole pressure. The invasion coefficient isn’t affected by axial load, invasion depth and other parameters. It is an important constant to describe the intrusion resistance ability of bottom-hole rock

4 Indoor Experiments and Result Analysis 4.1

Experimental Device and Method

The experimental device is ‘mechanical rock breaking simulation and analysis system’ which is developed by ‘efficient rock breaking drilling technology’ laboratory, as shown in Fig. 2. The main functions of device include intrusion crushing experiments with different rate of loading and different shape heads, cutting various alloy teeth experiments with different load and rotation speed and rotary rock breaking experiments with various sizes of drill bits. The range of axial load is 0–30 kN, the range of rotation speed is 0–500 r/min, the stroke of rock breaking tool is 0–400 mm. The size range of rock sample is 0–300 mm  0–300 mm  0–400 mm. There are two kinds of teeth invading experiments. One is under the normal temperature and pressure, the other is under the confining pressure. Teeth are chisel and bit angle is divided into three kinds, they are 10°, 15° and 20°. In oil and gas well engineering, sandstone is common drilling formation, so it is selected as sample lithology. It’s physical and mechanical parameters are as follows. Volume density is 2.54 g/cm3, elastic modulus is 9.8  103 MPa, compressing strength is 72.62 MPa, cohesive force is 8.13 MPa and angle of internal friction is 23°. The testing surface of sample is polished by grinding wheel before the experiment. The size of sample is determined according to the experimental needs (Fig. 3).

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Fig. 2. Mechanical rock breaking simulation and analysis system

Fig. 3. Use chisel teeth in intrusion experiment

4.2

The Experimental Results and Analysis

When bit angle is 10°, horizontal stress is 25.4 MPa, fluid column pressure is 11.5 MPa and pore pressure is 10 MPa. In this condition, draw the theoretical analysis curves of intrusion coefficient and angle of internal friction, as shown in Fig. 4. The intrusion coefficient is increasing with the angle of internal friction exponentially with different b value. Different b value is corresponding to different invasion coefficient. It increases with the increasing of b value. This is because in the unified strength theory,

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different b value represents different strength theories. When b = 0, the strength theory is Mohr–Coulomb. It is in the lower limit of strength theory and the intrusion coefficient is small. When b = 1, the strength theory is double-shear strength theory. It is in the upper limit strength theory and the intrusion coefficient is big. The greater the invasion coefficient is, the greater the difficulty of teeth invading rock is, the greater the invasion resistance strength is. In the same angle of internal friction, the invasion coefficient in bottom with b = 0 is more than it in normal pressure with b = 1. This shows that when the axial load is the same, the invasion depth in bottom is obviously less than it in normal pressure. It means that the pressure environment in bottom-hole will greatly reduce the penetration rate of cone bit.

Fig. 4. Curve between intrusion coefficient and angle of internal friction

In order to further explain the influence of pressure environment in bottom-hole on intrusion coefficient, analyse the relation curve of fluid column pressure, pore pressure and intrusion coefficient, as shown in Figs. 5 and 6. At this time, the bit angle is 10° and the horizontal stress is 25.4 MPa. Figure 5 shows that intrusion coefficient increases and invasion depth decreases with the increasing of fluid column pressure in borehole. This is consistent with the actual drilling conditions. When the fluid column pressure increases, the chip hold down effect of bottom-hole rock is obvious, the strength of rock increases and penetration rate declined obviously. Based on the effective stress principle, skeleton stress will decline with the increase of pore pressure. The reduction of compaction degree of rock will improve the rock breaking efficiency and penetration rate of cone bit. The theoretical analysis and experimental values are both consistent with the fact in Fig. 6. When b = 0, the theoretical intrusion coefficient value is minimum. When b = 1, it is maximum. The experimental values in Figs. 5 and 6 are most close to but slightly higher than the theoretical value of the intrusion coefficient with b = 0.

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Fig. 5. Curve between intrusion coefficient and fluid column pressure

Fig. 6. Curve between intrusion coefficient and pore pressure

In order to analyse the influence of teeth on intrusion coefficient, do a single tooth intrusion experiment respectively in normal temperature and pressure and in bottomhole, as shown in Figs. 7 and 8. The larger the bit angle is, the blunter the teeth are, the weaker the invasion ability is. The theoretical calculation value and experimental value in Figs. 7 and 8 show that the intrusion coefficient of rock increases exponentially with the increase of bit angle. The intrusion coefficient in bottom-hole is significantly greater than it in normal pressure with the same bit angle.

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Fig. 7. Curve between intrusion coefficient and bit angle in door

Fig. 8. Curve between intrusion coefficient and bit angle in bottom-hole

5 Conclusions 1. Based on unified strength theory, establish the intrusion equation of teeth invading bottom-hole rock with parameters of unified strength theory. The equation has considered pressure conditions in bottom-hole and the influence of intermediate shear principal stress on intrusion coefficient. 2. The intrusion coefficient is an important parameter in intrusion equation. It doesn’t affected by axial load, invasion depth and other parameters. It is an important indicator to describe the intrusion resistance ability of bottom-hole rock. 3. Based on the intrusion equation, analyse the influence of angle of internal friction, fluid column pressure, pore pressure and bit angle on the intrusion coefficient.

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4. The comparison of theoretical calculation value and experimental value show that the intrusion coefficient experimental value of sandstone is most close to but slightly higher than the theoretical value of the intrusion coefficient when b = 0. Acknowledgements. This work is supported by Fund project: National Natural Science Foundation of China (51774093)

References 1. Lai H, Zhu C, Li X, et al. Mechanical Rock Fragmentation. Changsha: Central South University Press; 1991. p. 1–15. 2. Xu X, Yu J. Rock Fragmentation. Beijing: China Coal Industry Publishing House, 1984; 108–115. 3. Yan T, Li W, Bi X, et al. Fractal analysis of energy consumption of rock fragmentation in rotary drilling. Chin J Rock Mechan Eng. 2008;27(2):3649–54. 4. Yang J. Correlation model of rock strength and formation pore pressure and application of the modle. J Univ Petrol Ed Nat Sci. 2001; 25(2): 1–5. 5. Liu Y, Wang H. Initial research on rock-breaking mechanism for gas drilling in Xushen Gas Field. Acta Petrol Sin. 2008;29(5):773–6. 6. Zhang D, Feng J. Mechanism of effect of downhole pressures on rock failure and its applications. Rock Soil Mech. 2011;32(1):205–8. 7. Kou S, Zhang Z, Yu J. Rock fracture under indentation. Chin J Rock Mech Eng, 1989; 18 (4): 275–285. 8. Yu M. New system of strength theory. Xi′an: Xi′anJiaotong University Press, 1992. 9. Yu M. Twin shear theory and its application. Beijing: Science Press, 1998. 10. Jiang M, Shen Z. Unified solution to expansion of cylindrical cavity for geomaterials with strain-softening behaviour. Rock Soil Mech. 1996;17(1):1–8. 11. Li H, Liao H, Sheng Q. Study on statistical damage constitutive model of soft rock based on unified strength theory. Chin J Rock Mech Eng. 2006;25(7):1331–6. 12. Ma GW, Yu MH, Iwasaki S, et al. Unified elastoplastic solutionto rotating disc and cylinder. J Struct Eng. 1995;41A:79–85.

Carbon Dioxide Corrosion on Casing Under High-Temperature and High-Pressure Conditions in Deep Wells Jingfu Zhang(&), Shuai Shao, Shuting Wang, Wenhui Xiao, and Ziyang Lin Enhanced Oil and Gas Recovery Key Laboratory, Ministry of Education, Northeast Petroleum University, Daqing 163318, Heilongjiang, China [email protected]

Abstract. In order to explore the corrosion and protection methods of casing used in CO2-riching block deep oil and gas wells, CO2 development wells, CO2 storage wells, we used high-temperature and high-pressure corrosion instrument and SEM to detect the form of corrosion product film and corrosion rate. We analyzed the basic principle of CO2 corrosion on casing steel and the influence of temperature and CO2 partial pressure on corrosion rate. We also established mathematical model for calculation and analysis of corrosion rate. The result shows that the corrosion product layer consists of three layers of films with different microstructures; the temperature and CO2 partial pressure affect the casing corrosion rate by affecting the chemical reaction process and the corrosion product film formation mechanism; the composition of the casing material, temperature, CO2 partial pressure conditions are different, the degree of change in the corrosion rate of the steel is different; when the temperature increases, the corrosion rate of N80 and J55 casings decreases, while the corrosion rate of P110 casing increases; the partial pressure of CO2 increases, and the corrosion rate of steels generally increases; the corrosion resistance of J55 steel in three casing grades is relatively strong, increasing the Cr content in the steel can effectively improve the corrosion resistance of the steel. The above research system reveals the law and mechanism of CO2 corrosion in down-hole casing under high-temperature and high-pressure conditions and establishes a corrosion

Copyright 2018, Shanxi Petroleum Society. This paper was prepared for presentation at the 2018 International Field Exploration and Development Conference in Xi’an, China, 18–20 September, 2018. This paper was selected for presentation by the IFEDC Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the IFEDC Committee and are subject to correction by the author(s). The material does not necessarily reflect any position of the IFEDC Committee, its members. Papers presented at the Conference are subject to publication review by Professional Committee of Petroleum Engineering of Shanxi Petroleum Society. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of Shanxi Petroleum Society is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of IFEDC. Contact email: [email protected]. © Springer Nature Singapore Pte Ltd. 2020 J. Lin (ed.), Proceedings of the International Field Exploration and Development Conference 2018, Springer Series in Geomechanics and Geoengineering, https://doi.org/10.1007/978-981-13-7127-1_24

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J. Zhang et al. rate calculation model suitable for higher temperature and pressure conditions, which provides a basis for reasonable determination of corrosion protection measures. Keywords: CO2
Casing
Corrosion
Corrosion mechanism
Corrosion rate

1 Introduction Under the containing CO2 deep oil or gas wells or CO2 storage wells, the CO2 will cause rapid overall corrosion and severe local corrosion of the casing (tubing) steel in the appropriate conditions of humidity and pressure, causing corrosion cracking or perforation of tubing and casing in oil and gas wells. This greatly reduces the production life of oil and gas wells and cause huge economic losses. With regard to the problem of corrosion of metals by CO2, as early as in 1924, it was reported that CO2 aqueous solution was more corrosive than hydrochloric acid at the same PH. In recent years, with the continuous development of oilfield production technology, hightemperature and high-pressure oil and gas wells, CO2 development wells, and CO2 storage wells have emerged continuously. The corrosion of underground CO2 has been highly valued, and the research on CO2 corrosion of casing or tubing has become increasingly in-depth studies. The effects of temperature, pressure, or other environmental conditions on corrosion, corrosion mechanisms, and some related predictions have yielded substantial research results which play a positive role in solving corrosion problems in specific oil fields [1–9]. However, due to the differences in the formation conditions of various oil fields, the existing research results cannot meet the requirements for specific on-site production and application conditions of certain oil fields. In particular, the corrosion problems of commonly used pipes in oil fields under the conditions of high temperature and high CO2 partial pressure environment are still lacking. So it’s difficult to spread the universal of anti-corrosion technology. Therefore, based on the conditions of formation and formation water characteristics in certain areas of the oilfield, and using the three types of casing pipe commonly used in oil fields as objects, the corrosion mechanism and laws of CO2 on casing steel are systematically studied, and the corrosion of steel materials is evaluated. We also explore the establishment of corrosion rate prediction model under high-temperature and highpressure conditions and provide basis for the targeted formulation of CO2 corrosion prevention measures.

2 Experiment This article uses the HTHP fluid dynamic corrosion meter as the main corrosion equipment. The design pressure of the meter is 25 MPa and the design temperature is 200 °C. The steel sample coupons used in the experiment were taken from the common casing in the oilfield. In this experiment, the samples were grinded to 1000# step by step with sandpaper, and cleaned with acetone, then rinsed with clean water, lastly

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dried with cold air. The samples were insulated each other and installed on a special anti-corrosion sample shelf and placed in an autoclave. Then add the corrosive medium. The corrosive medium is simulated to the oil formation water and its composition is: Cl−1 10 g/L, SO42− 1.2 g/L, HCO3− 0.15 g/L, Mg2+ 1.0 g/L, Ca2+ 6.0 g/L, Na++K+ 100 g/L, Fe2+ 0.12 g/L. Then the high-purity nitrogen was purged for 2 h to remove oxygen, and then the autoclave was sealed, and add in the high-purity CO2, the temperature and pressure rising time was 7 days. Different partial pressures, temperatures, and media flow rates were used in the experiment. After the end of the experiment, the sample shelf was removed and the microstructure of the corrosion product was examined with a scanning electron microscope. We used a 5% hydrochloric acid and the corrosion inhibitor to remove the product. The corrosion product was washed and dried, weighed, and then calculated its’ weightlessness corrosion rate.

3 Corrosion Mechanism of CO2 on Casing Steel and the Morphology of the Product Film The corrosion of steel by CO2 is mainly manifested as electrochemical corrosion. The corrosion process mainly consists of anode reaction and cathode reaction. The anode reaction is an anodizing process of iron, and the cathode reaction mainly includes two reactions, one is non-catalytic hydrogen ion cathode reduction reaction, one is the surface adsorption hydrogen ion catalytic reduction reaction. The total chemical reaction of corrosion can be described as: CO2 þ H2 O þ Fe ! FeCO3 þ H2 "

ð1Þ

The electrochemical analysis results show that the nature of the two cathodic reactions of corrosion is due to the reduction process of HCO3− ionized H+ formed after CO2 dissolution. This shows that since carbonic acid has a relatively high pH, it increases the corrosion rate of iron. On the other hand, after H2CO3 is adsorbed on the metal surface, the undissociated H2CO3 molecule can be directly reduced, and then the atom H combined H2 component with a quick speed. As H+ diffused from the electrolyte solution to the metal surface, it contributed to the formation of H2CO3 in combination with HCO3−. Therefore, the CO2 dissolved into water is more corrosive than the completely ionized acid, such as hydrochloric acid, at the same PH. At the beginning of the corrosion, the surface of the carbon steel forms a Fe (HCO3)2 film which holes a strong binding force and a certain protective effect. But, the following reactions can occur in the film: FeðHCO3 Þ2 þ Fe ! FeCO3 þ H2 "

ð2Þ

The FeCO3 product film gradually formed on the surface of the sample with the prolonged corrosion time. The initially formed fine FeCO3 crystals, and then the FeCO3 crystals began to grow over time, and the crystal grains merge into larger crystals,

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along with a new nucleation formed, eventually producing larger FeCO3 grains that fill the sample table. The resulting product layer consists of three layers of film (Fig. 1), the outermost layer consists of smaller FeCO3 crystals (Fig. 2), and the inner layer of

Fig. 1. Morphology of corrosion product layer containing 3% Cr steel

(a) N80-casing

(b) 3Cr-casing

(c) 13Cr-casing

Fig. 2. Surface morphology of corrosion products on casing steel

FeCO3 crystals are larger, and the crystals in the middle layer are between of them. In terms of interlayer adhesion, the outer two layers loosely bond with the inner layer, and there are many voids at the interface, which are easily scraped off the surface of the product; the corrosion products of the outer layer and the middle layer are loose and thin, the two layers’ combination is also loose; while the inner corrosion product is relatively dense, thicker, and stronger bonding with the substrate, it is difficult to remove it from the surface of the substrate mechanically.

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The corrosive form and corrosion rate of CO2 on the casing steel are closely related to the corrosion product film formed on the metal surface. Scanning electron microscopy (SEM) analysis results show that in the CO2 containing oil and gas field, the formed CO2 corrosion product film is basically the same in the layered characteristics when the casing contained Cr or not, and the corrosion product film can be roughly divided into the outer, middle, and inner (or bottom) sections (Fig. 1). However, the composition of different steel materials, the formation of corrosion products and morphology are different, and the composition and structure of the product film of each layer are also significantly different from the Cr-free casing (Fig. 2). When the matrix material contains Cr, the structure and densification of the corrosion product film will be changed in the product film due to the presence of oxides and carbonates, resulting in the corrosion product film of the Cr-containing steel being more corrosion product than the Cr-free steel. The film is more dense, and with the increasing of Cr content, the degree of film compactness is better. Thus, increasing the content of Cr is beneficial to improving the corrosion resistance of the steel. In addition, the morphology, properties, and corrosion patterns of the corrosion product films are different for different temperature ranges. When the temperature is below 60 °C, there is a small amount of soft and weak adhesion FeCO3 corrosion product film on the surface of steel. The metal surface is smooth and prone to uniform corrosion; when the temperature is around 100 °C, the corrosion product layer is thick and loose, and it is prone to serious average corrosion and local corrosion (deep hole); and when the temperature is above 150 °C, the corrosion products are FeCO3 and Fe3O4 film which is fine, tight, strongly adhesion, protective, and it can effectively inhibit the further development of corrosion.

4 Influence of in-Well Environmental Conditions and Steel Composition on CO2 Corrosion Corrosion of steel by CO2 is mainly achieved through electrochemical and other related chemical reactions, the main environmental factors affecting and controlling the CO2 corrosion behavior are temperature, partial pressure, and agent flow rate. 4.1

Effect of Temperature on Corrosion Rate

Figure 3 shows the variation of the corrosion rate of casing steel N80, J55, and P110 with temperature under different partial pressure conditions when the medium flow velocity is 1.2 m/s. Analysis of Fig. 3 shows that the casing substrate and the CO2 partial pressure conditions are different, while the rules of the casing corrosion rate and rate change with temperature are different. When the partial pressure of CO2 is equal or bigger than 1.5 Mpa, the corrosion rate of casing steel N80, J55, and P110 reaches the maximum value around 60 °C, and then decreases with the increasing temperature; when the partial pressure of CO2 is 0.5 and 0.1 Mpa, the rate of casing steel N80, J55 reaches the maximum value at 80 °C and minimum at 100 °C, while another higher rate point appears near 110 °C. When the partial pressure of CO2 is higher than 0.1 Mpa, the change trend of the

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3 4 2 1

4

3 2 1

4 3

2 1

(1-0.1MPa 2-0.5MPa 3-1.5MPa 4-2.5MPa 5-5.0MPa) Fig. 3. Effect of temperature on the corrosion rate of N80, J55, and P110 casings

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corrosion rate of P110 casing steel is obviously different from that of N80 and J55. When the partial pressure of CO2 is less than or equal to 1.5 Mpa, the corrosion rate of P110 increases with temperature; while the partial pressure is 2.5 and 5 Mpa, the corrosion rate of P110 increases with increasing temperature, reaches the maximum value around 100 ° C and decreases with temperature. The effect of temperature on the corrosion rate of N80, J55, and P110 casing steels varies with the temperature range. A single simple mathematical model cannot be used to describe the trend of the change in the corrosion rate over the entire temperature range within the experimental temperature range(60–130 °C). This is related to the complex electrochemical reactions that CO2 corrosion is affected by many factors, that is, the effect of temperature on corrosion is closely related to the partial pressure of CO2, the composition of steel materials, and the flow rate of the medium. On the other hand, temperature can affect the corrosion rate by affecting the formation and structure of the corrosion product membrane. Research indicates that the CO2 corrosion has 3 temperature ranges: In the lowtemperature area ( T, the right side of Eq. (6) is less than zero, the change of adsorption capacity under isobaric conditions is negatively affected by temperature change and vice verse. The four kinds of shale involved in this paper, all satisfy Δ > T, as shown in Fig. 2; the temperature derivatives are less than zero. Note that the temperature deviation is less than zero, and there is an extreme value. Comparing the Δ value in Table 3, there exists relatively large Δ value, although the temperature derivative curve changes greatly, but it is below the temperature derivative curve of relatively small Δ value. (II) The influence of pressure under constant temperature condition Under isothermal condition, the influence of adsorption capacity on the pressure equals to that Eq. (4) only partial to the pressure. The result is as followed,

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Fig. 2. Temperature deviation of T-1 and R-1 shale

    @V B D ¼ pffiffiffiffiffi T exp bPb1 @P T T M

ð7Þ

The right side of Eq. (7) is always positive, not negative, as shown in Fig. 3. Therefore, under the isothermal condition, the adsorption pressure always has a posi@V  tive influence on the adsorption capacity of coal @P T .

Fig. 3. Pressure deflector of T-1 and R-1 shale

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Note: the pressure deviation is greater than zero, and it is monotonous. Comparing the b value in Table 3, there exists relatively large b value, although the pressure derivative curve changes greatly, but it is below the temperature derivative curve of relatively small b value. (IV) The common influence of temperature and pressure Refer to the common influence of temperature and pressure on the adsorption capacity, Eq. (4) is mathematically total differential. Equation (8) can be obtained as followed:      B D B D D dV ¼ pffiffiffiffiffi T exp bPb1 dP þ pffiffiffiffiffi Pb exp 1 dT T T T M M

ð8Þ

If all the parameters involved in Eqs. (6)–(8) are all known, and the changing amount of temperature and pressure is selected, then partial derivative of adsorption on temperature, partial derivative of adsorption on pressure, and total differential of adsorption capacity on temperature and pressure can be calculated. Equation (5) shows that the influence of pressure still exists when the adsorption capacity is partial to the temperature under constant pressure condition. The influence of pressure on the adsorption capacity does not disappear under constant pressure condition. In the same way, Eq. (8) shows that the influence of temperature still exists when the adsorption capacity is partial to pressure under constant temperature condition. The influence of temperature on the adsorption capacity does not disappear under constant temperature condition. Meanwhile, on the surface adsorption, the variable quantity of adsorption capacity in Eq. (7) is a function of temperature and pressure. Input the actual temperature gradient and ground pressure gradient obtained from the gas well exploration into the equation, variable quantity of adsorption capacity in Eq. (7) is a function of buried depth (Fig. 4).

Fig. 4. Total differential of T-1 and R-1 shale

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TOC effects TOC means the total organic carbon. In general, the higher TOC value, the larger adsorption amounts. The four kinds of shale rock properties and their corresponding TPAE parameters are listed in Table 5.

Table 5. Four kinds of shale rock properties and their corresponding TPAE parameters T-1 T-2 R-1 R-2

TOC 3.42 1.75 2.26 2.28

RO 2.71 0.94 2.01 1.45

B 0.001487 0.001137 0.0015 0.00166

Δ 722 560 602 607

B 0.36795 0.46293 0.38953 0.3771

From the only four sets of data, the relationship between TOC and RO can be verified on the following figure RO means the thermal maturity of the sample (Fig. 5). If there are good relationship, TOC and RO are no two independent variables. This pair of variables has one independent variable, but another one is dependent. The higher the TOC, the larger the RO value.

Fig. 5. Relationship between TOC and RO

TOC and Δ D is a parameter in the TPAE, which relates to the temperature effects (Fig. 6).

Fig. 6. Relationship between TOC and Δ

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The higher the TOC, the larger the Δ value, the more serious of temperature negative effect. TOC and b. b is a parameter in the TPAE, which relates to the pressure effect (Fig. 7). Larger TOC value indicates smaller b value and less serious of pressure positive effect at the same time.

Fig. 7. Relationship between TOC and b

5 Conclusion TPAE equation can also be used to deal with the series isothermal adsorption experimental data of shale. Within the tested temperature and pressure range, TPAE can simplify each shale’s four test temperature, eight Langmuir’s parameters to four parameters of each shale, and express the quantitative relationship between the three by using the Temperature Pressure Adsorption surface. It can be seen from the relative figure that TPAE surface of the T-1 shale is in good agreement with the adsorption values calculated from the Langmuir volume and the Langmuir pressure. For any kind of shale, if TPAE parameters are known and variable quantity of temperature and pressure is chosen, then partial derivative of adsorption on temperature, partial derivative of adsorption on pressure, and total differential of adsorption capacity on temperature and pressure can be calculated accurately.

References 1. Li WG, Yang SL, Xu J, Dong Q. A new model for shale adsorption gas amount under a certain geologica conditions of temperature and pressure. Nat Gas Geosci. 2013;34(2):301– 11. 2. Yang F, Ning ZF, Hu CP, et al. Characterization of microscopic pore structures in shale reservoirs. Acta Petrol Sin. 2013;34(2):301–11. 3. Wei X, Wei G, Liu HL, et al. Shale reservoir characteristics and isothermal adsorption properties. Nat Gas Ind. 2012;32(1):113–6.

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4. Li WG, Yang SL, Chen F, et al. The sensitivity study of shale gas adsorption and desorption with rising reservoir temperature. J Mineral Petrol. 2012;23(2):115–20. 5. Zhao TY, Ning Z, Zeng Y. Comparative analysis of isothermal adsorption models for shales and coals. Xinjiang Petrol Geol. 2014;35(3):319–23. 6. Langmuir I. The adsorption of gases on plane surfaces of glass, mica and platinum. J Am Chem Soc. 1918;40:1361–403. 7. Brunauer S, Emmett PH, Teller E. Adsorption of gases in multi-molecular layers. J Am Chem Soc. 1938;60:309–19. 8. Zhong L. Adsorption capacity of coals and its affecting factors. Earth Sci J Chin Univ Geosci. 2004;29(3):327–33. 9. Zhang T, Xu H, Li S, et al. The effect of temperature on the adsorbing capability of coal. J Chin Coal Soc. 2009;34(6):802–5. 10. Xue-hai FU, Yong QIN, Biao QUAN, et al. Study of physical and numerical simulations of adsorption methane content on middle-rank coal. Acta Geol Sin. 2008;82(10):1368–71. 11. Zhao L, Qin Y, Wang G, et al. Adsorption behavior of deep coalbed methane under high temperatures and pressures. Geol J Chin Univ. 2013;19(4):648–54. 12. Tang S, Han D. Adsorption and desorption of multi element gas by coal. Coal Sci Technol. 2003;30(1):58–60. 13. Ma D, Zhang S, Lin Y. Isothermal adsorption and desorption experiment of coal and experimental results accuracy fitting. J Chin Coal Soc. 2011;36(3):477–9. 14. Li D. Preparation and characterization of silicon base inorganic membrane for gas separation. USA: University of Cincinnati; 1991. 15. Li D, Hwang ST. Gas separation by silicon based inorganic membrane at high temperature. J Membr Sci. 1992;66:119–27. 16. Li D, Hao J, Zhang X, et al. To establish and calculate the regression sample set for temperature-pressure-adsorption equation—taking Shannxi Jiaoping Cuijiagou Coal as An Example. Unconventional Oil Gas. 2018;5(2):46–9. 17. Dong LI. Mathematical analysis of anthracite’s adsorption under variable temperature and pressure. Chin Coalbed Methane. 2017;14(2):30–5. 18. Wei Y, Zhang X, Cheng S, et al. Study on effects of changes of temperature and pressure on Li adsorption-flow equation. Coal Quality Technol. 2017;1:9–12. 19. Li D, Hao J. Study on methane adsorption variation of coal under variable temperature and pressure-a case study of Xiayukou coal in Hancheng, Shaanxi Province. Unconventional Oil Gas. 2017;4(2):8–12. 20. Li D, Hao J, Qian J. et al. Mathematical analysis of high rank coal’s swing adsorption under variable temperature and pressure-taking YQ4-15 as example. 2017; 14(4), 3–6.

A New Method for Flooded Layer Evaluation by Logging with Strong Heterogeneous in Heavy Oil Reservoirs, K Field, Central Asia Yaping Lin1(&), Zhenhua Guo2, Shanbo Sheng3, Junzhang Zheng1, Man Luo1, and Hongwei Liang1 1

Research Institute of Petroleum Exploration & Development, CNPC, Beijing, China {linyaping-hw,zjz,luoman,L2003468}@petrochina.com.cn 2 Great Wall Drilling Company, Beijing, China [email protected] 3 China National Oil and Gas Exploration and Development Corporation, Beijing, China [email protected]

Abstract. K oil field of Central Asia has several characteristics: sand grain is relatively fine, reservoirs heterogeneous character is obvious, oil viscosity is high, and water flooding is serious. Based on long-term work on well log interpretation for K oil field, an effective method for evaluating water-flooded layers has been found out, and a new reservoir classification chart has been generated, which is applied especially in heterogeneous reservoirs. The key of log interpretation of water-flooded layers is mastering the reduction degree of oil saturation of reservoirs rather than the oil saturation itself, especially to the old oil field with incomplete data. K oil field has three grades of reservoir: Type I is mainly fine sandstone that deposits in distributary channel; Type III is mainly argillaceous sandstone that deposits in mouth bar; Type II is mainly silt that deposits in both distributary channel and mouth bar. Besides, the relationship between resistivity and oil column height of hundreds of wells’ original oil layers has been analyzed, and these oil layers in cross plot of resistivity and oil column can be divided into three groups according to reservoir classification and a sole capillary pressure curve. The resistivity of each group of oil layers has Copyright 2018, Shaanxi Petroleum Society. This paper was prepared for presentation at the 2018 International Field Exploration and Development Conference in Xi’an, China, September 18–20, 2018. This paper was selected for presentation by the IFEDC Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the IFEDC Committee and are subject to correction by the author(s). The material does not necessarily reflect any position of the IFEDC Committee, its members. Papers presented at the Conference are subject to publication review by Professional Committee of Petroleum Engineering of Shaanxi Petroleum Society. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of Shaanxi Petroleum Society are prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of IFEDC. Contact email: [email protected]. © Springer Nature Singapore Pte Ltd. 2020 J. Lin (ed.), Proceedings of the International Field Exploration and Development Conference 2018, Springer Series in Geomechanics and Geoengineering, https://doi.org/10.1007/978-981-13-7127-1_31

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been made multivariate regression. As a result, the resistivity of water-flooded layers could be inversed, and water cut could be estimated. According to the study of well log on flooded zoon, the application in 34 new wells showed that the coincidence rate is 85.3%, and this method can be used to other old oil fields in Central Asia. Keywords: Central Asia
Water-flooded layer
Heterogeneous Reservoir petrophysical classification
Heavy oil




1 Introduction About 88% of China’s total oil and gas production are yielded from oil fields developed by water injection. The oil fields, especial the heavy oil fields operated in Central Asia, face the same problems. Under these new situations, new requirements have been asked for logging evaluation for the water-flooded layers in old oil fields. Previous researchers have done a lot of research work on water-flooded layers. Tian et al. [1] studied changes in reservoir parameters of water-flooded layers and considered that the permeability of coarse-grained glutenite reservoirs after water injection changes significantly, while fine and siltstones (The permeability of mD 27 23–27 500 50–500 3% during the mature stage. Nanpanjiang depression had a higher degree of evolution than Guizhong depression during the late mature-deep evolution phase. Table 1. Statistical table of TOC and Ro mud shale of Devonian–Lower Carboniferous in the Nanpanjiang area Formation Lithology Main distribution area of effective source rock D1

TOC (%) range value/average value 0.8–1.0/0.9

>3

I, II

100–435/200 50–183/100 100–1285/800

0.53 0.4–0.93/0.6 0.25–1.0/0.6

>3 >3 >3

I, II I, II I, II

100–370/250

0.25–0.6/0.4

2–3 I, II

50–166/100

0.58–1.67/0.9 0.46–1.63/1.0 0.25–0.6/0.4

>3 >3 1.3– 3 2–3

D3

Mudstone Nouth of Longlin -Nandan Mudstone Qiubei Mudstone Tianlinbadu mudstone Noth of Ceheng and Leye Mudstone The Western of Wenshan mudstone Tianlinbadu Mudstone Wangmosanglang Mudstone Panxi

C1

Shale

Nandanbaping

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Shale Shale

Well-3 Well 2

93 154

D2

Ro Organic (%) matter type

Thickness (m) range value/average value 100–850/400

3.59– 4.83/3.99 1.6–7.1/4.08 1–4.51/1.76

II, III II, III I, II I, II

2–3 I, II 1.2– I, II 2

The Lower Carboniferous (Fig. 2) developed a deep-water continental high-quality shelf shale with a higher abundance than the Devonian mud shale, which was distributed along both sides of the Yaziluo fault zone. Luodian block, Anlong block, and Guizhong depressions of north of Nanpanjiang depression were the most developed, with thickness ranging from 50 to 200 m. TOC distributed between 0.5 and 4.9% with average organic carbon up to 2.27% was an excellent source rock. The organic type of source rock was mainly I and II1, the degree of evolution was moderate, and Ro was generally between 1 and 3%, which was favorable for the formation of shale gas.

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Fig. 2. Sedimentary facies of Lower Carboniferous in the north of great Nanpanjiang area

2.3

Shale Reservoir Characteristics

Samples of Middle Devonian and Early Carboniferous which collected in the field determined physical properties, the Devonian shale porosity ranges was from 1.0 to 2.8% with an average of 2.05% (Table 2), and the permeability was 0.09–0.63 md with an average of 0.16 md. The early Carboniferous shale porosity was in the range of 0.52–9.11%, with an average of 4.28%, with a large range of changes. The porosity of mudstone was obviously higher, with an average value of 7.15%. But the shale was relatively low, with a permeability of 0.1–1.3 md and an average of 0.45 md. It could be seen that the Carboniferous reservoir had better storage conditions. Table 2. Physical parameter table of mud shale reservoir in great Nanpanjiang area Formation Lithology Porosity (%) range value/average value 2 Mudstone 1.89–2.8/2.4 D2y

D2y D2dl C1y

Mudstone 2.51–2.65/2.58 Shale 1.0–1.8/1.18 Mudstone 3.31–9.11/7.15

C1y

Shale

0.52–2.82/1.41

Permeability (md) range Pore type value/average value 0.1–0.63/0.16 Solution pore, intergranular micropore 0.15–0.20/0.17 Solution micropore 0.12–0.19/0.16 Solution micropore 0.09–1.29/0.56 Micropore— Middlepore, Microcrack 0.13–0.98/0.33 Solution micropore

The results of scanning electron microscope showed (Fig. 3) that pores in Lower Carboniferous were well-developed more than in Middle Devonian, and mesopore

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micropore dominated with microfracture. Middle Devonian was mainly composed of Solution pore and Solution micro pore, with few Intergranular micro pore and localized pyrite microcrystals. Apart from the brittle minerals such as quartz, feldspar, calcite, and pyrite in the shale reservoir, there were also some clay minerals and carbonate, and the content of brittle minerals was relatively high, about 45% (Fig. 4), and the content of carbonate rocks was low. Middle and Upper Devonian mud shales have high brittle mineral content, most of the quartz content was more than 50%, and the carbonate rock content was extremely low. The Well 2 show that the clay content in the upper–middle part of the Early Carboniferous was relatively high, in the bottom, the content of brittle minerals was relatively high, the feldspar and quartz contents were 45%, and the carbonate rock content was 35%. The gas-bearing property was positively correlated with the brittle mineral content, the upper gas-bearing property was relatively poor, and the middle–lower mud shale content was relatively high. It can be seen that the Middle–Upper Devonian and Upper Carboniferous shale in the great Nanpanjiang area had storage conditions.

Fig. 3. Scanning electron microscopy photograph of Middle Devonian and Lower Carboniferous

Fig. 4. Triangular diagram of brittle mineral content in great Nanpanjiang area

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Buried Depth and Preservation Conditions

The great Nanpanjiang area had undergone multi-stage tectonic evolution, and the reformation had been carried out with great strength. The oil and gas reservoirs formed in the early stages may be damaged. Therefore, preservation conditions were one of the main controlling factors for oil and gas exploration decisions in this area [5]. Through analysis of the capping capacity of the Nanpanjiang cap rock, it had been shown that the upper Triassic turbidite sedimentary cap rock generally had a good capping ability. The coverage areas of remnants of mudstone and silty mudstone in the middle Triassic, oil and gas continuing preservation, it was an advantageous area for oil and gas exploration, but the capping ability of the middle and Upper Devonian–Lower Carboniferous caps was poor. Based on the comprehensive evaluation of the fault closure and cover sealing ability, showed the main controlling factors for the preservation conditions in this area were tectonic uplift and fault movement [6]. The seismic line of the Yaziluo fault zone showed that the middle of the fault zone was strongly deformed during the late Yanshan period, but the relative deformation of the Qianzhong uplift and the Qianxinan depression was weak, which was favorable for preservation [7]. The formations in the north of Qianxinan Depression were fully exposed, the faults were not developed, but the preservation conditions were good. The Nanpanjiang depression was also better preserved in the north than in the south. In addition, shale gas of the area with a certain depth of burial and away from high-angle fracture systems was well preserved. The depth of burial depth of Carboniferous shale was moderate, mostly between 2000 and 4000 m. The conditions of roof and floor were good, mostly dense limestone and marl. The red region in Fig. 5 belongs to the low uplift part of the slope belt, fault relatively undeveloped, structural deformation was weak, and preservation conditions were relatively good. Shale gas can be explored in this area.

Fig. 5. Nanpanjiang area seismic section

3 Prediction of Favorable Exploration Targets Shale gas reservoir has source-reservoir-integrated continuous gas reservoir characteristics; therefore, it was necessary to comprehensively analyze the three elements of source rock conditions, reservoir conditions, and preservation conditions [8]. The key

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factor in the existence of shale gas was the characteristics of its source rocks, and the preservation condition was a key factor in whether shale gas can accumulate or affect the scale of accumulation, especially important in the evaluation of marine shale gas zones in southern China. But the final scale and productivity of shale gas reservoirs mainly depend on eight key geological elements, such as organic matter content, effective thickness, maturity, mineral composition, brittleness, pore pressure, matrix permeability, and original natural gas geological reserves. Considering the above-mentioned geological factors, we evaluated that the favorable shale gas zone in the great Nanpanjiang area was the Qianxinan depression and north of Nanpanjiang depression (i.e., Luodian, Anlong, and Wangmo areas) along the Yaziluo fault zone (Fig. 6).

Fig. 6. Favorable exploration targets of shale gas in great Nanpanjiang area

4 Conclusions The structure evolution of Nanpanjiang Basin was divided into four main stages, for, respectively, parcel accretion stage in Jinning–Caledonian period, back-arc rifting basin evolution stage in Hercynian–early Indosinian period, back-arc foreland basin development period in mid- and late Indosinian period, and thrusting, folding, lifting, and transformation in late Indosinian–Himalayan period.

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There are two sets of good-quality shale in the upper Carboniferous and Devonian in the Great Nanpanjiang area. Deep-water shelf facies of shale were developed in Upper–middle Devonian which were distributed near Yaziluo fault zone. The largest thickness area which was mainly located in the northern of Nanpanjiang depression, and Guizhong depression was the favorable exploration potential area. Deep-water shelf facies of shale with good quality were developed in Upper–middle Devonian in Nanpanjiang and Guizhong depression along with the southern and Yaziluo fault zone. Two sets of mud shale were distributed along with both sides of the fault zone. There was a good reservoir condition of mud shale of middle–upper Devonian and upper Carboniferous in the big Nanpanjiang area, but reservoir conditions of the mud shale of upper Carboniferous were well. The areas which were capping bed by the remnants of the Triassic mudstone and silty sand mudstone and well-preserved condition were pointed out favorable exploration targets of shale gas. In the future, shale gas exploration must choose some areas of medium-buried depth and away from fracture system.

References 1. Zhao M, Zhang S, et al. The thermal evolution history and oil and gas generation history of main source rocks in the Nanpanjiang basin. Pet Geol Exp. 2006;28(3):271–275. 2. Liu T, Liu B, et al. Tectonic evolution and hydrocarbon preservation region division in Nanpanjiang basin. Nat Gas Ind. 2001;21(1):18–22. 3. Zhou M. A study on the petroleum system of Nanpanjiang sag. Yunnan Geol. 1999;18 (3):248–65. 4. Ren L, Deng J, Wang X. Analysis of Nandan-Du’an fault along east margin of Nanpanjiang depression. J Kunming Univ Sci Technol. 2008;33(2):1–11. 5. Li M, Jin A, et al. Hydrocarban preservation Conditions and preferential exploration targets in marine sequences of Nanpanjiang depression. J China Univ Min Technol. 2011;40(4): 566–75. 6. Liu L. Study of hydrocarbon preservation conditions in Nanpanjiang depression. Beijing: China University of Petroleum; 2010. p. 1–71. 7. Wang X, Guo T, et al. Characteristics of deep structural segmentation and transformation of the Yaziluo fault zone. Oil Gas Geol. 2013;34(2):220–228. 8. Wang S, Wang S, Man L, et al. Appraisal method and key parameters for screening shale gas play. J Chengdu Univ Technol. 2013;40(6):610–620.

Application and Characterization Technology of Cleat in Medium-Rank Coalbed Methane Liangchao Qu(&), Zhaohui Xia, Lijiang Duan, Ming Zhang, Lingli Liu, and Kening Zheng Asia-Pacific Department, PetroChina Research Institute of Petroleum Exploration & Development, Beijing, China {quliangchao,xiazhui,duanlj,zhmlv,liulingli, zhengkening}@petrochina.com.cn

Abstract. Whether coalbed methane can be produced with high efficiency, permeability is a key parameter. However, cleats are widely distributed in the coalbed and are of great significance for coalbed permeability. Compared with high-rank and low-rank coal, the highlighted characteristic is that cleats are very developed in medium-rank coal; cleat is the endogenetic fracture system in coal, including face cleat and butt cleat, which are the main seepage channels. Cleat characterization contains the study of three cleat elements, which are cleat orientation, cleat density, and cleat permeability. Cleat density and permeability can be used to predict the potential area with high production, while cleat orientation has a great significance for the development strategy, such as optimum drilling survey designing. Through the recognization of coal reservoir in B area of A country, from qualitative description for cleat orientation to quantitative characterization for cleat orientation, density, and permeability, integrating with other parameters of coal reservoir, the potential areas were predicted and four pilot wells were designed and drilled. Testing data show that the relationship between horizontal interval and cleat orientation has a great effect on the production, and when the horizontal interval of surface to inseam (SIS) wells is perpendicular to the face cleat, the maximum production of one well is 27,700 m3/d. Keywords: Medium-rank coal
Cleat density Cleat permeability
Characterization


Cleat orientation


Copyright 2018, Shanxi Petroleum Society. This paper was prepared for presentation at the 2018 International Field Exploration and Development Conference in Xi’an, China, 18–20 September, 2018. This paper was selected for presentation by the IFEDC Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the IFEDC Committee and are subject to correction by the author(s). The material does not necessarily reflect any position of the IFEDC Committee, its members. Papers presented at the Conference are subject to publication review by Professional Committee of Petroleum Engineering of Shaanxi Petroleum Society. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of Shaanxi Petroleum Society is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of IFEDC. Contact email: [email protected]. © Springer Nature Singapore Pte Ltd. 2020 J. Lin (ed.), Proceedings of the International Field Exploration and Development Conference 2018, Springer Series in Geomechanics and Geoengineering, https://doi.org/10.1007/978-981-13-7127-1_33

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1 Introduction Permeability is the measurement for the seepage capacity of coal, it is one of the most important parameters in coalbed methane production, and also it is the most complicated and difficult to determine. Compared with conventional reservoir, the coal seam has such mechanical properties as soft and low elastic modulus, changes in external conditions in drilling, fracturing, and mining which can have a significant impact on permeability. For medium-rank coal, one prominent feature is that the cleats are specially developed [1]; the cleat is the main channel for fluid seepage, which has a great significance for coalbed methane output with high efficiency. The permeability for coal includes two parts: One is from matrix, which permeability is very low, and it can be ignored generally; usually, the permeability of coal is thought as cleat permeability [2]. Currently, there are the following methods to obtain the permeability of coal cleat, laboratory, logging, testing, and numerical simulation. While the cleat system of coal is relatively complicated, cleat should be studied firstly, then to get the cleat permeability. The resources of coalbed methane are abundant in B block of A country, coal belongs to medium rank, the coalbed has such characteristics as low burial depth (100– 600 m), high gas content (11–12 m3/t) and low permeability (0.1–10 mD), and currently, SIS horizontal well type is adopted for developing. The highlighted problem for developing coalbed methane in this block is low permeability, which has an obvious effect on producing with high efficiency. Based on cores, mines, outcrop, special logging, and production data, the qualitative and quantitative characterization of cleat can be conducted, which has great significance for high-yield coal reservoir with efficient development to do the favorable area prediction and optimum placing well direction.

2 Characterization Technology of Coal Cleat In order to characterize coal cleat in detail, firstly using cores, mines, and outcrops data to recognize cleat, then each element of recognized cleat can be characterized, including strike, length, density, filling degree, filling material, and the cleat strike is the main direction for fluid seepage, and cleat density can reflect the development degree of cleat mostly. According to the characterization for cleat elements, combined with production data, cleat permeability can be obtained by using numerical simulation method. Cleat definition Cleat is the internal fracture system in coal, and it develops in coal widely, and of great significance for coalbed methane producing. Cleat is the natural fracture formed by desiccation, coalification, lithification, and tectonic force. Cleat is usually shown in two vertical groups and intersected with coal bedding as vertical of high angle. Normally, in cleats, one group with continuous, extended long is called face cleat, and another group which only developing between two face cleats and discontinuous distribution is called butt cleat. These two group cleats cut the coal into a series of matrix block with rhombus or cube shape (Fig. 1). Usually, cleats are concentrated in bright coal, the

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surface of cleat is smooth, no scratches, more tensile characteristics. Generally, the filling materials in cleat are authigenic, such as clay, calcite, and so on, and there are few coal particles.

Fig. 1. Schematic of cleat in coal

Cleat direction Among the characterization methods for cleat direction, mines, outcrop, cores, and microscope can be used to observe qualitatively, and special logging data can be interpreted quantitatively. ① Cores, mines, and outcrop observation In a relatively tectonic stabilization area, the development degree and direction of cleat in coal can be speculated through outcrop observation, which can observed by means of wellbore directional coring, and then cleat features can be determined according to laboratory analysis (Fig. 2).

Fig. 2. Cleat observation in B block

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② Cleat characterization of special logging Experiments show that the fracture in rock can be characterized by the use of acoustic array scanning imaging logging. In sandstone, there have no obvious fast wave direction, the differentiation of frequency dispersion curves of fast and slow waves is poor, and all of these reflect that acoustic array scanning imaging logging to stress is not sensitive in studying area (Fig. 3a). From the slow frequency dispersion curves and interpretation result of acoustic array scanning imaging logging (Fig. 3b, c), the slow frequency dispersion curves of fast and slow waves are almost coincident, and it is very difficult to reflect the fractures in sandstone.

fast wave direcƟon

Depth=244.297m Slowness

fast wave slow wave

Frequency

(a) Rose map of fast wave

(b) slow frequency dispersion curve

(c) acousƟc array scanning imaging logging interpretaƟon Fig. 3. Analysis of acoustic array scanning imaging logging in sandstone

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While in coal, the differentiation of frequency dispersion curves of fast and slow waves is obvious, acoustic array scanning imaging logging can reflect the anisotropic characteristics in coal, and the direction of fast wave is corresponding to the direction of face cleat (Fig. 4a). From slow frequency dispersion curves of fast and slow wave (Fig. 4b), there are two obvious separations in 370.332 m. In logging interpretation (Fig. 4c), there exists differentiation in about 370 m between fast wave and slow wave. Integrated with all these data, the fracture was interpreted, that is cleat, and the direction is nearly northeast. Depth=370.332m Slowness

fast wave direcƟon

slow wave

fast wave

Frequency

(a) Rose map of fast wave

(b) slow frequency dispersion curve

(c) acousƟc array scanning imaging logging interpretaƟon Fig. 4. Analysis of acoustic array scanning imaging logging in coal

Cleat density Cleat density is referred to the cleat numbers on the coal surface or interface which is intersecting a straight line with a certain length and perpendicular to the extension of the cleat, the length of the line is determined by the cleat amounts, and generally, it is

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5 cm. For cleat genesis, currently it is widely thought of the product from coal metamorphism. However, different stages of metamorphism can give different cleat features [3–5]. The understanding of cleat and coal rank from Andrew [6] indicates that cleat density is gradually increasing from low coal rank, reaching the maximum to medium coal rank, and then decreasing gradually to high coal rank, it is normally distributed. Levine [7] points out, cleat density will increase with the increase of coal rank; when to maximum, it will remain unchanged. It can be seen that in these three coal ranks of low, medium and high, the cleat density of medium coal rank is the largest; that is, the cleat is the most developed. According to the relationship between coal rank and cleat density (Fig. 5), Ro is in 1.0–2.0%, and cleat density is the maximum.

Fig. 5. Relationship between cleat density and Ro

Cleat permeability Cleats in coal provide the main seepage channels for fluid, because of the difference of extending length, fluid seepage capacity for face cleat and butt cleat, face cleats provide the main channel for coalbed methane seepage, butt cleats connect face cleat, provide the secondary channel. Through the analysis of cleat direction and density, in order to determine the fluid seepage contribution of cleat to coalbed methane extraction, cleat permeability is needed to calculate. In actual production, cleat permeability in coal will change with the reservoir temperature, pressure, stress, and so on [8]. Currently, there are such methods to calculate cleat permeability as laboratory testing, log interpretation, and well testing [9]. Laboratory method is mainly based on coal cores and finished in permeability instrument. But the numbers of the permeability data tested in laboratory are limited, and coal rock is brittle and easy cracked; what’s more, the coal cleat system is more developed, and all of these make it more difficult to obtain laboratory samples; on the other hand, the permeability tested in laboratory is single flow, and this cannot reflect the cleat permeability which are two-phase flow. Logging method to calculate permeability uses dual lateral logs, which was suggested by Faivre and Sibbit [10]; in this

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process, many factors were needed to be obtained, and the parameter of vertical width for cleat is very difficult to get; there are a few wells with dual lateral logs; this method is very suitable. There is another method to calculate cleat permeability, which is well testing; the permeability from this method is single flow; it cannot characterize the cleat permeability with two-phase flow rightly while the coalbed methane production. In this study, through the analysis and summary, pointing the shortcomings to calculate coal cleat permeability, adopting numerical simulation technology, simulating gas production, water production and bottom hole pressure, the cleat permeability can be gotten which can reflect the features of coalbed methane production.

3 Application Through the observation of mine outcrops for 41 wells in studying area, and acoustic array scanning imaging logging interpretation of 4 wells, it is deemed that the cleat direction is affected by basin structure, face cleat is perpendicular to basin axis, and butt cleat is parallel to basin axis (Fig. 6).

DirecƟon of max. horizontal stress Cleat direcƟon from imaging logging interpretaƟon Cleat direcƟon from mine outcrop Cleat direcƟon from cores

Fig. 6. Characterization of cleat direction in studying area

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Combined with the previous studying results, the scope of Ro in B block is 1.0– 2.5%, there shows a trend of increasing from northwest to southeast as the burial depth increases (Fig. 7), it is mainly belong to medium rank, and to a certain extent, this shows that the degree of cleat development is generally high in B block.

Fig. 7. Ro contour map of F coal measure in B block

Normally, in a relatively tectonic stabilization area, the cleat direction can be kept unchanged in a long distance, and according to this principle, the cleat direction in coal can be speculated through the outcrop information, while the cleat direction changes great near the fault. Combined with structure characterization in B block, the main directions of cleat in basin are NE-SW, NW-SE, also some regions are EW, and the main reason is the whole B block is affected by the compressive stress of EW direction. The stress can make the cleat open or close, when the present maximum stress is parallel to face cleat, face cleat is open, the permeability is increased, the optimal drilling direction is perpendicular to face cleat; vice versa, when the present maximum stress is perpendicular to face cleat, face cleat is close, and the permeability is decreased; the optimal drilling direction is parallel is butt cleat. Using the CBM Module of Eclipse software from Schlumberger Company to do the numerical simulation, cleat permeability can be gotten. The function in CBM module

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can consider the followiing characteristics for coal reservoir: double medias for coal reservoir; desorption process of coalbed methane on coal matrix surface; coalbed methane diffusion from primary pores into second fractures; Dcrcy flow of gas and water in coal reservoir; permeability changes caused by stress sensitivity in coalbed methane development. Here we selected the typical well for analysis: by adjusting the porosity and permeability to fit water yield; when water yield fitting is good, by adjusting cleat space to fit gas yield; if it is necessary, gas content can be adjusted according to single well controlling reserves; then fine-tune the porosity, permeability and desorption time to achieve the best fit effect (Fig. 8).

Fig. 8. Cleat permeability calculation and fitting relationship

On the basis of determined cleat direction, cleat density in studying area, through establishing the relationship of cleat permeability and burial depth, using 3D geological model, the distribution of coalbed permeability in 3D space can be obtained; combined with the structure, thickness and gas content of coal reservoir, the favorable area can be predicted. Due to the relatively low permeability in studying area, in the prediction of favorable zones, it is necessary to find a relatively high permeability zone in low permeability areas and try to improve the speed of water drainage, gas production, and swept area. Based on this, two favorable areas were predicted, and four pilot wells were deployed (Fig. 9).

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Fig. 9. Favorable area prediction and pilot well deploying map

When designing the trajectory of horizontal section of four pilot wells, make full use of studying results in studying area, and the horizontal section validates the effect of cleat direction on production through production data. The results are followings: when horizontal section is perpendicular to face cleat, the highest yield; when horizontal section is oblique to face cleat, the medium yield; when horizontal section is parallel to face cleat, the lowest yield (Fig. 10).

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Fig. 10. Cleat direction and horizontal section direction

4 Conclusions One of the prominent features for medium-rank coalbed is that cleat is very developed, which is the main seepage for fluid flow. The cleat characterization includes three elements studying; they are cleat density, cleat direction, and cleat permeability, and cleat characterization is of great importance to the exploitation of development strategies such as favorable area prediction and optimal deploying well direction. In the application of B block in A country, from describing the cleat direction qualitatively to characterizing the cleat direction, cleat density, and cleat permeability quantitatively, combined with other parameters of coal reservoir, favorable area was predicted and pilot wells were deployed; when horizontal section is perpendicular to face cleat, it has the highest yield with 27,000 m3/d.

References 1. Close JC. Natural fracture in coal. AAPG. 1993;38:119–32. 2. Fu XH, Qin Y, Zhang WH, et al. Fractal classification and natural classification of coal pore structure based on migration of coalbed methane. Chin Sci Bull. 2005;50(Supp):66–71. 3. Tremain CM, Whitehead NH. Natural fracture (cleat and joint) characteristics and pattern in upper Cretaceous and Tertiary rocks of San Juan basin. Gas Research Institute GRI90/0014, 1990;(I):73–84. 4. Laubach SE, Marrell RA, Olson JE, et al. Characteristics and origins of coal cleat a review. Intern J Coal Geol. 1998;35(1–2):175–207.

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5. Ammosov II, Eremin IV. Fracturing in coal, version translated from Russian. Washington, DC: Office of Technical Services, U.S. Department of Commerce, 1963. 112p. 6. Law BE. The relationship between coal rank and cleat spacing: implications for the prediction of permeability in coal, Presented at the 1993 international coalbed methane symposium, the University of Alabama/Tuscaloosa, 1993;II: 435–441. 7. Levine JR. Model study of the influence of matrix shrinkage on absolute permeability of coal bed reservoirs. Geol Soc Publ. 1996;(199):197–212. 8. Somerton WH, Soylemezoglu IM, Dudley RC. Effect of stress on permeability of coal. Int J Rock Mech Min Sci Geomech Abstr. 1975;12(5):129–45. 9. Puri R, Evanoff JC, Brugler ML. Measurement of coal cleat porosity and relative permeability characteristics. In: Proceedings of 1991 SPE Annual Technical Conference & Exhibition. Houston: Society of Petroleum Engineers of AIME; 1991. 10. Sibbit AM, Faivre O. The dual laterolog response in fractured rocks. In: SPWLA Twentysixth Annual Logging Symposium, 1985. p. 1–12.

Characteristics and Classification Evaluation of Tight Sandstone Caprock: In ManjiaerYingjisu Sag as an Example Wancang Tan1,2(&), Yuanlin Meng1, Qiang Li2, Hongjun Shao2, Liang Zhao2, Lijuan Wang2, Na Jiang2, and Yaguang Li2 1

College of Earth Science, Northeast Petroleum University, Daqing, China [email protected], [email protected] 2 Exploration and Development, Research Institute of Daqing Oilfield Co. Ltd., Daqing, China {tanwancang,liqiang3,shaohongjun,zhaoliang3, wanglijuan,jiangna,liyaguang}@petrochina.com.cn

Abstract. The Manjiaer-Yingjisu sag is located in the eastern Tarim Basin, the exploration target layers are the Silurian Kalpintag and Tataertage formation, and the tight sandstone caprock is developed. The formation and sealing mechanism of tight sandstone caprock is not clear yet. It is urgent to carry out the research on the characteristics of the cover layer. The upper limit of the physical property of the caprock of tight sandstone is determined by the combination of minimum pore throat radius method, bound water saturation method, and empirical statistics. On this basis, the evaluation criteria of the Silurian tight sandstone caprock in the Manjiaer-Yingjisu sag are established with the parameters of displacement pressure, average pore throat radius, porosity–permeability, and calcite content. The main controlling factors for the formation of tight sandstone caprock are sedimentation, diagenesis, and water lock effect. The formation mechanism is that the lithic sandstone with high shale content has a strong compaction and carbonate cementation, and the cementation of the authigenic clay minerals makes the physical property worse. The reticular clay in the pores develops and produces water locks, which greatly reduces the permeability and forms a tight sandstone caprock. Tight sandstone caprock is mainly distributed in the Silurian strata of Mandong-Yingjisu area, the overall continuity is poor, only as a partial cover layer. Research shows that the plane Copyright 2018, Shaanxi Petroleum Society. This paper was prepared for presentation at the 2018 International Field Exploration and Development Conference in Xi’an, China, 18–20 September, 2018. This paper was selected for presentation by the IFEDC Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the IFEDC Committee and are subject to correction by the author(s). The material does not necessarily reflect any position of the IFEDC Committee, its members. Papers presented at the Conference are subject to publication review by Professional Committee of Petroleum Engineering of Shaanxi Petroleum Society. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of Shaanxi Petroleum Society is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of IFEDC. Contact email: [email protected]. © Springer Nature Singapore Pte Ltd. 2020 J. Lin (ed.), Proceedings of the International Field Exploration and Development Conference 2018, Springer Series in Geomechanics and Geoengineering, https://doi.org/10.1007/978-981-13-7127-1_34

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W. Tan et al. distribution of tight sandstone at the bottom of the Silurian Tataertage formation is continuous; the buried depth of the Kalpintag formation sandstone is shallow, with better reservoir properties and better reservoir cap matching. At the same time, structural traps are developed, so the area can be used as an advantageous area for exploration. Keywords: Tarim basin characteristics


Manjiaer-Yingjisu sag
Tight sandstone
Caprock

1 Introduction With the continuous improvement of the global oil and gas exploration and development degree, the reserves and production of high-quality oil and gas fields are decreasing year by year, while the proportion of reserves and production in low permeability and low-grade oil and gas fields is increasing year by year, which has become the main resource for reserve and output increment in the present and future [1–5]. Tight sandstone is a special kind of sandstone, which is composed of relatively compact clastic rocks, mainly including siltstone, fine sandstone, and some middle— coarse sand rock. It is closely related to deep basin gas reservoir, basin central gas reservoir, and continuous accumulation-type gas reservoir. Under certain conditions, the tight sandstone can not only be used as the reservoir of natural gas, but also can be used as the caprock of oil and gas reservoirs. Compared with the conventional reservoir sandstone, it has obvious differences in rock physical and hydromechanical properties [6–8]. Some scholars have carried out a detailed study on the properties of lowpermeability reservoirs and caprock properties of tight sandstone [9–12]. However, the study of the microscopic pore structure of tight sandstone, the formation mechanism of the tight sandstone caprock, and the influence of different water saturation on the tight sandstone are less. At present, the understanding of the concept of tight sandstone is not entirely consistent, and the situation in various regions is not the same, especially a set of unified classification and evaluation criteria for tight sandstone are not formed. In this paper, the characteristics of tight sandstone in Manjiaer-Yingjisu area are systematically analyzed through many experiments, and the evaluation criteria for tight sandstone caprocks in the area are established to provide technical support for future oil and gas exploration and development.

2 The General Situation of Regional Geology The Manjiaer-Yingjisu sag is located in the east of the Tarim Basin, north of the Tadong Uplift, the south of the Peacock River slope, and the north of the Tabei, with an exploration area of 4.3  104 km2. The exploration targets are mainly the Silurian Kalpintag and Tataertage formation, and the reservoir rocks are feldspar lithic sandstone and lithic sandstone. The study area developed two sets of regional caprock, namely Jurassic coal measure strata in Manjiaer-Yingjisu area and Carboniferous mudstone and gypsum rock stratum in Manxi area. The oil and gas reservoirs are

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mainly concentrated in the Lower Silurian. The mudstone thickness is only about 10 m, and the ratio of the thickness of mudstone to the thickness of the stratum is less than 2%. Fine and siltstone thickness accounts for more than 85% of the stratum thickness; that is to say, there is no conventional caprock on the oil and gas layers, but only relatively compact fine siltstone. The Manjiaer-Yingjisu sag is sag with abundant oil and gas resources. Some oil and gas structures have been discovered at present, and the exploration prospect is very broad.

3 Characteristics of Tight Sandstone Caprock The Silurian tight sandstone caprocks in the Manjiaer-Yingjisu are mainly composed of fine sandstone and siltstone. Rock types are mainly lithic sandstone with high shale content, low composition maturity, and low structural maturity. The pore types are intragranular dissolved pores and a few residual intergranular pores. The distribution of pore throat radius is less than 0.3 lm, accounting for about 80%. The intergranular pore and pore throat of the rock are largely filled by authigenic quartz and calcite minerals, and most pores and pore throat are reduced to narrow gaps. 3.1

Upper Limit of Physical Property of Tight Sandstone Caprock

Based on the statistical analysis of core pressure mercury and log test data, the minimum pore throat radius method,bound water saturation method, and empirical statistics method are used to determine the lower limit standard of physical property of the Silurian reservoir, that is, the upper limit of physical property of tight sandstone caprock [13–15]. The minimum pore throat radius method: The core pressure mercury data of 151 samples from six wells were optimized, and the minimum pore throat radius was determined by Val. When the average minimum pore throat radius is 0.1 µm, the corresponding lower limit of physical property of reservoir is porosity 5.0% and permeability 0.1 mD. Bound water saturation method: It is generally considered that there is no movable fluid in the pores when the bound water saturation is 80%, and the corresponding lower limit of physical property of reservoir is porosity 5.2% and permeability 0.12 mD. Empirical statistics method: 500 samples from three oil and gas indication wells were selected, and the corresponding porosity was 5.5% when the cumulative loss capacity was less than 5.0%. The corresponding permeability is 0.15 mD on the pore permeability relation diagram, that is, the corresponding lower limit of physical property of reservoir is porosity 5.5% and permeability 0.15 mD. It is comprehensive determined that the lower limit of physical property of the Silurian reservoir is porosity 5.5% and permeability 0.15 mD. For determining the upper limit of physical properties of tight sand caprocks, porosity and permeability are the minimum values, namely porosity 5.0% and permeability 0.1 mD (Table 1).

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The minimum pore throat radius method Bound water saturation method Empirical statistics method Lower limit of physical property of reservoir Upper limit of physical properties caprock

3.2

Physical property standard Effective porosity Air permeability (%) (mD) 5.0 0.1 5.2 0.12 5.5 0.15 5.5 0.15 5.0

0.1

Standard for Dividing the Caprock of Tight Sandstone

Using core test and conventional logging data analysis, the main factors affecting the evaluation of tight sandstone caprock are replacement pressure, porosity, permeability, average pore throat radius, and calcite content [16–18]. 3.3

Replacement Pressure

The replacement pressure is the minimum pressure required for the wetting fluid in a rock sample begins to be displaced by the non-wetting fluid. Sedimentary rocks are mostly wetted by water. If oil and gas migrate through sedimentary rocks, they must first replace the water in order to enter the sedimentary rocks. If the driving force of oil does not reach the replacement pressure required to enter the caprock, the oil will be blocked under the cap. The differential pressure between the reservoir and the cap resulted in the sealing effect of the caprock on the oil and gas in the reservoir [19, 20]. Based on the experimental analysis data of capillary pressure of four wells, the relationship between replacement pressure Pd and porosity is established as y = 19.885x−1.4249. According to this formula, when the porosity of rock is 5% and the lower limit of replacement pressure of tight sandstone cap is 2.0 MPa (Fig. 1).

Fig. 1. Relation diagram of replacement pressure and porosity

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For the tight sandstone section of well YN2, the breakthrough pressure experiment shows that under the condition of no water cut, the overall breakthrough pressure of the tight sandstone section is 0.07–12.5 MPa. The overall breakthrough pressure of tight sandstone from 3410.0 to 3512.0 m is 1.31–1.90 MPa. According to the oil test data and theoretical calculation, the pressure difference of the well from the gas-producing layer (3626.02–3667.56 m) to 3410.0 m is 5.69 MPa. That is, the tight sandstone of the 3410.0–3512.0 m well section of this well can not block the gas reservoir beneath it without water cut, and it can not be used as a caprock. How does the sandstone that replacement pressure from 2.0 to 5.69 MPa in well YN2 block the gas reservoir? This involves the problem of water lock effect. Water lock effect refers to the phenomenon that the external fluid enters the formation, increases the water saturation of the formation, increases the flow resistance of the oil and gas, and leads to the decrease of the effective permeability of the oil and gas. When the water saturation reaches 20%, the permeability loss is more than 85%, and the permeability decreases below 0.02 mD. Therefore, the replacement pressure of 2.0, 5.69 MPa, and bound water saturation 20% can be used as the limits of the classification of tight sandstone cover layers (Table 2). Bound water saturation is equivalent to minimum water saturation. Table 2. Classification evaluation criteria of the Silurian tight sandstone caprocks in the Manjiaer-Yingjisu sag Category Macroscopic parameters of pore structure

Microcosmic parameters of pore structure

Calcite content (%)

3.4

I

II

Porosity (%) Permeability (mD)

m > < dz dPF ¼ f qm v2m 2Doi > > ddPz : dv m A dz ¼ qm vm
dz

ð12Þ

where

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where PG, PF and PA are, respectively, the gravity pressure drop, friction pressure drop and acceleration pressure drop, Pa; h is the hole drift angle, radian. 2.5

Prediction Models for the Formation and Decomposition of Natural Gas Hydrate

In the production of deepwater water-bearing gas reservoir, it is necessary to predict its formation or decomposition situation after the judgement of whether it is formed or decomposed through the gas hydrate phase equilibrium model according to the wellbore temperature field and pressure field. Therefore, the formation and decomposition prediction models of natural gas hydrate are established as follows. The formation of gas hydrate can be divided into: nucleation and growth process. Based on Skovborg and Rasmussen’s research [11], we deeply analyze and establish the prediction model of gas hydrate formation as follows:
rf ¼ Kf Af Prm
e


R

Ef f Tm

e



 a DT b

ð1 þ KG Pm Þ1

ð13Þ

where rf is the formation rate of gas hydrate, mol/s; Kf is the formation rate constant of the hydrate, mol/(s m2 Pa); Af is the effective area of formation reaction of the hydrate, m2; r is the coefficient of partial pressure of natural gas, dimensionless; Ef is the activation energy of generating reaction, kJ/mol; Rf is the general gas constant, valued as 0.008314 kJ/(mol K); DT is the difference between wellbore temperature and phase equilibrium temperature, K; a and b are both the overcooling correction factor, dimensionless; and KG is the adsorption equilibrium constant, Pa−1. The decomposition of natural gas hydrate can be divided into: the destruction of the surface structure of hydrate particles and the desorption of methane gas molecules on the surface of hydrate particles. Based on this mechanism, combined with the research of Kim et al. [13], the prediction model of natural gas hydrate decomposition is deeply analyzed and established as follows:   rd ¼ Kd Ad feq ðTm ; Peq Þ  fm ðTm ; Pm Þ

ð14Þ

where rd is the decomposition rate of the natural gas hydrate, mol/s; Kd is the decomposition rate constant of the hydrate, mol/(s m2 Pa); Ad is the effective area of decomposition reaction of the hydrate, m2; feq and fm are the fugacity of the methane gas in the wellbore temperature of Tm and, respectively, in the hydrate phase equilibrium pressure Peq and in the wellbore pressure of Pm, Pa. 2.6

Numerical Calculation

According to the wellbore temperature field, pressure field, gas hydrates phase equilibrium, formation and decomposition prediction model, and combining the basic parameter equation, and gas wellbore flow equation, the numerical calculation method focusing on the prediction of formation and decomposition of hydrate in the production

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of water-bearing gas reservoir in deep water is established. The boundary conditions are as follows. Wellhead pressure is equal to tubing head pressure, which is written as Pm ð0Þ ¼ P0

ð15Þ

Bottom hole temperature is equal to reservoir fluid temperature, which is written as Tm ðzH Þ ¼ Tmr

ð16Þ

where Pm(0) is the wellhead pressure, Pa; P0 is the tubing head pressure, Pa; Tm(zH) is the bottom hole temperature, K; and Tmr is the temperature of formation fluid, K. In this model, the spatial domain of numerical calculation is the wellbore, and the numerical method of finite-difference iterative method is used: take any two nodes i and i + 1 in the wellbore as an example to demonstrate that the numerical process (Fig. 1), where the parameters of the node i to the known conditions.

Boundary conditions: wellhead pressure Pm(0), bottom hole temperature Tm(zH)

Assumed condition: wellhead temperature Tm(0)

Space node meshing Construction parameters in the production of deep water water-bearing gas reservoir: production, tubing head pressure Calculate the wellbore temperature Tm(i) and pressure pm(i) of node i Judge if there are any phase changes of natural gas hydrate at the calculation node according to the phase equilibrium prediction model No-hydrate area

Hydrate formation area

Hydrate decomposition area

Formation amount by Decomposition amount by prediction model of prediction model of hydrate decomposition hydrate formation Calculate the parameter of next node i+1 Calculate the bottom hole temperature Tmi(zH) |Tmi(zH) Wellbore temperature

Wellbore pressure

Tm(zH)| < η Yes

No

The formation and decomposition of natural gas hydrate

The prediction of hydrate formation and decomposition in the production of water-bearing gas reservoir in deep water

Fig. 1. Numerical calculation process of hydrate formation and decomposition in the production of water-bearing gas reservoir in deep water

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3 Results The basic parameters of hydrate formation and decomposition prediction in the production of water-bearing gas reservoir in deep water are as follows: The well depth is 2500 m, the seawater depth is 1500 m, the surface temperature is 298 K, geothermal gradient is 0.025 K/m, tubing outer diameter is 0.114 m, tubing inner diameter is 0.094 m, riser outer diameter is 0.508 m and the riser inner diameter is 0.488 m. 3.1

The Sensitivity Behaviors of Different Tubing Head Pressure

(1) The sensitivity behaviors of different tubing head pressure in the condition of gas production of 10  104 m3/d. In the condition of gas production of 10  104 m3/d and water production of 0.01  104 m3/d, through the numerical calculation, the influence of different tubing head pressure (0, 1, 2, 3, 4 and 5 MPa) on the formation and decomposition of hydrate in the production is compared, as shown in Figs. 2 and 3. As can be seen from Fig. 2, the wellbore temperature decreases with the depth of well and then increases in the construction of gas production. It is mainly caused by that the formation temperature decreases with the decline of the depth in the well section below the mudline, and the temperature of seawater increases with the decline of the depth in the well section above the mudline. The heat transfer between wellbore fluid and formation or seawater causes that the wellbore temperature decreases with the decline of the well depth and then increases. As can be seen from Fig. 3, the equilibrium pressure curve of hydrate calculated on the basis of wellbore temperature is changed with the well depth in the same way as that of wellbore temperature. The wellbore pressure constantly decreases with the decline of the well depth.

Fig. 2. Wellbore temperature field distribution in different tubing head pressure in the condition of gas production of 10  104 m3/d and water production of 0.01  104 m3/d

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Fig. 3. Distribution of wellbore pressure field and hydrate phase equilibrium pressure in different tubing head pressure in the condition of gas production of 10  104 m3/d and water production of 0.01  104 m3/d

In the condition of gas production of 10  104 m3/d and water production of 0.01  104 m3/d, the wellbore temperature changes little with the increase of tubing head pressure from 0 to 5 MPa (Fig. 2), the wellhead temperature is kept at about 288.10 K, and the minimum wellbore temperature is about 277.65 K. Meanwhile, the wellbore pressure obviously rises from 1.72 to 7.68 MPa (Fig. 3). In Fig. 3, there is a critical intersecting position between the equilibrium pressure curve of hydrate and the wellbore pressure curve at the well depth of 1028 m while the tubing head pressure is 3 MPa, indicating that there is a critical position needed for hydrate formation in the wellbore in this construction condition. There is no critical intersecting position between the equilibrium pressure curve of hydrate and the wellbore pressure curve while the tubing head pressure is smaller than 3 MPa, indicating that there is no hydrate formed in the wellbore in this construction condition. When the tubing head pressure is larger than 3 MPa, there are two intersecting points between the equilibrium pressure curve of hydrate and the wellbore pressure curve with the gas production and the decline of well depth. The first intersecting point represents the critical formation position of the hydrate, and the second represents the critical decomposition position of the hydrate. When the updraft is not reached at the first intersection, the formation condition of gas hydrate is not reached, and there is no hydrate formed in the wellbore. The hydrate is continuously formed in the wellbore between the first and second intersections. As the airflow rises to the second intersection, the hydrate particles that rise with the flow are decomposed into gases and water. The formation and decomposition of gas hydrate in wellbore are obtained by numerical calculation for the tubing head pressure of 4 and 5 MPa in the construction of gas production in Fig. 4. As shown in Fig. 4, with the decline of well depth, the wellbore can be divided into no-hydrate area, critical formation position of hydrate, hydrate formation area, critical decomposition position of hydrate and hydrate decomposition area. In the hydrate formation area, the hydrate is formed and the amount of substance is

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Fig. 4. The distribution of formation and decomposition of hydrate with well depth in the tubing head pressure of 4 MPa (a) and 5 MPa (b), the gas production of 10  104 m3/d, and the water production of 0.01  104 m3/d

increased constantly. In the hydrate decomposition area, the hydrate is decomposed and the amount of substance is decreased constantly, and it is still not decomposed completely at the wellhead. Meanwhile, with the increase of tubing head pressure from 3 to 5 MPa, the wellbore pressure is increased, and the critical intersection formation position between the wellbore pressure curve and the equilibrium pressure curve of hydrate is moved down. And the hydrate is easier to be formed and formation area is larger, the amount of formed hydrate is getting more, and it is much easier to block pipeline and bring the problem of production safety. (2) The sensitivity behaviors of different tubing head pressure in the condition of gas production of 20  104 m3/d. In the condition of gas production of 20  104 m3/d and water production of 0.02  104 m3/d, through the numerical calculation, the influence of different tubing head pressure (0, 1, 2, 3, 4 and 5 MPa) on the formation and decomposition of hydrate in the production is compared, as shown in Figs. 5 and 6.

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Fig. 5. Distribution of wellbore temperature field in different tubing head pressure in the condition of gas production of 20  104 m3/d and water production of 0.02  104 m3/d

Fig. 6. Distribution of wellbore pressure field and hydrate phase equilibrium pressure in different tubing head pressure in the condition of gas production of 20  104 m3/d and water production of 0.02  104 m3/d

As can be seen from Figs. 5 and 6, in the condition of gas production of 20  104 m3/d and water production of 0.02  104 m3/d, the wellbore temperature changes little with the increase of tubing head pressure from 0 to 5 MPa (Fig. 5), the wellhead temperature is kept at about 285.28 K, and the minimum wellbore temperature is about 279.72 K. Meanwhile, the wellbore pressure rises from 3.39 to 8.04 MPa (Fig. 6). In Fig. 6, there is a critical intersecting position between the equilibrium pressure curve of hydrate and the wellbore pressure curve at the well depth of 784 m while the tubing head pressure is 4 MPa, indicating that there is a critical position needed for hydrate formation in the wellbore in this construction condition. There is no hydrate formed in the wellbore while the tubing head pressure is smaller than 4 MPa. The hydrate will be formed in the wellbore when the tubing head pressure is larger than 4 MPa.

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Meanwhile, similar to the condition of the gas production of 10  104 m3/d, with the increase of the tubing head pressure from 4 to 5 MPa, the wellbore pressure is increased, and the critical intersection formation position between the wellbore pressure curve and the equilibrium pressure curve of hydrate is moved down. And the hydrate is easier to be formed and the formation area is larger, the amount of formed hydrate is getting more, and it is much easier to block the pipeline and bring the problem of production safety. (3) The sensitivity behaviors of different tubing head pressure in the condition of gas production of 30  104 m3/d. In the condition of gas production of 30  104 m3/d and water production of 0.03  104 m3/d, through the numerical calculation, the influence of different tubing head pressure (0, 1, 2, 3, 4 and 5 MPa) on the formation and decomposition of hydrate in the production is compared, as shown in Figs. 7 and 8.

Fig. 7. Distribution of wellbore temperature field in different tubing head pressure in the condition of gas production of 30  104 m3/d and water production of 0.03  104 m3/d

Fig. 8. Distribution of wellbore pressure field and hydrate phase equilibrium pressure in different tubing head pressure in the condition of gas production of 30  104 m3/d and water production of 0.03  104 m3/d

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As can be seen from Figs. 7 and 8, in the condition of gas production of 30  104 m3/d and water production of 0.03  104 m3/d, the wellbore temperature changes little with the increase of tubing head pressure from 0 to 5 MPa (Fig. 7), the wellhead temperature is kept at about 284.80 K, and the minimum wellbore temperature is about 281.71 K. Meanwhile, the wellbore pressure rises from 5.08 to 9.05 MPa (Fig. 8). In Fig. 8, there is a critical intersection position between the wellbore pressure curve and the phase equilibrium pressure curve of hydrate at the well depth of 641 m while tubing head pressure is 5 MPa, indicating that there is a critical position needed for hydrate formation in the wellbore. The hydrate won’t be formed in wellbore when tubing head pressure is smaller than 5 MPa. 3.2

The Sensitivity Behaviors of Different Gas Production

In the condition of the tubing head pressure of 5 MPa, through the numerical calculation, the influence of different gas production (10  104 m3/d, 20  104 m3/d and 30  104 m3/d) on the formation and decomposition of hydrate in the production is compared, as shown in Figs. 9, 10 and 11.

Fig. 9. Distribution of wellbore temperature filed in different gas production

In Fig. 9, the lowest temperature in the wellbore increases from 277.65 to 281.71 K and the wellhead temperature decreases from 288.10 to 284.80 K with the increase of gas production. The main reason is that the fluid flow in the wellbore increases with the increase of gas production, the heat exchange time between fluid and formation, and fluid and seawater, is shortened, and the heat exchange is reduced during the production process. In Fig. 10, the wellbore pressure increases and the critical formation position of the intersection of the wellbore pressure curve and hydrate phase equilibrium pressure curve is moved upward from 1501 to 641 m, and there is no intersection area in the end, indicating that the larger the gas production volume, the more difficult it is to generate gas hydrates in the wellbore.

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Fig. 10. Distribution of wellbore pressure filed and hydrate phase equilibrium pressure in different gas production

Fig. 11. Distribution of formation and decomposition of hydrate in different gas production

In Fig. 11, the area where the amount of substance of hydrate increases is just the area where the hydrate is formed in the wellbore, which is shortened with the increase of gas production until there is no formation area in the end. Moreover, the formation rate of hydrate is reduced, and the gas hydrate formed in the wellbore is reduced, which is more helpful to secure the wellbore.

4 Conclusion The prediction models of wellbore temperature and pressure field, and the prediction model of hydrate phase equilibrium, formation and decomposition in the deepwater water-bearing gas reservoir production process are established in this paper. And the prediction method of hydrate formation and decomposition is established combining the wellbore flow equation. The sensitivity behaviors of different production construction parameters are obtained.

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(1) With the increase of production, the wellbore minimum temperature increases, the wellhead temperature decreases, wellbore pressure increases, the critical intersection position of wellbore pressure curve and hydrate phase equilibrium pressure curve is moving upward, and there is no intersection area finally, hydrate formation area decreases, and there is no formation area finally. Moreover, the formation rate of hydrate decreases, and the gas hydrate formed in the wellbore decreases, which helps to ensure the safety of the wellbore. (2) The larger the tubing head pressure, the greater the wellbore pressure, the lower the critical intersection position of wellbore pressure curve and hydrate phase equilibrium pressure curve, the more easily the gas hydrate formed in the wellbore, the larger the hydrate formation area, the greater the amount of hydrate formed, and the greater the risk of wellbore blockage. (3) The parameters of production and tubing head pressure in the production of deepwater water-bearing gas reservoir should be rationally adjusted, so as to prevent the formation of hydrate in the wellbore and ensure the production safety. Acknowledgements. This study was carried out with the support of the National Key Research and Development Program (No. 2016YFC0304008), Strategic Research Program of Chinese Academy of Engineering in Science and Technology Medium and Long-Term Development Strategy Research Field (No. 2017-ZCQ-5) and the National Natural Science Funds of China (No. 51334003).

References 1. Xi FY, Liu WF, Li RZ. Supply–demand status and trends of world oil & gas. Pet Petrochem Today. 2007;15(6):14–8. 2. Wu Y, Wei WX, Cai WX. A research on the development strategy of unconventional oil and gas resources in China. China Popul Resour Environ. 2015;25(11):292–5. 3. http://www.360baogao.com/List_NengYuanCaiLiaoBaoGao/70/HaiYangYouQiZiYuanKai FaDeFaZhanQianJing.html. Accessed Jan 2018. 4. Zhang W, He NX. Strategic analysis of offshore oil and gas resources exploitation. Technol Innov Appl. 2016;13:122. 5. Waals JHVD, Plateeuw JC. Clathrate solutions. In Prigogine I, editor. Advances in chemical physics. 1st ed. Wiley; 1959 p. 1–57. 6. Clarke MA, Poolladi-Darbish M, Bishnoi PR. A method to predict equilibrium conditions of gas hydrate formation in porous media. Ind Eng Chem Res. 1999;38(6):2485–90. 7. Clennell MB, Hovland M, Booth JS, Henry P, Winters WJ. Formation of natural gas hydrates in marine sediments: 1. Conceptual model of gas hydrate growth conditioned by host sediment properties. J Geophys Res. 1999;104(B10):22985–3003. 8. Henry P, Thomas M, Clennell MB. Formation of natural gas hydrates in marine sediments: 2. Thermodynamic calculations of stability conditions in porous sediments. J Geophys Res. 1999;104(B10):23005–22. 9. Vysniauskas A, Bishnoi PR. A kinetic study of methane hydrate formation. Chem Eng Sci. 1983;38(7):1061–72. 10. Englezos P, Kalogerakis N, Dholabhai PD, Bishnoi PR. Kinetics of formation of methane and ethane gas hydrates. Chem Eng Sci. 1987;42(11):2647–58.

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11. Skovborg P, Rasmussen P. A mass transport limited model for the growth of methane and ethane gas hydrates. Chem Eng Sci. 1994;49(8):1131–43. 12. Bahman Z, Mona M, Farshad V. A new approach for determination of single component gas hydrate formation kinetics in the absence or presence of kinetic promoters. Chem Eng Sci. 2015;137:447–57. 13. Kim HC, Bishnoi PR, Heidemann RA, Rizvi SSH. Kinetics of methane hydrate decomposition. Chem Eng Sci. 1987;42(7):1645–53. 14. Kamath VA, Holder GD, Angert PF. Three phase interfacial heat transfer during the dissociation of propane hydrates. Chem Eng Sci. 1984;10(39):1435–42. 15. Kamath VA, Holder GD. Dissociation heat transfer characteristics of methane hydrates. AIChE J. 1987;33(2):347–50. 16. Clarke MA, Bishnoi PR. Measuring and modeling the rate of decomposition of gas hydrates formed from mixtures of methane and ethane. Chem Eng Sci. 2001;56(16):4715–24. 17. Clarke MA, Bishnoi PR. Determination of the intrinsic rate of ethane gas hydrate decomposition. Chem Eng Sci. 2000;55(21):4869–83. 18. Wei N, Sun WT, Meng YF, Zhou SW, Li G, Guo P, Dong K, Li QP. Sensitivity analysis of multiphase flow in annulus during drilling of marine natural gas hydrate reservoirs. J Nat Gas Sci Eng. 2016;36(A):692–707. 19. Wei N, Sun WT, Li YJ, Meng YF, Gao L, Guo P, Liu AQ. Characteristics analysis of multiphase flow in annulus in natural gas hydrate reservoir drilling. AER–Adv Eng Res. 2015;40:396–400. 20. Sun WT, Meng YF, Wei N, Li YJ, Li G, Chen GL. Sensitivity of wellbore temperature in offshore drilling. Nat Gas Technol Econ. 2016;10(4):36–40. 21. Ramey HJ. Wellbore heat transmission. J Petrol Technol. 1962;14(4):427–35. 22. Kabir CS, Hasan AR. Heat transfer during two–phase flow in wellbore, part I formation temperature. In: SPE Annual Technical Conference and Exhibition, Dallas, Texas; October 1991, p. 469–478. 23. Wei N, Sun WT, Meng YF, Zhou SW, Fu Q, Guo P, Li QP. Annular phase behavior analysis during marine natural gas hydrate reservoir drilling. Acta Pet Sin. 2017;38(6):710–20.

Horizontal Well Technology for Tight Reservoirs with Coal Seams in the Fangzheng Fault Depression Jingfeng Wu(&) Exploration and Development, Research Institute of Daqing Oilfield Company Ltd., Daqing, China [email protected]

Abstract. In the Fangzheng Fault Depression Cretaceous reservoirs represent significant resources that are deeply buried, have very low porosity and permeability, and low rates of production at single wells when using conventional technology. Their conditions do allow increased production via horizontal wells. The top of Cretaceous tight reservoirs are adjacent to coal seams and therefore have a high risk of fracturing when drilling is taking place. At present, there is relatively little experience, either at home or abroad, for the exploration of coal seams immediately above horizontal sections. For the first time, horizontal wells have been implemented in the Fangzheng Fault Depression, something that represents a significant technological challenge. This practice draws on the horizontal well design, drilling and tracking, and large-scale volume-fracturing technology, using a technique known as “three optimizations, two accuracies, and one match,” in the Daqing Oilfield (Cui et al. in Pet Geol Oilfield Dev Daqing 33(5):16–22, [1]). Starting with selective lateral drilling and the determination of horizontal well orientation, fine seismic lateral predictions of coal seams and target layers were carried out. During the drilling process, integrated drilling, cutting logging, and logging while drilling, quickly allowed the identification of coal seams. An effective horizontal well technology, that prevents and controls coal wellbore stability, was formulated. Drilling-adjustment techniques were used to ensure the drilling trajectory deviations required due to

Copyright 2018, Shaanxi Petroleum Society. This paper was prepared for presentation at the 2018 International Field Exploration & Development Conference in Xi’an, China, 18–20 September 2018. This paper was selected for presentation by the IFEDC&IPPTC Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the IFEDC&IPPTC Committee and are subject to correction by the author(s). The material does not necessarily reflect any position of the IFEDC&IPPTC Committee, its members. Papers presented at the Conference are subject to publication review by Professional Committee of Petroleum Engineering of Shaanxi Petroleum Society. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of Shaanxi Petroleum Society is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of IFEDC&IPPTC. Contact email: [email protected]. © Springer Nature Singapore Pte Ltd. 2020 J. Lin (ed.), Proceedings of the International Field Exploration and Development Conference 2018, Springer Series in Geomechanics and Geoengineering, https://doi.org/10.1007/978-981-13-7127-1_36

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J. Wu variations in formation dip angle. To increase oil well productivity and reduce perforation, open hole stage fracturing technology was adopted. Output from a horizontal well was found to be 16 times greater than from a single well—the effect of this on increased production cannot be overstated. During this investigation valuable experience was accumulated in horizontal well drilling and fracturing of tight reservoirs with coal seams in fault basins. Keywords: Tight reservoirs
Coal seams
Fangzheng fault depression
“three optimizations, two accuracies, and one match/configuration” technique

1 Introduction The Fangzheng Fault Depression is a narrow, long, faulted depression basin, part of the Jiayi Fault in the northern section of the Tan-lu Fault Zone, located in central and western China, in the Heilongjiang Province. At this location, Cretaceous reservoirs sit at depths of over 3000 m, having oil thicknesses of about 30 m, an oil reservoir distribution area of about 25 km2, porosity from 2 to 6%, and a permeability from 0.1 to 0.5 mD—representing typical deep, tight reservoirs. The Cretaceous exploratory wells employ conventional techniques to produce low output levels per well. The upper part of the target layer in this study area was adjacent to coal seams (Fig. 1), and the risk of coal wellbore collapse was relatively high. Very few people have experience, either locally or globally, of working with horizontal wells with coal seams that sit above target levels. This study represents the first time horizontal drilling has been performed in this area. Therefore, a horizontal well technology known as “three optimizations, two accuracies, and one match/configuration,” used for tight oil in the Daqing Oilfield, was used to guide the design and construction of a horizontal well. “Three optimizations” refers to the deployment and design techniques of horizontal wells. This technique firstly identifies the “desserts” in the target area, clarifies the target layer; secondly determines the optimal drilling direction; and finally optimizes the drilling trajectory. “Two Accuracy” refers to horizontal well tracking and adjustment techniques that are accurate tracking of the drilling trajectory and prevention techniques that deviate from the drilling trajectory. “One Match/Configuration” refers to an optimization technique for horizontal well fracturing stimulation and retrofitting.

2 Target Layer Determination and Trajectory Optimization The design of the study followed the “three optimizations” approach. At the top of the development area of the Cretaceous tight reservoirs, the F6 well was chosen as the site for implementing a horizontal well and subsequent lateral drilling. The F6 well was chosen because of the low yield it achieves from Cretaceous tight reservoirs when using conventional drilling techniques. Seismic reflection characteristics of the tight oil

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Fig. 1 A comprehensive stratigraphic column for the F6 well

reservoirs in this well area show strong amplitude and continuous reflection (Fig. 2). The target area was determined at the top of the Cretaceous tight oil layer in the F6 well. According to structural characteristics, the horizontal well trajectory runs perpendicular to the direction of maximum principal stress, that is, in the direction of minimum principal stress. The best drilling direction was determined as being from high structural to the low structural orientation to avoid significant changes in horizontal well trajectory [2], consistent with the direction and distribution of the body of sand [3, 4].

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Fig. 2 Seismic reflection characteristics of coal seams and tight reservoirs in the vicinity of the F6 well

The tight oil layer is located at the top of the Cretaceous reservoirs. Horizontal drilling was found to be difficult to control, with deviations from the oil layer occurring easily. In order to ensure that the trajectory of the horizontal section was within the oil layer, the target and control points in the tight oil layer were carefully designed (Fig. 3). Consideration was given to the cracks that formed during fracturing operations (ranging from −20 m to +30 m). The vertical distance of the design horizon was 10–30 m from the top of the Cretaceous layer. After fracturing, the fractures can communicate with the tight reservoirs at the top of Cretaceous, so that higher production can be obtained.

Fig. 3 Geological model showing the F6 horizontal well design

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3 Precise Targeting and Advanced Trajectory Control Precise stratigraphic correlation, well-seismics combined with comparative calibration, seismic prediction, and geological-modeling (Fig. 3) methods were used to accurately predict the top boundary depth and formation thickness of both the coal seams and target layer. The drilling process was combined with geo-steering, logging while drilling, cutting logging, etc., to facilitate real-time corrections to deviations and to reduce drilling risks thereby ensuring smooth entry. The specific requirement was to ensure that the actual drilling trajectory was about 6° smaller than the original design deviation angle; to keep the vertical depth trajectory slightly less than the vertical depth of the designed trajectory so that the trajectory could be adjusted when deviations in the oil reservoirs were encountered during subsequent drilling operations. The slight fluctuation of formation will cause the change of formation dip, which will affect the deviation of drilling trajectory. To counter this, a set of horizontal well trajectory adjustment techniques, for changing formation dip angle, were used (summarized in the drilling practices indicated in Fig. 4) to ensure that the horizontal trajectory maximized the drilling capability within the reservoirs.

Fig. 4 Horizontal trajectory adjustment pattern for formation dip change

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4 Effective Risk Prevention and Control Measures for Coal Seams While the coal seams served as reliable marker layers, they also represented a significant risk in terms of wellbore collapse. Coal seam vertical thickness was 5.3 m, but horizontal sections were drilled to lengths of nearly 30 m. Therefore, a process technology was required that was both suitable for drilling coal seams before horizontal drilling and maintaining a stable drilling fluid performance in the coal seams.

5 Coal Seam Drilling Control Technology When drilling in coal seams, it is necessary to drill through them in one go in order to prevent wellhole collapse, reduce drilling pressure and rotational speed so as to slowly and fully release coal seam stresses, promptly repair any damage within a wellbore, and avoid pumping. It is important while controlling the drilling speed in coal seam sections to continuously grouting. When drilling trajectory enters coal seam, according to cuttings logging and logging while drilling data, timely analysis of whether the drilling trajectory drills through the coal seam, confirm that the drilling passes through the last group of coal seams and then normal drilling.

6 Drilling Fluid Performance Control Technology In order to ensure wellbore stability drilling fluid is used—usually in the form of a water-in-oil system. Drilling fluid density is always maintained above 1.15 g/cm3 for sidetrack drilling and is increased to 1.20 g/cm3 before drilling into coal seams. At a depth of 50 m from coal seams, a 1–2% plugging agent is added to the drilling fluid. After passing through a coal seam, drilling fluid density is reduced below 1.18 g/cm3.

7 Open Hole Stage, Large-Scale Fracturing Horizontal well and large-scale volume fracturing represents the core technology for tight oil exploration and development [5–7]. To ensure the best possible oil production and reduce perforating processes, according to differences in oil level display in a horizontal section [8], changes in the deviation angle [9–11], and vertical distance from the top of the oil layer, the horizontal section was divided into six stages in order to complete open hole stage fracturing. To avoid the risk of high construction pressure and an inability to open strata during fracturing, it is important to first select fracturing parameters by testing fracturing, and then to select an appropriate propping agent and fracturing fluid construction according to fracturing test results.

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8 First- and Second-Stage Construction Technology Complete a test fracture, identify the formation, and select the fracturing parameters. If the net pressure in the reservoirs decreases during construction, adjust the displacement of the fracturing fluid. The method of “critical sand ratio in short sand section” is used to determine the appropriate sand content.

9 Third-, Fourth-, and Fifth-Stage Construction Technology Complete a test fracture to further identify the formation and select a fracturing fluid for construction displacement. Use medium and low sand for long-term treatment to ensure matching of crack and sand ratio; at the same time, adopt the “critical sand ratio in a short sand section” method to determine the boundary for safe sand addition.

10

Sixth-Stage Construction Technology

Complete test fracturing to identify formations and adopt the “critical sand ratio in a short sand section” method to determine the boundary for safe sand addition. Finally, the sixth stage of open hole fracturing adopted in this process, is to ensure that each for each stage the sliding sleeve is open, and that each stage of fracturing works smoothly. The operation of adding propping agent to all six stages can now be successfully completed. A total of 3800 m3 of fracturing fluid and 360 m3 of proppant were injected into the six fracturing stages (Fig. 5). Open hole stage construction fracturing effect meets design requirements.

Fig. 5 Fracture curves for the six stages at the F6 horizontal well

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Analysis

As a consequence of the above technical measures to ensure the smooth completion of a horizontal well and large-scale fracturing, the length of the drilling section achieved was 383.6 m, the cumulative length of oil sands was 348 m, giving an oil–sandstone drilling rate of 90.7%. Horizontal well production increased by 16 times compared with conventional well technology.

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Conclusions

The practice of using a horizontal well in tight oil reservoirs with coal seams in the Fangzheng Fault represents an application of the “three optimizations, two accuracies, and one match” technology used in the Daqing Oilfield. Through this practice, a set of drilling technologies can effectively control the stability of coal seam wellbores. Horizontal well technology, integrating design, drilling, and the fracturing of a fault basin with coal seams has been established, providing experience for similar applications in other fault depressions. Acknowledgements. The authors express their sincere thanks for the support received from the major science and technology projects fund of the China National Petroleum Corporation (Project number: 2016E-0202).

References 1. Cui B, Lin T, Dong W. Horizontal well technology and exploration practice for tight oil in northern Songliao Basin. Pet Geol Oilfield Dev Daqing. 2014;33(5):16–22. 2. Xu X, Li J. Seismic sedimentology in oil and gas exploration research and application. J Yangtze Univ. 2015;12(29):32–5 (Natural Science Edition). 3. Dai G. Optimized design of horizontal wells for tight oil in Fuyu reservoirs and adjustment while drilling. J Yangtze Univ. 2016;13(20):50–5 (Natural Science Edition). 4. Bi X, Yan T, Han H. Study on the design of wellbore section of lateral inclined well in Daqing oilfield. Spec Oil Gas Reserv. 2005;12(2):29–33. 5. Dou Y. Structure design of wellbore in large displacement well. Spec Oil Gas Reserv. 2013;20(5):141–4. 6. Xu Z, Liu Z, Li Y. Application of early prediction methods for formation pressure in the Gulf of Thailand. Pet Geol Oilfield Dev Daqing. 2011;30(1):47–53. 7. Ye Z, Yang S, Zhao B. Segmented fracturing technology for ultra-deep and ultra-low permeability horizontal wells in the Shun 9 well area of Tazhong oilfield. Spec Oil Gas Reserv. 2013;20(4):134–7. 8. Giger FM, Reiss LH, Jourdan AP. The reservoirs engineering aspects of horizontal well. SPE 13024; 1984. 9. Soliman MY, Hunt JL, El Rabaa AM. Fracturing aspects of horizontal wells. SPE 18542; 1990. 10. Richardson M. A new and practical method for fracture design and optimization. SPE 59736; 2000. 11. Chen Y, Tang Y, Liu S. Optimization of the stage fracturing of horizontal wells with low permeability and tight gas reservoirs. Spec Oil Gas Reserv. 2012;19(6):85–7.

Reservoir Characteristics of Epimetamorphic Rock Gas Reservoir in Pingxi Area, Qaidam Basin Zhiyuan Xia1(&), Senming Li1, Zhanguo Liu1, Bo Wang2, Yanqing Wang1, and Mei Xie2 1

2

PetroChina Hangzhou Research Institute of Petroleum, Hangzhou 310023, Zhejiang, China [email protected] Research Institute of Petroleum Exploration and Development, PetroChina Qinghai Oil Field Company, Dunham 736202, Gansu, China

Abstract. Metamorphic rock gas reservoirs whose protolithic is sedimentary rock were found for the first time in Pingxi area, Altun foreland, Qaidam Basin. Comprehensive analysis containing core data, thin section analysis, X-ray diffraction analysis, scanning electron microscopy and confocal laser scanning shows that there are three types of shallow metamorphic rock reservoirs in Pingxi area, such as slate, “metamorphic limestone” and calc-schist which have good responses in logging and seismic data. Fractures and pores develop in epimetamorphic rock reservoir, and there are five types and eight subcategories of reservoir space. Industrial CT shows that there are differences in pores and throats of the three types of metamorphic rock reservoirs, and the fractures have a significant impact on the development of pore throats. The protolithic type is the genetic basis of epimetamorphic rock reservoirs in Pingxi area, and thin section, mineral characteristics and carbon and oxygen isotopes data show that the protolithic of epimetamorphic rock is Palaeozoic Ordovician marine sedimentary rock. Five kinds of actions, such as metamorphism, weathering,

Copyright 2018, Shanxi Petroleum Society. This paper was prepared for presentation at the 2018 International Field Exploration and Development Conference in Xi’an, China, 18–20 September 2018. This paper was selected for presentation by the IFEDC Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the IFEDC Committee and are subject to correction by the author(s). The material does not necessarily reflect any position of the IFEDC Committee, its members. Papers presented at the Conference are subject to publication review by Professional Committee of Petroleum Engineering of Shaanxi Petroleum Society. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of Shaanxi Petroleum Society is prohibited. Permission to reproduce in print are restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgement of IFEDC. Contact email: [email protected]. © Springer Nature Singapore Pte Ltd. 2020 J. Lin (ed.), Proceedings of the International Field Exploration and Development Conference 2018, Springer Series in Geomechanics and Geoengineering, https://doi.org/10.1007/978-981-13-7127-1_37

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Z. Xia et al. structural fragmentation, dissolution and filling, are external mechanisms of reservoir genesis. Metamorphic, weathering and structural fragmentation form fractures, and dissolution is the main cause of matrix porosity. Keywords: Epimetamorphic rock characteristics
Reservoir genesis


Rock type
Reservoir space
Pore throat

1 Introduction Metamorphic rock reservoir exploration is one of the hotspots in unconventional exploration. Many scholars have done little research on the characteristics of metamorphic rock reservoirs and hydrocarbon forming conditions and done some research on the characteristics of metamorphic original rock and shallow metamorphism. Ömer Faruk Celik, through the study of XRD and mineral chemical characteristics, found that the protoliths of the granitoids and granitoids in Taorides region in central Turkey are alkaline basalts, gabbro or pyroxenes. All hornblendes are calcareous and cluster-like due to Late Cretaceous tectonic stress [1]. Andrea Borgia analysed the relationship between three structural planes and bedding angle of the Palaeozoic heavy-low metamorphic rocks in the Apennines, Italy. He believed that the relationship between page angles and bedding intersections can determine the orientation, magnitude and interference patterns of folds [2]. Frey M studied the very low metamorphism of detrital sediments, and Kisch H J analysed the relationship between very low-grade metamorphism indicators [3, 4]. In China, many scholars have done some research on metamorphic rock reservoir. At present, in Liaohe Depression of Bohai Bay Basin, the Archaeozoic buried-hill metamorphic rock reservoirs dominated by migmatites, biotite plagioclase gneisses and cataclastic rocks have been discovered, and relevant scholars have studied metamorphic rocks in terms of reservoir formation main factors, reservoir characteristics, comprehensive evaluation, fracture characterization and hydrocarbon forming conditions [5–9]. In Dongying Sag, an ancient buried-hill metamorphic rock reservoir mainly composed of Archaean gneiss and granulite was found [10], and in Bayer fault depression, Hailaer Basin [11, 12], Badatt epimetamorphic rock series reservoir was found too. In the above metamorphic rock reservoirs, most of the protolithic types of metamorphic rock reservoirs are volcanic rocks, and there are few studies on metamorphic rock reservoirs with primary rocks that are sedimentary rocks and have low metamorphic degrees. On the aspect of shallow metamorphic rocks, by organic geochemical analysis, some scholars believe that the underlying Carboniferous–Permian strata in the Songliao Basin are in a stage of shallow metamorphism [13]. And other scholars conclude that the extremely low-grade, shallow metamorphic rocks (mudstones) in Songliao Basin have strong hydrocarbon generation capabilities based on thermal simulation experiments, thermal simulation product composition and stable carbon isotope analysis [14]. Exploration of volcanic and metamorphic rock gas reservoirs has made great breakthroughs and discoveries in the Qaidam Basin in recent years. Metamorphic gas reservoir with fractures and dissolved pores has been found in Mabei oil field, Qilian Mountain [15]. Fracture-dissolution granites or slate volcanic

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rocks and metamorphic rock reservoir have been discovered in Kunbei area [16]. A volcanic gas reservoir dominated by granite and granitic gneiss was discovered in the Dongping area which demonstrated broad exploration prospects [17]. In the past two years, metamorphic rock gas reservoir with lower metamorphic rocks was first found in Pingxi area, Altun Mountain, Qaidam Basin. The current situation of exploration and development reveals that the distribution of metamorphic rock gas reservoirs is not controlled by the tectonic location and reservoir depth. Complex reservoir formation and strong heterogeneity is the most critical factor in the enrichment and distribution of metamorphic gas reservoirs in Pingxi area.

2 General Situation of Regional Geology Pingxi area is located in the west of the Dongping uplift in the east section of the front Altun Mountains in the Qaidam Basin. It starts from Spiles hill, Great Wind hill in the west, Nose Beam in the east, and near the Alkali hill in the south, which is a south inclined slope controlled by the north-south fault. The eastern area of Arkin section mainly experienced three major tectonic evolution stages, such as early extension and fault depression in Yanshan, early Himalayan fracture depression, and late Himalayan extrusion inversion. The present structure formatted the Jianbei slope, Pingxi slope, Dongping uplift and Niubei slope from the west to east. The structural morphology of the Pingxi area is strong, and the small faults in each structure are developed, forming many traps of anticline, faulted anticline and fault block. The basement of the Pingxi area is mainly composed of metamorphic rocks and granites from Proterozoic and Palaeozoic. The zircon U-Pb dating and trace elements study indicate that the age of the Paleozoic black mica granite was 406.9 + 4.4 Ma, which belongs to the early Devonian [18]. The original rock of metamorphic rocks, whose thickness range from 460 to 970 m, belongs to Ordovician, and the lithology is mainly calc-schist, “metamorphic limestone” and slate from bottom to up. Above the basement, there is the residual Mesozoic Jurassic stratum which sedimentary by the delta front and submarine shores. The lithology is mainly grey, brownish grey fine sandstone and purple mudstone, and the stratum thickness ranges from 0 to 120 m. Above the Jurassic strata, it is the strata of the Lulehe Formation and Xiaganchaigou Formation in the Paleogene of the Cenozoic. The lithology of the lower stratum of the Lulehe Formation is mainly thick brownish glutinous and greyish-white argillaceous deposits from alluvial fan, and the upper stratum is brown mudstone covered by brown mudstone siltstone of the alluvial plain. The thickness of the stratum ranges from 1000 to 1500 m. The lower part of the Lower Ganchaigou Formation is braided fine-grained sandstone and medium-sized conglomerate from braided river facies. The upper lithology is grey, brown-grey mudstone, brown-grey siltstone, fine sandstone, is sediment of delta, shore shallow lake, and formation thickness ranges 1200–1600 m (Fig. 1).

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Fig. 1. Tectonic geology and stratigraphic map in the Pingxi area

3 Characteristics of the Epimetamorphic Rocks 3.1

Rock Types

Core, lamella, scanning electron microscope and whole-rock X-ray diffraction analysis indicate that there are three types of metamorphic rock reservoirs in the Pingxi area (Fig. 2).

Fig. 2. Characteristics of metamorphic rock types in the Pingxi area

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The first type is slate, and the rocks are mostly grey and greyish green, and the texture is well developed. The lamella analysis shows obvious congruent structures and residual quartz and feldspar. Scanning electron microscopy shows that clay minerals, quartz and feldspar have certain orientation. The image logging is characterized by a weak layered, low-light clip dark colour, seismic reflection characteristics, and poor continuity of the same axis. The mineral composition of slate is dominated by clay minerals accounting for more than 35%; followed by quartz, accounting for about 30%; followed by carbonate rock minerals mainly calcite, accounting for 6–15%. The feldspar is dominated by albite, small amount of potassium feldspar, accounting for 3– 5%, and the rest is small amount of pyroxene, anhydrite, barite, pyrite and siderite. The second category is “metamorphic limestone,” which is named “metamorphic limestone” because of its low metamorphic degree, less than 80% of calcite, low proportion compared with marble, and retains more characteristics of primary rock. “Metamorphic limestone” is the main rock type in the basement of Pingxi area. The rock colour is mostly grey, greyish-white and greenish-grey, and the block structure is dominant. The thin section analysis shows that the crystalline calcite content is high, and it is oriented with a small amount of sericite. The morphologies of crystalline calcite under scanning electron microscope are universal. The imaging logging shows blocky and highlights features; the seismic features are weakly chaotic reflections and have poor co-axial continuity. The main mineral composition of “metamorphic limestone” is calcite, accounting for 40–65%. Dolomite content is less, accounting for 300 °C in the Rock-Eval experiment. Delvaux et al. [11] made some modifications on the definition and normalized the experiment results of the amount S1 of free or adsorbed hydrocarbons and the amount S2 of hydrocarbons generated from kerogen pyrolysis. References [12–14] believed that S2 was hydrocarbons released during the pyrolysis of kerogen between 300 and 550 or 600 °C with a linear temperature gradient usually between 25 and 30 °C per minute. Wang et al. [15] found that the value of S2 after chloroform extraction was less than that before chloroform extraction through the comparison of a direct pyrolysis experiment on a source rock sample with a pyrolysis experiment on it after chloroform extraction. This indicates that there are some liquid hydrocarbons in S2; due to the adsorption and swelling action of organic matters and too high boiling point of part liquid hydrocarbons (boiling point of n-C18 302 °C), these liquid hydrocarbons cannot be evaporated out at −26.4 −26.4 to −27.3 −27.3 to −28.4 >5 5–4.3 4.3–3.5 >0.73 0.73–0.68 0.68–0.62

Very rich gas condensate 140–250 27–40 −43.4 to −45.1 −31.1 to −33.3 −28.4 to −30.1 3.5–2.4 0.62–0.52

Table 2. Division standard for grades of liquid-rich hydrocarbons in Duvernay shale Rich oil >250 >40 50

R% ¼ 5

(i) if RP  50 (ii) if RP > 50

R% ¼ 9

R% ¼ R% ¼

245 þ 9ðRP50Þ

RP

460 þ 15ðRP50Þ

RP Natural gas liquids R% ¼ 12:25 Sulfur R% ¼ 10:25 3 3 RP reference price in $ per 10 m ; R Royalty rate as a percentage

royalty/tax rates by the basic royalty/tax rate multiplied by the reduction factor, as follows: Royalty=Tax Rate ¼ Basic Rate  Basic Rate  Reduction Factor

ð1Þ

In addition, the tax preferential policy includes the producer cost of service allowance and Gas Cost Allowance. The producer cost of service allowance is intended to cover the Crown’s share of costs for gathering, dehydration and compression of raw gas and in some cases processing gas that is used as fuel in these activities. The Gas Cost Allowance (GCA) is a rate per 103 m3 of raw gas approved by the Royalty Administrator to offset the capital and operating costs associated with: (1) processing the Crown’s share of raw gas at a producer-owned gas plant and (2) transmission of the Crown’s share of residue gas through a producer-owned sales line.

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Fig. 2. Marketable gas royalty/tax base rates

3 Net Reserves Evaluation Method and Cash Flow Model of Tight Gas Project 3.1

Net Reserves Evaluation Method

Net reserves are recognized in situations where there is an economic interest and after deduction for any royalty owed to others. Royalties are typically paid to the owner of the mineral rights in exchange for the granting of the rights to extract and produce hydrocarbons. Net reserves refer to the share of total reserves available under the net economic interest of the contract, which is related to the economic parameters such as working interest, royalty and cost recovery and profit. The annual outputs in the output profiles of total reserves and net reserves are, respectively, called total production and net production. Calculation of net reserves: Rnet ¼

n X i¼1

Rnet i Qneti n Qgrossi WI

Qneti ¼

n  X

Qgrossi  WI



i¼1

Net reserves of contractor Time starting from current-year to (i) years in the future The net production of i year Project economic (or contractual) life in years The gross production of i year Working interest.

ð2Þ

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It can be seen from the formula (2) that the higher the output and oil price, the higher the net reserves and income of the contractor, as long as the project is kept running smoothly. Royalty volumes that are payable either in-kind or in monetary terms to the owner of the mineral rights. If it is paid in kind, the royalty volumes should be excluded from net reserves. If it is paid in cash, the royalty volumes can be booked by contractor, but the amount of the reserves will not affect the contractor’s cash flow [6, 7]. 3.2

Cash Flow Model

Figure 3 shows the cash flow model flow chart of contract and government under royalty & tax system. Total sales gas gross revenue refers to the gross income of marketable gas sales after deducting the corresponding expenses (such as transportation expense or other expenses, according to the sales contract). Net revenue after tax is calculated by the gross revenue deducted from the royalty, operating expenses, capital and abandonment costs, income tax and other taxes. The government’s income is the sum of the royalty, income tax and other taxes and profit sharing after tax. The contractor’s income is the corresponding profit sharing after tax.

Fig. 3. Cash flow model flowchart for sales gas project in British Columbia, Canada

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4 Influential Factors for Net Reserves and Net Present Value of Tight Gas Project Net reserves and net present value evaluation of tight gas project is a comprehensive work, the volumes of net reserves are not only affected by the technical factors, such as planning, development and production, but also related to the contract terms, transportation, sales and many other factors. The influential factors can be divided into four major factors as follows. 4.1

Technical Factors

4.1.1 Five-Year Plan Five-year plan refers to the production, well drilling, recompletion, the corresponding investment plan and supporting data (such as well location maps, structure maps and isopach maps) officially approved by the government. Detailed degree and credibility of the data directly affect the evaluation of PUD reserves (proved undeveloped reserves) and PDNP reserves (proved developed non-producing reserves). 4.1.2 Initial Production Initial production is the starting point of future output profile. The historical output data of the last few months in the annual evaluation have a great impact on the starting point, which will directly affect the future output profile and even the corresponding period. Therefore, there exists a strategy to raise and stabilize production adjacent to the data cut-off point, which has a positive impact on the evaluation of PD reserves (proved developed reserves). 4.1.3 Declining Rate Declining rate is an important parameter of dynamic method, mainly used for developed project. The reasonable determination of evaluation unit, declination type and curved shapes directly affect the prediction of PD reserves. The declining rate should be adjusted according to the actual situation of the project and the dynamic change of production, especially for the project during in the stage of increasing production or no steady declination. 4.1.4 Recovery Factor In the initial production stage or non-production area, dynamic method cannot be used because of insufficient production data. Under the circumstances, volumetric method is generally used to calculate PIIP (total petroleum initially in place), analogy with adjacent similar blocks or pilot experiments in the local area are used to determine the recovery factor, and then EUR (estimated ultimate recovery) is calculated. For the recovery factor of P1, it is usually required to provide a more rigorous demonstration data. If the secondary oil recovery is not implemented, the primary recovery factor is adopted [8, 9].

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Economic Factors

4.2.1 Opex and Economic Limit Opex includes material supplies, maintenance of well equipment and surface facilities, employee salary and management fee, etc. The economic limit refers to the minimum amount of production that can be paid for operating costs. Total reserves are determined by volumetric method, dynamic method and other methods, then the results should be measured and calculated by running economic model. If the cash flow obtained is positive after running the economic model, then the project has economic benefit. The time point of positive cash flow refers to the economic limit. The reserves are valid above the economic limit. Therefore, optimizing the Opex of oilfield, carrying out reasonable proportion and splitting of costs, may extend the economic limit point to some extent and have a positive impact on the evaluation of net reserves. 4.2.2 Taxes Under the royalty & tax system, the important factors that affect the net reserve and profit of oil companies are not only the technical factors, but also the taxes, mainly consists of royalty, asset tax, income tax, additional profit tax, export tax and other taxes [10]. In British Columbia (Canada), some tax rates are floating with the actual production and price, some taxes adopt fixed rate, and royalty rates are linked not only to productivity and price, but also to the drilling time, drilling depth, well type, well location and gas component. By analyzing various taxes and the impact on the economic benefit of oil and gas field, the rational controlling of royalty and taxes can realize the maximization of the interests of the contractors. 4.2.3 Price For the royalty & tax system, price changes have the positive correlation with net reserves, which directly affect the project’s benefits and the ultimate value of reserves. Low prices affect the economy of reserves, shorten the economic life of reserves, and reduce the net reserves and their values. When the prices rise, economic limits are likely to be extended, and net reserves and the value will rise accordingly. 4.3

Commercial Factors

4.3.1 Contract Restriction Limitations of the contract period. The reserves are the sum of future proposed output of a project in a certain contract period and economic limit. Close to the end of the contract period, if the contract is not deferred, even if the project is under good production situation and the economic recoverable resources underground is abundant, the reserves beyond the contract period will not be booked [11]. Limitations of contract terms. For the assessment of natural gas reserves, the corresponding sales contract is required under SEC rules, otherwise the reserves cannot be booked as P1 reserves even though the large reserves scale. If the sales contract is signed only for one year, contractor can book only one-year reserves, and the remaining predicted output will be deducted.

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4.3.2 Modification of Contract Significant changes in the terms of the contract significantly affect the economy of reserves. From 2014 to 2016, the major changes in oil prices directly led to some projects that are uneconomic and do not have reserves. By negotiating with governments to deal with low prices, changing some of the contract’s terms, it is possible to turn the uneconomic projects into economic benefits directly. 4.4

Engineering Factors

The integrity of oil and gas field surface engineering (such as infrastructure, pipeline, capacity of gas compressor, oil and gas processing plant, oil refinery and water treatment) and the length of time for putting into use impact the oil and gas transportation and productivity construction, directly affect the implementation capacity of development plan, thus influence the results of reserves evaluation.

5 Sensitivity Analysis The following example analyzes the sensitivity factors of X tight gas project under R&T system in British Columbia of Canada. The planned annual gas production and gas condensate production, respectively, are 50,000 MMCF and 2689 MMCFE in 2018. In the future 15 years, the project will increase the gas annual production to 80,000–100,000 MMCF, increase the gas condensate annual production to 4000–5000 MMCFE, then the production will be reduced progressively. The royalty is 26.86 CAD/MCF based on the present production situation, and the tax rate fluctuates during 18–14%. Oil prices are forecast Brent at 90 U$/barrel and gas prices are pegged to oil prices (Table 3).

Table 3. X tight gas project summary Project size

Gas production during RT term (since 2019.1.1) Gas condensate production during RT term (since 2019.1.1) Oil price Gas price Capex Opex Royalty Royalty rate

Annual gas production and gas condensate production in 2018, respectively, are 50,000 MMCF and 2689 MMCFE 2,349,080 MMCF 114,090 MMCFE Predicting oil price 90 U$/barrel 5.33 U$/MMCFE CAD 3265 million CAD 4460 million 26.86 CAD/MCF 14–18%

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According to the analysis on economic benefit index of X project, five main parameters were optimized, including tight gas production, gas condensate production, price, Capex and Opex. Assumption that other factors were constant, the single factor sensitivity analysis was carried out on NPV. The results can be summarized from Fig. 4 that tight gas production, price, Capex and Opex had significant effect on NPV of the project, and the price was the most sensitive factor and had the greatest effect on NPV. Tight gas production, gas condensate production and price were positively correlated with NPV. Capex and Opex had the negative correlation with NPV. Gas condensate production was a relatively insensitive factor due to its subordinate production. How to increase output is the key to this project in the case of limited Capex and Opex.

Fig. 4. Sensitive analysis of X tight gas project

6 Conclusions Net reserves evaluation of tight gas project is a comprehensive work, integrated with technical, economic, commercial and engineering factors, not only affected by the technical factors, such as gas reservoir parameters and development planning, but also related to the contract terms, Capex, Opex, price, taxes, tariff, sales and many other factors. Various related factors should be entirely considered, the key assessment elements should be grasped accurately, to make sure that the evaluation result of net reserves is reasonable and objective. For the tight gas project under the royalty & tax system in British Columbia (Canada), tight gas production, prices, Opex and Capex have significant effects on the net reserves and NPV of the assets. Annual evaluation works of net reserves often are confronted with different difficulties and challenges with the change of the production and development level, international oil price, the policy and situation of resource-host country government and local environment. Adequate analytical work should be

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carried out before the net reserves assessment, corresponding development and evaluation strategy should be formulated to realize the optimization and rationalization of net reserves and net present value of the project.

References 1. Heffernan K, Dawson FM. An overview of Canada’s natural gas resources. Canadian Society for Unconventional Gas, May 2010. 2. National Energy Board, Canada’s Energy Future 2017 Supplement: Natural Gas Production, 2018. 3. Yin X, Qi M, Sun D, et al. Income analysis of royalty and tax regime and project development strategy of oil and gas project. China Min Mag. 2012;21(08):42–4. 4. Young ED, Lasswell FM. Reserves reporting under modern fiscal agreements. IPTC 16514. 2013. 5. Young ED, McMichael CL. Evaluation of fiscal terms, reporting reserves, and financials. SPE 77510. 2002. 6. Petrochina Exploration & Production Company. Classification system and categorization principles of SEC/SPE for oil & gas resources and reserves. In: Proceedings of SEC rules for evaluating oil & gas reserves. Petroleum Industry Press, Beijing; 2012, p. 399–406. 7. SPE/AAPG/WPC/SPEE. Petroleum Resources Management System, 2007. 8. Society of Petroleum Engineers. Guidelines for application of the petroleum resources management system. American Society of Petroleum Engineers Inc.; 2011, p. 35–88. 9. Gaspar Ravagnani ATFS, Costa Lima GA, Barreto CEAG, Munerato FP, Schiozer DJ. Comparative analysis of optimal oil production strategy using royalty & tax and production sharing petroleum fiscal models. SPE 150907. 2012. 10. Dharmadji T, Parlindungan T. Fiscal regimes competitiveness comparison of oil and gas producing countries in the Asia Pacific Region: Australia, China, India, Indonesia and Malaysia. SPE 77912. 2002. 11. Yi Y, Lu B, Yuan R, et al. Features of SEC reserves estimation and existing problems in international cooperation project. Spec Oil Gas Reservoir. 2014;21.

A Case Study of Upscaling Extra-Fine Coalbed Methane Geological Model Lijiang Duan(&), Zhaohui Xia, and Liangchao Qu Asia-Pacific Department, PetroChina Research Institute of Petroleum Exploration & Development, Beijing, China {duanlj,xiazhui,quliangchao}@petrochina.com.cn

Abstract. Extra-fine geological model of the coalbed methane (CBM) field is not suitable for being adopted directly as a simulation model, and upscaling work is necessary. The main challenge of upscaling is to preserve important reservoir heterogeneities and flow characteristics of fine model, meanwhile ensure reasonable cell count. In study area, an extra-fine coal reservoir model was built, and 125 plies in 20 sublayers of six coal members were identified with an average single coal thickness of 0.46 m. Up-gridding was conducted from coal-member level to sublayer level and finally to coal-ply level. Various ways were adopted to estimate the results at each coarsening step. The optimal-layergrouping scheme was achieved by conducting only 20 plus up-gridding trials. The results show that compared with ply model, active cell count was reduced by 85.28%, and average production error was less than 3%. Some of the plies cannot be merged with adjacent plies indicating significant heterogeneity. Hierarchical up-gridding was used, which saves more layer-grouping trials. Six ways were adopted to analyse the up-gridding results, enabling the final layergrouping scheme is optimal. This paper should therefore be of interest to reservoir engineers facing a complex geo-model of CBM reservoir. Keywords: Upscale


Geological model
Coalbed methane
Surat basin

Copyright 2018, Shaanxi Petroleum Society. This paper was prepared for the presentation at the 2018 International Field Exploration and Development Conference in Xi’an, China, September 18–20 2018. This paper was selected for the presentation by the IFEDC Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the IFEDC Committee and are subject to correction by the author(s). The material does not necessarily reflect any position of the IFEDC Committee, its members. Papers presented at the Conference are subject to publication review by Professional Committee of Petroleum Engineering of Shaanxi Petroleum Society. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of Shaanxi Petroleum Society is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgement of IFEDC. Contact email: [email protected]. © Springer Nature Singapore Pte Ltd. 2020 J. Lin (ed.), Proceedings of the International Field Exploration and Development Conference 2018, Springer Series in Geomechanics and Geoengineering, https://doi.org/10.1007/978-981-13-7127-1_46

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1 Introduction Geological model built by geologist tends to be extra-fine to describe depositional cycles and internal architecture of the reservoir. However, this model cannot be used directly by reservoir engineer for production history matching and performance forecasting due to computationally expensive. Therefore, upscaling work is necessary. The main challenge of upscaling is to preserve important reservoir heterogeneities and flow characteristics of fine model, meanwhile ensure reasonable cell count. Upscaling process can be divided into two steps: (1) determining the manner of grouping fine cells to preserve inherent reservoir heterogeneity (this is called upgridding) and (2) reassigning reservoir properties of coarse cells using optimal property upscaling method to capture flow characteristics. In literatures, there are two major up-gridding methods: variance-based method and simulation-based method. The former method group cells having similar sweep efficiencies [1] or velocities [2] or pressure profiles [3] or effective permeabilities [4] through variance calculating of fine geo-model. It has the advantage of being fast. However, it is hard to ensure the complex fluid flow features in fine model could be accurately represented in coarse model. The latter method is directly based on the comparison of simulation results between fine and coarse models at each coarsening step [5]. It gives accurate results but too time-consuming to upscale extra-fine and complex geo-models. Coalbed methane (CBM) reservoir is more complex compared with conventional reservoir, and it is difficult to select representative parameters for calculating to describe reservoir flow features. Therefore, simulation-based method was used in this paper, but new measures were adopted to make the up-gridding process faster. For the property upscaling methods, more argues exist about permeability. After comparing the simulation results of various permeability upscaling methods, flowbased upscaling was recommended by Allan et al. [6] and Ma et al. [7]. Volumeweighted averaging method was used by King et al. [2], Hosseini and Kelkar [3] and Zhou and King [8]. Shehata et al. [9] found the optimal permeability upscaling method varies along with different scenarios, such as depletion process and water injection process. For making the simulation results of coarse model closer to that of fine model, different permeability upscaling techniques were investigated in this paper before upgridding process.

2 Fine Model of CBM Reservoir The example is from a gas field in Surat Basin, Australia. Coals in this gas field belong to Walloon subgroup of Jurassic, which are further divided into six coal measures (Kogan, Macalister, Wambo, Argyle, Upper Taroom and Condamine) from shallower to deeper. The relatively stable alluvial flood plain allows river channels to freely migrate and disturbs coal swamp development. The Walloon subgroup is characterized by carbonaceous mudstone, siltstone, minor sandstone and coal. The coal seams are generally thin and inter-bedded with siltstone and sandstone. By identifying depositional cycles and building isochronic stratigraphy frames, 20 sublayers were divided for

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these six coal members. And, 125 plies were further identified by conducting single coal-ply correlation, which were described in detail in Table 1. Table 1. Zone division of coal reservoir Coal member Kogan Macalister

Wambo

Argyle

Upper Taroom

Condamine

Sublayer name K1 K2 M3 M2 M1 W4 W3 W2 W1 A4 A3 A2 A1 UT4 UT3 UT2 UT1 C3 C2 C1

Sublayer number 2 3

4

4

4

3

Ply name K1*K3 K4*K6 M3-1*M3-6 M2-1*M2-8 M1-1*M2-8 W4-1*W4-5 W3-1*W3-9 W2-1*W2-6 W1-1*W1-8 A4-1*A4-9 A3-1*A3-8 A2-1*A2-8 A1-1*A1-6 UT4-1*UT4-6 UT3-1*UT3-6 UT2-1*UT2-7 UT1-1*UT1-5 C3-1*C3-6 C2-1*C2-4 C1-1*C1-4

Ply number 3 3 6 8 8 5 9 6 8 9 8 8 6 6 6 7 5 6 4 4

For capturing the complexity and heterogeneity of coal sediment, an extra-fine geological model with 125 plies (also named as ply-based model) was built. The model size is 2,824,173 cells (119  99  257) in total. The cells are 100 m in width and length. Considering the total 58 m thickness for 125 coal plies, the average coal thickness is 0.46 m which is stratigraphic. Due to the lateral discontinuous and relatively thin coal seams, vertical wells are optimal for development. For estimating the production performance of existing wells and find opportunity for infill wells, this extra-fine geo-model was built. The dynamic model was built with gas content, permeability, Langmuir volume, and Langmuir pressure from the correlations of actual measured data, and other parameters, such as relative permeability, porosity, sorption time and compressibility, from basin-wide analogue, rules-of-thumb or educated guesses. To reduce the number of active cell counts for minimizing the simulation runtime, some cells were deactivated, including Kogan coal measure (no perforation), inter-burden and over-burden. Through adjusting reservoir parameters, satisfactory matching results were achieved for both gas and water production on field level, as described by green line in Fig. 1. However, a runtime of 43.52 h was needed and unacceptable for the following

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Fig. 1. Comparison of observed production and simulated production on ply, sublayer, coalmember levels and optimal model

individual well history matching work. In this case, the upscaling was necessary to reduce simulation time.

3 Determination of Permeability Upscaling Technique In this paper, single-phase upscaling approach was adopted. In other words, relative permeability of the fine model was used directly in the simulation of coarse model. Five reservoir parameters (i.e. gas content, gas saturation, net-to-gross (NTG), porosity and permeability) were upscaled. The former four parameters are scalar quantity, so volume-weighted arithmetic averaging technique was recommended by most researchers [9, 10]. Permeability is a vector quantity, and more argues exist about the best upscaling technique. Therefore, seven upscaling techniques in PetrelTM were investigated, and the detailed items were listed in Table 2. We only focus on vertical up-gridding in this paper and keep the areal cells same as in fine geo-model. Ply-based model was up-gridded to both sublayer and coal-member levels, and the corresponding simulation results were indicated by grey line and deepsky-blue line, respectively (Fig. 1). During this process, flow-based harmonic averaging technique was used for permeability upscaling. It was found that the sublayerbased model has closer match results compared with that of ply-based model and the runtime is also reasonable (6.4 h). Hence, it was selected as the basis for the following permeability upscaling technique testing. Seven coarse models were created and four parameters were defined to analyse the simulation results: simulation runtime ratio,

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Table 2. Detailed information of seven permeability upscaling techniques and corresponding simulation results Sampling method

Averaging method

Runtime ratio (%)

Cum gas error (%)

Cum water error (%)

Flow-based

Harmonic average (HA) Finite difference (FD) Arithmeticharmonic (AH) Harmonicarithmetic (HA) CardwellParsons (CP) Arithmetic (A) Harmonic (H)

14.71

−0.57

−2.91

Average production error (%) 1.74

15.26

−0.57

−2.91

1.74

15.09

−1.03

−3.22

2.12

15.73

−1.03

−3.22

2.12

15.64

−1.03

−3.22

2.12

16.23 15.90

−0.54 −0.56

−2.95 −3.00

1.75 1.78

Directional average

Volume weighted

cumulative gas error, cumulative water error and average production error. Runtime ratio means the ratio of simulation runtime of coarse model and fine model. Cumulative gas and water errors were calculated by using Eq. (1). error ¼

Xc  Xf Xf

ð1Þ

where Xc is cumulative gas or water production of coarse model, MSCF or STB; Xf is cumulative gas or water production of fine model, MSCF or STB. By calculating the absolute value of cumulative gas and water errors and then averaging them, the average production error was attained. As shown in Table 2 and Fig. 2, by contrast to directional averaging technique, flow-based and volume-weighted averaging techniques have less average production errors. Flow-based harmonic averaging technique has the least runtime ratio and average production error among seven upscaling techniques. So, it was selected for the following up-gridding work.

4 Procedure of Up-Gridding Up-gridding was usually proceeded by iterating layers one by one [4], which needs more layer-grouping trials, and hence more computational time. In this paper, a new approach considering deposition cycles was proposed. In other words, up-gridding was conducted from coal-member level to sublayer level and finally to ply level.

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Average production error (%)

2.2 2.1

Directional average

AH

Volume weighted

CP HA

2.0 1.9 1.8 H 1.7 1.6 14.5

HA

A

FD

14.9

15.3

15.7

16.1

16.5

Run Time Ratio (%)

Fig. 2. Simulation results of different permeability upscaling techniques

4.1

Up-Gridding on Coal-Member Level

The sublayer-based model has a reasonable runtime and close matching results compared with that of ply-based model. Therefore, it was set as the basis for the following up-gridding work. The aim of up-gridding on coal-member level is to fast determine the layers with strong heterogeneity. Five coal members (i.e. Macalister, Wambo, Argyle, Upper Taroom and Condamine) were investigated excepting Kogan for no perforation. Though up-gridding workflow was described in Fig. 3, an example of Macalister coal member was used to explain it in detail.

Fig. 3. Up-gridding workflow on coal-member level

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(1) Upscale all three sublayers (M3, M2 and M1) to coal-member level, and keep the sublayers in other coal members unchanged. (2) Upscale properties and then create a simulation case. (3) Calculate cumulative gas and water errors. (4) Attain the average production error (Δ). (5) Judge whether all these three sublayers can be merged together by comparing Δ with the threshold value of 5%. (6) Repeat this procedure for the other four coal members. Five simulation runs were performed and the results are summarized in Table 3. It indicated that if all the sublayers in any of the four coal measures (i.e. Macalister, Wambo, Argyle and Condamine) were merged together, the simulated cumulative gas and water production of the coarse model are both lower than that of ply-based model, and the average production error are all less than 4%. But different phenomena were observed when merging all sublayers in Upper Taroom coal measure, and the simulated cumulative gas and water production of the coarse model are both higher compared with the corresponding values of ply-based model. The average production error is 5.02%, which is higher than the tolerance of engineering errors (5%), indicating that a major heterogeneity in fine model was homogenized. Therefore, the four sublayers in Upper Taroom coal measure (UT1, UT2, UT3 and UT4) cannot be merged.

Table 3. Comparisons of different up-gridding results on coal-member level Active cell Fine model Case 1 Case 2 Case 3 Case 4 Case 5

4.2

Active cell ratio (%)

Runtime ratio (%)

Cum gas error (%)

Cum water error (%)

Average production error (%)

20.95 19.58 19.58 19.58 20.89

13.76 12.39 15.85 11.72 13.81

−1.79 −3.20 −4.42 7.59 −5.38

−2.25 −0.05 −0.31 2.46 −2.07

2.02 1.63 2.06 5.02 3.72

839,294 175,805 164,351 164,332 164,332 175,321

Up-Gridding on Sublayer Level

Since the four sublayers in Upper Taroom coal measure cannot be merged together, several simulation cases were created to test whether the sublayer can be merged with adjacent sublayers individually, and the workflow was described in Fig. 4. Keeping all layers in Upper Taroom coal measure on sublayer level and others on coal-member level, a new simulation case (UTo) was created and the cumulative production error (Δ) was calculated. This case was set as the basis for the following upgridding work on sublayer level. Further merging UT1 and UT2 to create a simulation

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Fig. 4. Up-gridding workflow on sublayer level

case (UTa), the Δ value of UTa was calculated, and then the Δ values’ difference of UTa and UTo (named as Δ1) was attained. A judgment was conducted based on the comparison of the absolute value of Δ1 and threshold value of 1% to identify whether these two sublayers can be merged. If Δ1 is less than 1%, UT1 and UT2 can be merged. Otherwise, these two sublayers cannot be merged. Then, UT3 was merged with UT1 + UT2 to create a new simulation case (UTb), and same method was used to identify if these three sublayers could be merged together. The final step was to test whether UT4 can be merged with UT1 + UT2 + UT3. Four simulation cases were run and the results indicated that UT1 and UT2 can be merged together but UT3 and UT4 should be kept individually according to the judgment criterion discussed above. The detailed information was listed in Table 4.

Table 4. Comparisons of different up-gridding results on sublayer level Active cell

Active cell ratio (%)

Fine 839,294 model 87,912 10.47 UTo UTa 76,923 9.17 UTb 65,934 7.86 UTc 54,945 6.55

4.3

Runtime Cum gas Cum ratio (%) error (%) water error (%)

1.03 1.01 0.55 0.41

−2.14 −1.64 2.06 14.42

4.34 4.92 7.25 10.67

Average production error (%)

Difference of two cases (%)

3.24 3.28 4.65 12.54

0.04 1.37 7.89

Up-Gridding on Ply Level

Since UT3 and UT4 cannot be merged with each other and with the other two sublayers in Upper Taroom coal measure, further trials were done to identify if the ply in the same sublayer can be merged with adjacent plies.

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Keeping layers in UT3 and UT4 on ply level, UT1 and UT2 merged together, others on coal-member level, a new simulation case (UT34o) was created. The upgridding work on ply level was conducted following the workflow in Fig. 5. The layergrouping sequence for the 12 plies was from shallower to deeper (i.e. from UT4-1 to UT3-6). This workflow was same as that described in Fig. 4, excepting for two differences: 1) adopting 0.1% as an identifying criteria of merging adjacent layers. 2) honouring depositional cycle constraint of sublayer during up-gridding process. After running five cases (from UT34a to UT34e) to test the plies in UT4, the sixth simulation case (UT34f) was created by further merging UT3-1 and UT3-2 on the base that all piles in UT4 were merged together, rather than merging the total seven plies from UT41 to UT3-1. Hence, ten trials were conducted.

Fig. 5. Up-gridding workflow on ply level

The simulation results were described in Table 5. Based on the identifying criterion of merging adjacent plies, it revealed that UT4-1, UT4-2, UT4-3, UT4-4 can be merged together, UT4-5, UT4-6, UT3-1, UT3-3, UT3-3, UT3-4 should be kept individually, and UT3-5 and UT3-6 can be merged.

5 Results and Discussion The final layer-grouping scheme was that layers in Kogan, Macalister, Wambo, Argyle and Condamine were on coal-member level, and layers in Upper Taroom were optimized into nine zones, as described in Table 6. A new dynamic model was built based on this scheme (named as the optimal model), and the simulation results showed that the active cell count was reduced by 85.28%, runtime was reduced by 98.78%, cumulative gas and water errors were −1.98 and 3.90%, respectively, by contrast to the ply-based model. When putting the simulation results of the optimal model, sublayer level model and coal-member level model together, it was found that coal-member level model has the

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Fine model UT34o UT34a UT34b UT34c UT34d UT34e UT34f UT34g UT34h UT34i UT34j

Active cell ratio (%)

Runtime Cum gas Cum ratio (%) error (%) water error (%)

17.93 16.84 15.75 14.62 13.59 12.61 9.60 9.52 9.20 9.17 9.17

1.72 1.52 1.40 1.19 1.10 1.03 0.78 0.78 0.78 1.22 1.01

Average production error (%)

Difference of two cases (%)

3.01 3.01 2.92 2.97 2.66 3.01 3.84 3.27 3.47 3.35 3.28

0.00 −0.08 0.05 −0.31 0.35 0.83 −0.57 0.21 −0.12 −0.07

839,294 150,499 141,378 132,227 122,677 114,042 105,844 80,601 79,899 77,224 76,927 76,923

−2.94 −2.75 −2.29 −2.10 −1.30 −1.68 −4.77 −1.56 −0.88 0.08 −1.64

3.09 3.27 3.56 3.85 4.03 4.34 2.90 4.97 6.07 6.62 4.92

Table 6. Comparison of layer-grouping schemes Original zone division Kogan Macalister Wambo Argyle Upper Taroom

Condamine

Final zone division Kogan Macalister Wambo Argyle UT4-1*UT4-4 UT4-5 UT4-6 UT3-1 UT3-2 UT3-3 UT3-4 UT3-5*UT3-6 UT1 + UT2 Condamine

biggest average production error, indicating significant loss of heterogeneity and flow characteristics of fine model. Compared with the sublayer level model, the optimal model reduced the simulation runtime ratio by more than a factor of 10 from 14.71 to 1.22%, and introduced no more than 2% error in average cumulative production (Fig. 1 and Table 7). This is a very good result which provides us with the foundation required for the following individual well history matching work.

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Table 7. Comparisons of different up-gridding results on ply, sublayer, coal-member levels and optimal model Active cell ratio (%)

Runtime ratio (%)

Cum gas error (%)

Cum water error (%)

Average production error (%)

197,296 54,945

23.51 6.55

14.71 0.41

−0.57 14.42

−2.93 10.67

1.75 12.54

123,535

14.72

1.22

−1.98

3.90

2.94

Active cell Fine model Sublayer Coal member Optimal

839,294

After putting all the up-gridding simulation results together, it was found that as active cell ratio decreased, runtime ratio deceased and the trend can be described by an exponent formula (Fig. 6). With decreasing active cell ratio, cumulative water error increased linearly, and most error values are positive. There is no obvious relationship between cumulative gas error and active cell ratio, and most error values are negative. In other words, layers up-gridding tended to overestimate water production and underestimate gas production for CBM reservoir (Figs. 7 and 8).

Fig. 6. Plot of runtime ratio versus active cell ratio

Layer up-gridding inevitably combines coal and non-coal, which overestimate the lateral continuity of coal. An example from six coal plies of UT4 sublayer can be used to illustrate this issue. As indicated in Fig. 9, the coal was only distributed in part of study area with thickness varying from 0 to 3.03 m. And the average thickness is 0.6 m. After combining these six plies together, the distribution of coal covers all the study area with the thickness varying from 0 to 8.48 m, as shown in Fig. 10. And the average thickness is 2.8 m. The comparison of cell thickness distribution in fine and

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Fig. 7. Plot of cumulative water errors versus active cell ratio

Fig. 8. Plot of cumulative water errors versus active cell ratio

coarse models was displayed by a histogram as shown in Fig. 11, and an obvious difference can be observed. In other words, the loss of heterogeneity in fine model is significant. During layer upscaling process, the loss of reservoir heterogeneity is inevitable. Three threshold values of 5, 1 and 0.1% were adopted, respectively, at each coarsening step on coal member, sublayer and ply levels to preserve critical level of heterogeneity. Total upscaling errors are caused by homogenization and discretization, and the impact of these two factors is opposed. The dynamic response of coarse model is a complex function of reservoir and simulation parameters [10]. By contrast to conventional reservoir, most gases are adsorbed in coal reservoir, which is controlled by pressure and saturation. That is to say, CBM reservoir is more complex than conventional reservoir. So, a multi-parameter criterion in this paper was used to analyse upscaling results, enabling the final layer-grouping scheme is optimal.

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Fig. 9. Thickness maps of six coal plies in UT4

Fig. 10. Thickness map of UT4

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Fig. 11. Thickness histogram comparison of layers in UT4

6 Conclusions An extra-fine CBM geological model with 125 plies was upscaled by conducting only 20 plus layer-grouping trials. Compared with fine model, the active cell count was reduced by 85.28%, runtime was reduced by 98.78%, cumulative gas and water errors were −1.98% and 3.90%, respectively. The key point of this successful work lies in that important strategies were adopted in property upscaling and up-gridding processes. Seven permeability upscaling techniques were investigated, and the flow-based harmonic averaging method was deemed as the best due to its shortest simulation runtime and least average production error. The up-gridding work was conducted in three levels (i.e. from coal-member level to sublayer level to ply level), and different layer-grouping workflows were used. Three layer-merging thresholds of 5, 1 and 0.1% were used in these three stages. Multiple measures were taken to estimate upscaling results, such as active cell ratio, cumulative gas and water errors, simulation runtime ratio, areal map and histogram, to ensure the final layer-grouping scheme is optimal.

References 1. Stern D, Dawson AG. A technique for generating reservoir simulation grids to preserve geologic heterogeneity. In: SPE 51942, presented at reservoir simulation symposium, 14–17 Feb 1999. 2. King MJ, Burn KS, Wang P, et al. Optimal coarsening of 3D reservoir models for flow simulation [A]. In: SPE 95759, presented at the annual technical conference and exhibition, 9–12 Oct 2005. 3. Hosseini SA, Kelkar M. Analytical up-gridding method to preserve dynamic flow behaviour [A]. In: SPE 116113, presented at the annual technical conference and exhibition, 21–24 Sept 2008. 4. Kelkar M, Atiq M. Up-gridding method for tight gas reservoir [A]. In: SPE 133301, presented at the annual technical conference and exhibition, 19–22 Sept 2010.

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5. Suzuki K, Asada K, Yoshida K, et al. Accelerated history matching through process independent scale-up techniques in a giant carbonate reservoir [A]. In: SPE 87012, presented at the Asia Pacific conference on integrated modeling for asset management, 29–30 Mar 2004. 6. Allam FA, EI-Banbi AH, Bustami SS, et al. History match tuning through different upscaling algorithms [A]. SPE 90292, presented at the annual technical conference and exhibition, 26– 29 Sept 2004. 7. Ma E, Ryzhov S, Wang Y, et al. Answering the challenge of up-scaling at 900 million-cells static model to a dynamic model—greater Burgan field, Kuwait [A]. In: SPE 164187, presented at the middle east oil and gas show and conference, 10–13 Mar 2013. 8. Zhou Y, King MJ. Improved upscaling for flow simulation of tight gas reservoir models [A]. In: SPE 147355, presented at the annual technical conference and exhibition, 30 Oct–2 Nov 2011. 9. Shehata AM, EI-Banbi AH, Sayyouh MH. Proper selection of upscaling techniques for different production processes [A]. In: SPE 150863, presented at the North Africa technical conference and exhibition, 20–22 Feb 2012. 10. Sablok R, Aziz K. Upscaling and discretization errors in reservoir simulation [A]. In: SPE 93372, presented at the reservoir simulation symposium, 31 Jan–2 Feb 2005.

The Challenges and Key Technology of Drilling Safety in the Area of the Arctic Yongqi Ma(&), Jin Yang, Pengtian Feng, and Can Zhang College of Petroleum Engineering, China University of Petroleum, 18 Fuxue Road, Changping, Beijing, China [email protected], [email protected]

Abstract. The Arctic is rich in oil and gas resources, which has been the focus on international oil petroleum companies presently. Understanding the challenges and key technologies of drilling safety in this area is of great importance for promoting safe and making high efficient development of oil and gas resources. Through a large number of literature research and field investigation, Arctic drilling safety key technologies as well as main research progress have been analyzed in domestic and abroad and have arrived at the following conclusions: the primary challenges for oil and gas exploration and development of Arctic include harsh operating environment, long-distance logistic support, and stringent environmental requirements. The investigation results indicate that main research directions for the Arctic oil and gas exploration and development should include long-distance icebreaker safeguard ship, ice monitoring and management system, the assessment and control of the disaster or risk, low-temperature drilling fluid system, which are the key technologies for the high efficiency and safe development of oil and gas resources in cold water area of the Arctic. Some exploratory viewpoints and recommendations for the Arctic oil and gas exploration and development on drilling safety are also proposed. Keywords: Arctic


Drilling safety
Logistic support
Icebreaker

Copyright 2018, Shaanxi Petroleum Society. This paper was prepared for presentation at the 2018 International Field Exploration and Development Conference in Xi’an, China, 18–20 September, 2018. This paper was selected for presentation by the IFEDC Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the IFEDC Committee and are subject to correction by the author(s). The material does not necessarily reflect any position of the IFEDC Committee, its members. Papers presented at the Conference are subject to publication review by Professional Committee of Petroleum Engineering of Shaanxi Petroleum Society. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of Shaanxi Petroleum Society is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of IFEDC. Contact email: [email protected]. © Springer Nature Singapore Pte Ltd. 2020 J. Lin (ed.), Proceedings of the International Field Exploration and Development Conference 2018, Springer Series in Geomechanics and Geoengineering, https://doi.org/10.1007/978-981-13-7127-1_48

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1 Introduction About 22% of the total unconfirmed conventional oil and gas in the world is buried in the Arctic region where the level of Arctic drilling technology is related to the exploration and development of Arctic oil and gas [1]. For Arctic drilling technology, drilling environmental conditions are become more complicated by factors such as ultra-low temperatures, ice floes, snowstorms, permafrost, which are prone to technical problems that are difficult to overcome in conventional drilling engineering. Therefore, Arctic drilling technology is affecting the future globally energy security [2]. The Arctic oil and gas resources are abundant. It is estimated that the Arctic oil resources account for about 25% of the world’s proven crude oil reserves, and natural gas accounts for 41% of the world’s natural gas reserves. It is still in the early stage of exploration. According to the US Geological Survey (USGS) report in 2009, the Arctic crude oil reserves are 120  108 m3, and the natural gas reserves are 47  1014 m3, which respectively account for 13 and 30% of the world’s unrecognized resources (Figs. 1 and 2), and it is estimated that 84% of oil and gas reserves are buried in the seabed [3]. The Arctic has been discovered totally of 439 types of oil and gas fields still in 2014. It is most obviously achieved that Russia’s oil and gas exploration discovered the total of 245 oil and gas fields among Arctic country, which accumulative output oil reaches 30  108 m3, and gas reaches 1.11  1014 m3. Thus, the Arctic oil and gas resources are an important area for future oil and gas exploration, because of it very potential and exploration prospects [4]. At present, only a few countries such as Russia, the USA, and Norway have conducted Arctic drilling operations, among which Russia has rich experience in Arctic drilling technology and operations. Although some

Fig. 1. Arctic oil reserve distribution map

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Fig. 2. Arctic natural gas reserves map

breakthroughs have been made in casing drilling, cryogenic drilling fluids, and cementing, the safety technology for Arctic drilling is not mature enough and there is deficient of systematic safety and security system. Therefore, it summarizes that the Arctic drilling faced main challenges by a large number of literature research, and which analysis of existing Arctic drilling safety critical equipment and technology status.

2 Drilling Technology Safety Challenges of Arctic 2.1

Operating Environment Challenges

Arctic offshore drilling has encountered a great safety risk in the Arctic due to the factors of extremely cold temperatures, snowstorms, and sea ice. The average annual temperature in January is between −20 and −40 °C, which not only threatens the life safety and increases the difficulty of platform operation, but also causes the rig equipment to easily undergo brittle damage and difficult to operate normally. Blizzard will cause displacement of the drilling vessel, which will cause deformation and vortexinduced vibration of the riser, posing a great challenge to its strength and safety. Ice floes also further limit the rig’s loading strength and operating time [5]. The harsh

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environment and extremely short operating time put forward higher requirements on the reliability of shallow drilling technology and well control facilities. 2.2

Vulnerable Ecology Challenges

Because the ecology of the Arctic is vulnerable. Once a catastrophic accident occurs during shallow drilling, damage to the drilling facilities and oil and gas leaks will cause serious damage to the ecological environment. First, the Arctic region will make traditional anti-leakage technologies such as the construction of oil screens difficult to achieve, crude oil cleaning is very difficult; Second, leakage oil leads to a large number of biological deaths, while the Arctic lacking sunlight, cold weather, oil may be sealed in the ice. It is long time that environment needs to be diluted or degraded oil, which will cause long-term pollution to the population and ecological environment in the area [6]. 2.3

Arctic Shallow Challenges

In the Arctic where are widely distributed the frozen sea and natural gas hydrates (Fig. 3) [2]. The permafrost region and on the seabed, natural gas hydrates exist in metastable states and are easily decomposed in the Arctic. It was generated a large amount of problems such as free gas and free water, increasing the pore pressure of the sedimentary layers, reducing the cementation strength of the seafloor formation, forming shallow gas/shallow layers. As a result, the shear strength and load carrying capacity of the gas/water deposits are reduced, possibly leading to geological disasters such as landslides and ground subsidence. Once drilled, it may also lead to gas/water impact on the wellbore and uplift, resulting in instability of wellbore and destruction of drilling facilities. In severe cases, it will lead to catastrophic accidents such as blowouts and explosions [7].

3 Arctic Drilling Safety Equipment 3.1

Icebreaker

The icebreaker is a special type of vessel used to break ice, open up navigation channels, and protect the safe operation of drilling platforms. Its characteristics include a wide body, small aspect ratio, high overall strength, and high power. The rigidity of the bow and tailwater zone is strengthened. The power plant uses a twin-shaft, multipropeller device [8]. Icebreaking mainly involves icebreaking in two ways: (1) If the thickness of the ice layer is less than 1.5 m, “continuous” icebreaking is used to break the ice using the impact of the bow. (2) If the ice layer is thicker, the “impact type” is used to break the ice, and the bow section squeezes the ice layer to break the ice. Icebreakers are operational safety guarantees for offshore oil and gas development in the Arctic region, which related to platform safety and logistics support [9].

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Fig. 3. Arctic permafrost and hydrate distribution map

At present, from the perspective of the number of Arctic icebreakers globally, there are about 51 icebreakers worldwide. Russia has a major advantage with 18 icebreakers, including 7 nuclear power, 7 diesel power generation, 4 shaft-line power generation diesel-electric icebreakers in Finland and Sweden; and 6 icebreakers in Canada, including 5 diesel power generation, Shaft power generation 1; USA 4 diesel power icebreaker; China, Norway, Japan, Germany are a diesel power icebreaker [10]. 3.2

Arctic Remote Supply Vessel

Logistical support is critical for safe drilling operations in the Arctic, and remote supply vessels are the key to ensuring safe operations. Firstly, it is necessary to ensure the continuous supply of materials during drilling to achieve smooth development of the oil field due to the characteristics of effective drilling, short drilling time, high drilling cost, and high risk; Secondly, because of the supply vessels passing through the ice area, it is resistant to the supply vessels, load strength, icebreaking capacity and other properties put forward higher requirements [7]. Judging from available information, there are few types of Arctic supply vessels in the world, of which the representative is the ARCC (Aker Arctic Technology)-developed “ARC105” icebreaker supply vessel, which is mainly used for offshore platforms and drilling, which provide materials and equipment to perform icebreaking/ice management operations. It has preliminary fire prevention and emergency rescue capabilities. It was provided rescue and guardian services for the installation of marine structures [11].

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Ice Float Monitoring System

Arctic sea ice can cover up to three-quarters of the entire area. Even in summer, at least half of the area is covered by floating ice. Ice floes, thickness up to 2–3 m, average lifespan 4a, can accumulate and form huge ice floes under the action of wind and currents, often moving for several hundred kilometers [6]. It poses a great challenge to the safety of Arctic drilling. The monitoring of ice through coastal radars, icebreakers, satellite remote sensing and other means to monitor sea ice conditions, mainly to provide reliable sea ice information for winter shipping. The exploration of oil and gas in the Arctic requires that the drilling platform maintains direction under the bad weather and the impact of ice floe. Therefore, Ice Float Monitoring System is usually used to control the ice that threatens the platform within 2 km, which mainly include ice defense systems and ice management systems [12]. The purpose of the ice defense system is to prevent ice floes threatening drilling equipment. It is predicted that the drift ice trajectory mainly through field experience, weather forecast, ice statistics, and satellite remote sensing to ensure the safe operation of the platform. Artificial observation and shipborne radar, satellite imaging and other measures provide real-time images of ice floe, tracking any ice floes that pose a potential threat to the platform. Ice management systems require the use of physical icebreaker intervention to tow, displace, or break ice floes to prevent ice floes from entering the platform’s safe operating radius that is calculated by multiplying the safety pause operation time by the average drift speed of the ice floe. If the ice floe enters the penalty zone, physical intervention is initiated and the floating rig begins to transfer to the safe zone. In this case, The ice management system was started to actively destroy ice floes that entered the restricted area and the hazard level was controlled within the platform.

4 Arctic Drilling Safety Key Technologies 4.1

Low-Temperature Drilling Fluid System

In Arctic sea drilling operations, since the Arctic drilling environment temperature is below zero, it has a great influence on the rheology of the drilling fluid, which increases the viscosity of the drilling fluid and generates a gel effect, and generates high frictional resistance in the wellbore, which result the risk of large sleeve shoes being pressed open [13]. This requires that the drilling fluid must have good rheological properties, dynamic shearing force, and water loss to achieve flushing and stabilizing the wellbore. It also avoids to the heat of the drilling fluid being transferred to the formation during the cycle, which may result in the collapse of the formation. When drilling in the frozen soil if the drilling fluid has insufficient anti-low temperature capability, it will cause the fluid to freeze and lose fluidity, collapse the wellbore, and destroy the orifice. Especially when drilling natural gas hydrate formations may result in dangerous conditions such as the decomposition of natural gas hydrates and formation instability will occur. The types of Arctic drilling fluids currently used are mainly classified into waterbased and oil-based drilling fluids. The water-based drilling fluid is a drilling fluid with continuous fluid medium. It is mainly composed of low-solid polymer and solid-free polymer drilling fluid [14], which mainly composed of solid-free polymer drilling fluid,

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low-temperature resistant medium, borehole stabilizer, inorganic electrolyte, fluid loss reducer. Low-temperature medium mainly contains low molecular weight alcohols, such as methanol, ethanol, propanol, and other inorganic electrolyte salts as the main antifreeze. Wellbore stabilizers include polyvinyl alcohol (PVA), polyacrylamide (PAM), and the like. The inorganic electrolyte contains NaCl and KCl. Fluid loss control agents include sodium carboxymethyl cellulose (Na-CMC) and potassium humate (KHm); Oil-based drilling fluids use oil as the continuous phase, usually based on hydrocarbons such as jet fuel or diesel, add oil, ethylene glycol solution, inorganic salts, surfactants, and other substances composed of oil-based drilling fluid system [15]. However, oil-based drilling fluids have high permeability, especially in drilling cracked formations, which can cause formation pollution. With the increasing environmental protection requirements for Arctic oil development, water-based drilling fluids will gradually replace oil-based drilling fluids [9]. 4.2

Shallow Layers Drilling Techniques

There are a numerous of permafrost and natural gas hydrates in the Arctic shallow stratum. As the conditions of temperature and pressure change during the drilling process, the hydrates are easily decomposed and the volume rapidly expands to resulting in drilling accidents such as kicks and blowouts, which seriously affect job safe [13]. In terms of drilling technology, gas hydrate formation drilling is dominated by decomposition suppression drilling technology that mainly increases the drilling fluid density to increase the pressure in the well, cool the drilling fluid, and adjust the relevant drilling parameters to maintain the gas hydrate phase equilibrium. It can temporarily inhibit the decomposition of natural gas hydrates though increase the hydrostatic pressure at the bottom of the well. Cooling the drilling fluid to the lowest possible temperature through a heat exchanger in the ground mud pool also suppresses the decomposition of natural gas hydrates [16]. Foreign studies have shown that by adding a certain amount of chemical reagents such as lecithin, polymer, or PVP to the drilling fluid, the drilling fluid can be adsorbed on the surface of natural gas hydrates that the rate of decomposition can be slowed down; In well control [17], the potential threats to shallow layers are dealt with mainly by optimizing well structure and designing shallow gas treatment measures before drilling, including 26 in casing piped into the shallow gas layer, using double-stage cementing to seal the shallow gas sand layer, using a plurality of blowout preventers with different sizes and pressure levels to form a BOP system, installing a diverter. Russia adopts controlled pressure drilling technology to complete safe drilling of shallow layers. 4.3

Arctic Disaster Risk Assessment and Control Technology

The key to risk assessment and control of Arctic disasters is to improve safety and reduce non-productive time. The solutions proposed by foreign companies for Arctic drilling risk control mainly include the enhancement of well control and management, which use of controlled pressure drilling technology and the strengthening of geology information analysis during drilling [18].

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(1) Controlled Pressure Drilling System This system closely monitoring the pressures of the following six operating processes to achieve drilling pressure control: ① ② ③ ④ ⑤ ⑥

Drilling and circulation process; Drilling fluid non-cyclical state (if connected to single) Implementation of gate control process; Casing process; Cementing process; Completion process.

In the case of shallow complex formations, the measurement of the downhole conditions while drilling is conducted to enhance data acquisition and processing control, which accurately predict the pressure change from the bottom of the well so that maintain the relative stability of the bottomhole pressure during the drilling process. This technology can effectively prevent the risk of shallow gas invading wellbore and shaft wall collapse, which achieve safe and efficient drilling and increase the profitability of a single well. Control pressure drilling data acquisition and processing control diagram shown in Fig. 4.

Fig. 4. Controlled drilling data acquisition and processing control schematic

(2) Drilling Geological Information Analysis System This technology mainly consists of GC-TRACER gas analyzer, SRA source rock analysis, SRA-portable pyrolysis device (Fig. 5), gas extraction membrane device and other mobile data analysis and processing center. It can collect information and real-

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time analysis of cuttings during the drilling process. It also qualitative assessment of the nature of the rock, the total content of organic hydrocarbons, fluid properties, etc., which was conducted to timely obtain the characteristics of the layers. and the gas collection membrane device (Fig. 6) can analyze the downhole gas that compared with the actual gas concentration in the drilling fluid, which will predict whether there is a risk of gas uplift in the shallow layer and minimizes the geological risk [19].

Fig. 5. SRA—portable pyrolysis device

Fig. 6. Gas extraction membrane system

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This technology has successfully operated more than 700 wells in the Arctic region, including more than 500 wells for stationary platform operations, more than 200 wells for semi-submersible drilling platforms, and 32 wells for power-operated drilling rigs, among which, The throttle manifold controlled by the programming controller has been well applied in the operation of 108 wells.

5 Development Trends and Prospects Arctic oil and gas development is a huge system project. The application of Arctic drilling technology and equipment is a key factor in the successful development of Arctic oil and gas resources. The difficulties encountered in the development of the Arctic oil and gas are mainly due to high drilling costs, short working hours, and harsh environmental conditions. To solve these problems, we need to learn from the experience of successful deepwater drilling operations. In currently, the development trend of Arctic equipment includes: (1) Research and development of drilling rigs or supply ships with strong icebreaking capabilities to enhance the replenishment capacity and ensure the successful completion of the subsequent operations. (2) The drilling operation adopts automatic design to reduce the operator’s work efficiency. Drill floor operation adopts a new type of continuous tripping device and double derrick system, which can effectively shorten the non-operation time. (3) With the continuous development of drilling equipment automation and intelligent technologies, the development of key equipment such as Arctic special exploration/monitoring equipment, cryogenic riser systems, underwater operating robots, and dynamic positioning systems will be accelerated. (4) The drilling equipment adopts a modular design, which is convenient for installation and maintenance and greatly reduces the construction period. In brief, the successful exploitation of Arctic oil and gas requires the cooperation of multiple equipment technologies. Only by continuous exploration, can we solve the problems encountered in the exploration and development of Arctic oil. I believe that Arctic oil development can effectively solve global energy shortages, situation in the future.

References 1. Zhenrui B, Mingyan L. Potential of oil and gas resources in the Arctic and their exploration and development trends. Contemp Petrol Petrochem. 2011;19(9):39–44. 2. Haowu L, Xiaoguang T. Exploration potential analysis of oil and gas resource in Arctic regions. China Petrol Explor. 2010;15(3):73–82. 3. Kipker, T, Gmbh B. Drilling rigs in Arctic deep temperature environments: design an operation challenges. OTC. 2011:22093. 4. Kai Z. Arctic offshore drilling patterns and development trends. Neijiang Sci. 2016;2:71–3, 75.

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5. Skeie G, Bjcrnbom M, Skeie E. High resolution oil spill response planning for operations in a sensitive Arctic environment: sharing information between operators, national authorities, local oil spill response groups and the general public. In: SPE international health, safety & environment conference. 2006. 6. Aggarwal R, D’souza R. Deepwater Arctic—technical challenges and solutions. In: Otc arctic technology conference offshore technology conference. 2011. 7. Qi S, Guodong J. Analysis of the status quo and development trend of polar drilling equipment. Oil Drill Technol. 2012;40(6):43–6. 8. Quan S, Yanping Z. Icebreaker technology and several icebreaking methods. Navig Technol. 2010;1:5–7. 9. Jian Z, Wendong H. Status quo of polar icebreaker and its development countermeasures in China. China Water Transport Mon. 2016;16(5):47–50. 10. Johnson GW, Gaylord AG. Development of the Arctic research mapping application (ARMAP): interoperability challenges and solutions. Comput Geosci. 2011;37(11):1735–42. 11. Baojiang S. Arctic deep water drilling equipment and development prospects. Oil Drill Technol. 2013;41(3):7–13. 12. Pilisi N, Maes M. Deepwater drilling for Arctic oil and gas resources development: a conceptual study in the Beaufort sea. In: OTC Arctic technology conference. Offshore technology conference. 2011. 13. Ling Z, Guosheng J. A review of the characteristics of low temperature formation drilling and the status of drilling fluid technology. Drill Fluids Complet. 2006;23(4):69–72. 14. Vasilyev H, Б Б. Ice drilling mechanical drilling technology. China University of Geosciences Press; 1998. 15. Fenglin T, Кyдpяшoв Б. On-ice drilling technology in Antarctica, Russia. Geol Sci Technol Inf. 1999;s1:4–7. 16. Guosheng J, Fulong N. Decomposition inhibition and induced decomposition of natural gas hydrate during drilling process. Geol Prospect. 2001;37(6):86–7. 17. Yuanbiao L. Well control case analysis and technical measures. Industry. 2016;4:00286. 18. Lars B, Knut Ø. Application of the iNTeg-risk emerging risk management framework (ERMF) for drilling in Arctic. 2014. 19. Bergan HH. Risk analysis of well control operations considering Arctic environmental conditions[D]. UiT The Arctic University of Norway, 2015.

Author Biography Yongqi Ma (1991–), male, master, mainly engaged in polar drilling, ocean engineering structural analysis direction.

Spectral Shaping Technology and its Application for Dense-Gas Dessert Prediction on Songliao Basin Hong-wei Deng, Yi Bao(&), Jiang-yun Pei, Hui-tian Lan, and Ji-feng Ding Seismic Data Processing and Interpretation Center, Exploration and Development Research Institute of Daqing Oilfield Company Ltd. CNPC, Ranghulu District, Daqing 163712, Heilongjiang, China [email protected]

Abstract. In Anda-Songzhan area, the dense sandy gravel of Shahezi formation is generally gas-bearing, which is a key field of natural-gas reserve replacement in Songliao Basin. However, the resolution of deep seismic data is low, so it is difficult to meet the accuracy requirements of dessert prediction in unconventional reservoirs. On the basis of amplitude-preserving imaging processing, we count the global wavelet for poststack anti-Q filtered seismic records, get the global filter operator by shaping the global wavelet with the expected output wavelet, and obtain the seismic records of frequency extension by making convolution the operator with the poststack data. After processing, the main frequency of data is increased by 14 Hz, and the average coincidence rate of sandstone “dessert area” selected by combining multiple attributes with relative wave impedance inversion is increased from 67 to 80%. It supports the deployment of 7 exploration wells in this area and provides strong technical support for increasing storage and production in unconventional fields. Keywords: Unconventional reservoirs prediction
Songliao Basin
Dense gas




Spectral shaping




Desserts

Copyright 2018, Shaanxi Petroleum Society. This paper was prepared for presentation at the 2018 International Field Exploration and Development Conference in Xi’an, China, 18–20 September, 2018. This paper was selected for presentation by the IFEDC Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the IFEDC Committee and are subject to correction by the author(s). The material does not necessarily reflect any position of the IFEDC Committee, its members. Papers presented at the Conference are subject to publication review by Professional Committee of Petroleum Engineering of Shaanxi Petroleum Society. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of Shaanxi Petroleum Society is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of IFEDC. Contact email: [email protected]. © Springer Nature Singapore Pte Ltd. 2020 J. Lin (ed.), Proceedings of the International Field Exploration and Development Conference 2018, Springer Series in Geomechanics and Geoengineering, https://doi.org/10.1007/978-981-13-7127-1_49

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1 Introduction The successive success of well S9 and well S12 in Anda-Songzhan area reveals a good prospect for exploration of dense sandy gravel gas in the deep Shahezi formation and will also become a key field for the replacement of deep gas reserves in Songliao Basin. Due to the complexity of the gas reservoir itself, the exploration and deployment are still facing with a series of difficulties, although some progress has been made in seismic exploration of deep dense sandy gravel gas reservoirs. After two acquisitions and multiple rounds of processing, the imaging accuracy and resolution of deep seismic data are still difficult to meet the requirements of subdivision layer structural interpretation and reservoir prediction accuracy, and this directly leads to unclear understanding of sedimentary facies and reservoir distribution, which results in difficult prediction of desserts. As shown in Fig. 1, the latest collected data after processing has low vertical resolution and the main frequency is about 25 Hz. According to the empirical algorithm with vertical resolution of about 1/4 wavelength, the vertical resolution of the data is about 40–50 m. The seismic identification of single sand body is difficult, and there are some problems such as insufficient seismic imaging accuracy, unclear fault breakpoints between layers, low signal-to-noise ratio of data and unclear relationship between some formation reflection wave groups. The full coverage area of the research area is 200 km2, and the period of dessert prediction is short. Therefore, a processing method with good effect frequency extension and efficient in computation must be found to improve the quality of seismic data.

Fig. 1. RTM migration section in Anda-Songzhan (Line_262)

2 Principles There are many methods to improve the vertical resolution of seismic data, such as inverse Q filter, spectral decomposition technique represented by generalized S transform, spectrum shaping technique and prestack time migration technology of viscoelastic media unique to Daqing Research Institute, etc. The following is a brief description of the principles of these techniques.

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3 Inverse Q filter When plane wave propagates in viscoelastic medium, the analytical solution of onepass wave is as follows: Pðz þ Dz; xÞ ¼ Pðz; xÞ exp½jkðxÞDz

ð1Þ

where z is depth, j is imaginary unit, x is angular frequency, where the Q effect of the formation can be introduced by the complex number wave kðxÞ:

r x j x kðxÞ ¼ 1 tr 2Qr xh

ð2Þ

where, Qr and tr are the quality factor and phase velocity of the reference frequency, xh is the tuning parameter, r ¼ 1=pQ. Therefore, the inverse Q filter results can be expressed as, 


  x r xDs Pðs þ Ds; xÞ ¼ Pðs; xÞexp xh 2Qr 
r  x  exp j xDs xh

ð3Þ

when the Q value varies continuously with the travel time, the surface wave field can be extended to the time depth s, and the continuation wave field is: 2 Pðs; xÞ ¼ Pð0; xÞ exp4 2  exp4j

Zs


x xh

0

Zs
0

x xh

rðs0 Þ

rðs0 Þ

3 x ds0 5 2Qðs0 Þ 3

ð4Þ

x ds0 5

Further deformation (4), Pðs; xÞ ¼ Pð0; xÞKð0; xÞ 2 3 Z s
rðsÞ0 x  exp4j x ds0 5 xh

ð5Þ

0

Kðs; xÞ ¼

bðs; xÞ þ r2 b2 ðs; xÞ þ r2

ð6Þ

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2 bðs; xÞ ¼ exp4

Zs
0

x xh

rðs0 Þ

3 x ds0 5 2Qðs0 Þ

ð7Þ

where, r2 is a stability factor, which is related to the gain limit of the actual data Glim (db), r2 ¼ exp½ð0:23Glim þ 1:63Þ

ð8Þ

In order to improve the efficiency of inverse Q filtering, the Gabor transform is used to inverse Q filtering in time and frequency domain, and then the formula (4) is changed to, ~ xÞKðs; xÞ Pðs; xÞ ¼ Pðs; 2 3 Z s
rðs0 Þ ! x  exp4j 1 x ds0 5 xh

ð9Þ

0

~ xÞ ¼ Pð0; xÞexp½jxs where, Pðs; Formula (9) is an inverse Q filter equation based on Gabor transform. For the wave field of different time depth, the surface seismic record is transformed by Gabor, and the amplitude compensation operator and phase compensation operator are combined to carry out inverse Q filtering in time and frequency domain. The inverse Gabor transform can be used to obtain the seismic record PðtÞ via inverse Q filtering for the obtained wave field Pðs; xÞ.

4 Spectral Decomposition Technique Represented by Generalized S Transformation The time series hðtÞ 2 L2 ðRÞ, L2 ðRÞ represent the integrable function space on the real number field. The S transformation proposed by Stockwell can be expressed as follows. Z1 Sðs; f Þ ¼ 1

(

" #) jf j f 2 ðs  tÞ2 hðtÞ pffiffiffiffiffiffi exp dt 2 2p

Z1 expði2pftÞdt

ð10Þ

1

where, s; f denote time and frequency respectively, both are real numbers. The basic wavelets wðtÞ in the S transform are " # kjf j2a k2 f 2a ðs  tÞ2 wðtÞ ¼ pffiffiffiffiffiffi exp expði2pftÞ 2 2p Then the generalized S transformation is obtained.

ð11Þ

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Z1 GSTðs; f Þ ¼ 1

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(

" #) kjf j2a k2 f 2a ðs  tÞ2 hðtÞ pffiffiffiffiffiffi exp dt 2 2p ð12Þ

Z1



expði2pftÞdt 1

Although wavelet transform (WT) can realize multi-scale focusing, the relationship between wavelet scale and frequency is uncertain. The generalized S transform inherits the advantages of STFT and WT transform and overcomes their disadvantages: The time window in low-frequency section is wider and the frequency resolution is higher, the time window in high-frequency section is narrower, and the time resolution is very high.

5 Spectral Shaping Technology The amplitude of a given seismic record is corrected to make it a specified form, which usually the amplitude spectrum is 1 at a given frequency, and the amplitude spectrum is a smaller value outside the given frequency. Transforming the seismic record into the frequency domain by Fourier transform to calculate the amplitude spectrum, and weighting the amplitude spectrum to correct according to the amplitude-frequency, while keeping the phase spectrum unchanged, then the spectral shaping record is obtained by inverse Fourier transform. Although the amplitude spectrum shaping technique is the most commonly used spectrum adjustment technology, there are some problems: For all components in the frequency correction, noise may be amplified; plastic spectrum is defined by the user, and there are many artificial control factors. Spectrum shaping technology can be used before and after stack. The specific prestack or poststack application depends on the quality of the collected data. Because both the low frequency and high frequency are easy to weaken and the frequency band is narrower during the processing, so the distribution of effective frequency needs to be adjusted.

6 Viscoelastic Prestack Time Migration Technique Viscoelastic prestack time migration technique is the characteristic technology of independent intellectual property of Daqing Institute, which uses the equivalent Q rather than the exact Q value when describing the dissipation of seismic waves. The seismic wave propagation time is calculated using equivalent velocity (root mean square velocity) rather than layer equation of wave field continuation in inhomogeneous viscous media can be velocity. On the basis of these two equivalent parameters, the analytical obtained. Using each seismic data as a collection of data, a viscoelastic medium backpropagation channel is obtained through a one-way travel from the surface to the deep layer,

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 p T x exp j 2 2p 2 s2g Vrms 



 xsg 1 x  exp jxsg 1  ln exp pQe x0 2Qe

PU ðx; y; x; TÞ ¼ FðxÞ

ð13Þ

where, sg is the travel time of the elastic medium at the receiving point to the imaging point (x, y, T), FðxÞ is the Fourier transform of seismic trace, Vrms and Qe are the two equivalent parameters introduced for this paper, where Vrms

sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi n 1X ¼ Vl DTl ; T l¼1

n 1 1X DTl ¼ Qe T l¼1 Ql

ð14Þ

Vrms corresponds to the root mean square velocity of the regular time offset an Qe is the equivalent Q value corresponding to the imaging point space position. In formula (13), two terms related to Qe represent dispersion and amplitude attenuation caused by dielectric absorption, and the fourth is the influence of geometric diffusion of wave propagation. The forward wave source wave field is as follows,
  p T SðxÞx xss exp j P ðx; y; x; TÞ ¼ exp  2 2p 2 s2s Vrms 2Qe 


1 x  exp jxss 1  ln pQe x0 D

ð15Þ

SðxÞ is Fourier transformation in seismic wavelet. In formula (13) and formula (15), sg and ss are the propagation time in elastic medium, which can be obtained by the detection point and the lateral coordinates of the seismic source. Although formulas (13) and formula (15) are derived under the assumption of layered media, the propagation of waves in a lateral inhomogeneous medium can be dealt with only by allowing Vrms and Qe transversal changes. From formula 13 and formula 15, we can see that the frequency-dependent travel time (the second exponential term in the formula) and amplitude compensation factor, as well as the amplitudes from the detection point and the source propagation to the imaging point, are determined only by the imaging point Vrms and Qe . In this way, the two equivalent parameters can be determined by scanning method. Like the traditional prestack time migration, the Kirchhoff compensation algorithm is used to compensate the medium absorption prestack time migration. However, the formula for compensating viscous medium absorption prestack time bias imaging conditions derived by Zhang Jianfeng et al., which is obtained by prestack depth migration, that is, each seismic trace is treated as a shot set. We use formula (13) and formula (15) to propagate seismic traces backward and forward propagation of source wave field in depth domain using one-way travel time T. Because the influence of the source wavelet can be eliminated by deconvolution. We neglected the first three items SðxÞ½x=2p expðjp=2Þ of the wave field in the formula (13). The formula (16) is obtained by substituting the forward propagating source wave field and the backward

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propagating seismic trace the into the prestack depth migration deconvolution imaging condition.
2 Z ss x p FðxÞ expðj Þdx Iðx; y; TÞ ¼ 2p 2 sg


  Z Z  xðss þ sg Þ 1 x  1 ln exp dx expfjxðss þ sg Þdx pQe x0 2Qe ð16Þ Formula (16) represents the migration pulse response of a seismic trace. The migration result is obtained by summing the impulse response of all seismic traces. Different from the conventional prestack time migration, the frequency-dependent dispersion term and amplitude compensation term (Qe related binomial) are introduced into the frequency domain formula. When Qe approaches infinity, the frequency integral in formula (16) is simplified to estimate the first order time derivative of seismic trace at the time sg þ ss . Formula (16) is simplified to conventional prestack time migration. The CRP gather can be obtained by calculating and summing the pulse response of each seismic trace. This is similar to conventional prestack time migration. The appropriate migration aperture should be set in advance and determined by the maximum dip angle of the formation at different times to be imaged. Two equivalent parameters Vrms and Qe are required for viscoelastic prestack time migration. The velocity parameter Vrms can be obtained by establishing a conventional prestack time migration velocity model. Equivalent parameter Qe can be obtained by scanning the equivalent Q parameter. In order to obtain Q model from ground seismic data, another problem must be dealt with, that is, thin layer tuning effect caused by thin interlamination. The strong tuning effect results in the occurrence of notch frequency in the reflected wave spectrum, and the error Q value can be obtained by using the spectral ratio method or the frequency shift method directly. The equivalent scanning method uses multiple constant Q viscoelastic prestack time migration results and picks up the best Q value. In order to reduce the computational workload of constant Q migration, we simplify formula (16) to constant Q formula, so that viscoelastic prestack time migration is simplified as prestack inverse Q filter plus constant Q model prestack time migration. Stability is a problem faced by all kinds of absorption compensation algorithms. Only by solving the stability problem and noise suppression problem of absorption compensation in medium and deep layers can we obtain the absorption compensation of the actual data in the middle and deep layers. This is because the amplitude compensation factor (the last term on the right of formula (16) approaches infinity for smaller travel times and higher frequencies. Because the prestack time migration for compensating viscous absorption has obtained an analytical compensation factor, we can ensure that when the compensation factor is less than the specified gain limit, the function is completely consistent with the accurate amplitude compensation factor by setting a smoothing gain function. The gain limit value is gradually approaching. The gain function is as follows,

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/ðgÞ ¼ expðgÞ;

g  ln G

/ðgÞ ¼ Gð1  ln G  2:5ðln GÞ2 Þ þ Gð1 þ 5 ln GÞg  2:5Gg2 ; /ðgÞ ¼ 1:1G;

ln G\g\ ln G þ 0:2

g [ ln G þ 0:2

ð17Þ ð18Þ ð19Þ

where, g ¼ xðsg þ ss Þ=ð2Qe Þ denotes gain limitation and stable imaging results can be

 obtained by using amplitude compensation factor exp xðsg þ ss Þ=ð2Qe Þ in uðgÞ instead of formula (16). By comparing several techniques to improve the resolution, it can be seen that the inverse Q filter is not enough to protect the low frequency, and the low-frequency deficiency of the processing result is serious, but the low-frequency component is the key to the prediction of dense-gas desserts. The spectral decomposition technique is difficult to control the frequency spectrum shape of the high-frequency end, it is easy to raise too high and reduce the high-frequency signal-to-noise ratio, and the spectrum shaping technology expects that the output spectrum will have more artificial control factors to be easily controlled. According to the characteristics and potential of the data, the fidelity and amplitude-preserving frequency can be maximized, and the technology of prestack time migration for viscoelastic media is advanced and effective, but it cannot meet the requirements of large area industrialization in a short period of time. By comparing and analyzing the principle, the improved method of spectrum shaping as the main frequency extension technique is adopted to improve the resolution of seismic data in the study area.

7 Example The research base of deep unconventional reservoir prediction is seismic data with wideband amplitude-preserving processing. In order to improve the fidelity and amplitude preservation, the characteristic processing techniques, such as iterative noise suppression and 3D Q compensation, are adopted. In order to improve the imaging accuracy of deep complex structures, a velocity model is established by using high precision mesh chromatography. By using prestack depth domain inverse time migration (CIG) focusing imaging technique, there is abundant information among the layers of the section after migration, the relationship between wave groups is clear, and the section is clear about fracture points, which is beneficial to the development of poststack frequency extension processing. Based on this data, (1) comprehensive spectrum analysis is carried out for the target layer; (2) the spectrum analysis of the whole region after the anti-Q filter is analyzed; (3) the amplitude spectrum and phase spectrum of the output anti-Q filter are output; (4) the result of step (3) is done by inverse Fourier transform to get the global statistical wavelet one after the anti-Q filtering; (5) by using the method of statistical amplitude spectrum energy envelope, the results of step (1) and step (2) are used to obtain the expected output wavelet 2 by inverse Fourier transform, and the global filter operator is

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obtained by shaping wavelet 2. By convolution between the operator and the seismic data after anti-Q filtering, the final results are obtained. The above is the spectral shaping technique flow based on global statistical wavelet. It can be seen from Fig. 2 that this method not only improves the high frequency, but also keeps the low-frequency feature well, and the main frequency and the octave of the data are increased simultaneously. The global filtering operator of this method is based on global data statistics, and it does not change the relative amplitude relation, so it is amplitude preserving. After increasing the frequency, the main frequency of seismic profile is increased by 14 Hz, the resolution is improved significantly, the information between layers is abundant, the matching degree of synthetic records is improved, and the imaging clarity of the four-level sequence interface is slightly improved. From the comparison of Fig. 3, it can be seen that the amplitude attribute characteristics are similar and the amplitude distribution characteristics are consistent before and after spectral shaping, which proves the amplitude preservation of this technique

Fig. 2. Comparison of profile contrast before and after spectral shaping and matching degree of synthetic records

In the geological model of phase control guiding ideology, comprehensive analysis using multiple attribute recognition gradually sandstone area: (1) The high-frequency reflection areas of shallow lake facies or marsh facies developed in coal seam and thin sandstone are excluded by high value of frequency attributes; (2) the amplitude of high value further eliminate the thick coal seam (>2 m) compared with the developed areas and the front sub thick dry layer sandstone area; (3) low impedance attribute values exclude the prodelta mudstone interbedded with thin siltstone of low-frequency weak amplitude and low impedance reflection area. Through correlation analysis, we choose the instantaneous bandwidth attributes and peak amplitude attributes which have good correlation with lithology and lay a foundation for qualitative prediction of sandstone relative development area. Comprehensive analysis of the following two properties for

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Fig. 3. a Before the spectral shaping, the SB4-3 root mean square amplitude property slice and b the SB4-3 root mean square amplitude property slice after spectral shaping

favorable sedimentary facies identification are: (1) The high value of instantaneous bandwidth properties excludes the development area of coal seam, middle and low value identification front and plain facies sandstone development area; (2) the peak amplitude attribute can distinguish between the leading edge coherent sandstone and the gas-bearing sandstone development zone, the middle-high value corresponds to the dry sand development area, the middle and low value corresponds to the gas sand development area, the peak amplitude attribute corresponds to the very developing area of the coal seam, in which the lithological assemblage is mainly composed of thick mudstone, coal seam and thin siltstone, and a thicker coal seam with a single layer thickness of over 2 m is developed. On this basis, combined with the relative wave impedance inversion results of no well constraints, the favorable area of sandstone is predicted. The reason is that the mean property of the relative wave impedance can distinguish between the plain and the front deltaic thick mudstones which are indistinguishable from the instantaneous and peak amplitude properties. The final criteria for determining the unconventional tight sandstone gas desserts in the area are: instantaneous bandwidth—low value, peak amplitude attribute—low value, and high value in relative impedance. Under the guidance of this knowledge, the sandstone undeveloped area is gradually eliminated with multi-attribute synthesis, and the favorable development area of sandstone is predicted and the multiple solution of single attribute prediction is reduced. The coincidence rate is raised from 67 to 80%. In the statistics of 14 wells, the coincidence rate of SQ4-3 is 85%, the average coincidence rate of the 7 layer statistics in SQ4-SQ2 sequence is 80%. As can be seen from Fig. 4, Fig. 4a is the seismic section of well X34 in the post well, and Fig. 4b is the relative wave impedance section of the over well. The relative wave impedance inversion of X34 well predicts 8 layers of sandstone. The real drilling meets 8 layers of sandstone, in which there are 3 layers of sand formation and 3 layers of more than 10 m single sand. The relative inversion prediction accords with 6 layers (2 layers of single sand body, 4 layers of sand layer), and the inversion prediction coincidence rate is 75%. The SQ4-2 layer (No. 36 layer) sand ratio is 0.47. The range of blue brackets in the three attribute figures (Fig. 4c is instantaneous bandwidth property, Fig. 4d is peak

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amplitude property, Fig. 4e is relative impedance inversion) that predict a favorable area for dessert, and the prediction results reveal the development of sandstone, consistent with the real drilling.

Fig. 4. a Cross-well seismic profile, b relative impedance inversion section, c instantaneous bandwidth attribute diagram, d peak amplitude attribute diagram and e relative impedance inversion plane map

8 Conclusions (1) According to the principle and the applicable conditions, the spectral shaping method is optimized to improve the vertical resolution of seismic data. Using the wavelet based on global statistics without changing the relative amplitude relation, the frequency processing has the amplitude-preserving property. After the process, the main frequency of the data is increased by 14 Hz, and the definition of the four sequence interface is improved. Improving high frequency and keeping low frequency, the main frequency and octave frequency range are increased simultaneously, and the seismic true resolution is improved. (2) The detailed full attribute analysis is carried out on the basis of spectral shaping extension data to optimize the property of instantaneous bandwidth and peak amplitude with better correlation with lithology, which lays the foundation for the qualitative prediction of sandstone relative development zone. The mean property of the relative wave impedance can distinguish between the plain thick layer sand conglomerate and the front delta thick mudstone which cannot be distinguished from the instantaneous and peak amplitude properties. Finally, the multi-attribute comprehensive analysis combined with the relative impedance inversion strategy is used to predict the dessert of the deep dense gas.

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(3) The new processing results are optimized by combining multi-attribute and relative wave impedance inversion to select the “dessert area” of sandstone, which reduces the multi-solution of single attribute prediction. The average coincidence rate is increased from 67 to 80%. The prediction coincidence rate of sand body inversion in X34 well is 75%, and the prediction coincidence rate of SQ4-3 sequence sandstone is 85.7%. (4) Spectral shaping and frequency expansion technology based on wideband amplitude-preserving imaging processing support the location deployment of 7 exploration wells in the area and provide strong technical support for increasing storage and production in unconventional fields. Multi-attribute comprehensive analysis combined with the method of relative impedance inversion has high prediction accuracy of deep dense gas and has a good prospect of popularization and application.

References 1. Gao JH, Chen WC, Li YM, et al. Generalized S transformation and seismic response of thin interbeds. Chin J Geophys. 2003;46(4):526–532. 2. Gao JH, Man W, Chen SM. Recognition of signals from colored noise background in generalized S-transform domain. Chin J Geophys. 2004;75(5):869–75. 3. Wan H, Fan XY, Liu T, et al. Methods and applications for improving pre-stack seismic data resolution. Prog Geophys. 2012;27(1):304–11 (in Chinese). 4. Li ZC, Wang QZ. A review of research on mechanism of seismic attenuation and energy compensation. Prog Geophys. 2007;22(4):1147–52. 5. Yao ZX, Gao X, Li WX. The forward Q method for compensating attenuation and frequency dispersion used in the seismic profile for depth domain. Chin J Geophys. 2003;46(2):229– 33. 6. Hargreaves ND, Calvert AJ. Inverse Q-filtering by Fourier transform. Geophys. 1991;56 (4):519–27. 7. Wang YH. A stable and efficient approach of inverse Q filtering. Geophys. 2002;67(2):657– 63. 8. Hale D. An inverse Q-filter. Stanford Explor Project. 1981;28:289–98. 9. Chen CR, Zhou XX. Improving resolution of seismic data using wavelet spectrum whitening. Oil Geophys Prospect. 2000;35(6):703–9. 10. Stockwell RG, Mansinha L, Lower RP. Localization of the complex spectrum: the Stransform. IEEE Trans Signal Process. 1996;44(4):998–1001. 11. Liu XW, Liu H, Li YM, et al. Study on characteristics of seismic stratigraphyized Stransform. Prog Geophys. 2006;21(2):440–51. 12. Pinnegar CR, Mansinha L. The S-transform with windows of arbitrary and varying shape. Geophys. 2003;68(1):381–5. 13. Pinnegar CR, Eaton DW. Application of S transform to prestack noise attenuation filtering. J Geophys Res. 2003;108(B9):1–10. 14. Zhang GL, Xiong XJ, Rong JJ, et al. Stratum absorption and attenuation compensation based on improved generalized S-transform formation. Oil Geophys Prospect. 2010;45(4):512–5. 15. Li GF, Zhou H, Zhou H, Zhao C. Potential risks of spectrum whitening deconvolutioncompared with well-driven deconvolution. Pet Sci. 2009;6:146–52.

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16. Mauricio DS, Danilo RV, Alberta HC. Minimum entropy deconvolution with frequencydomain constraints. Geophys. 1994;59(6):938–45. 17. Lu PF, Yang CC, Guo AH. The present research on frequency-spectrum imaging technique. Prog Geophys. 2007;22(5):1517–21.

Author Biography Yi Bao male, Master of Engineering, Exploration and Development Research Institute of Daqing Oilfield Company Ltd. CNPC, engineer. The research field is seismic data processing, processing and interpretation integration, complex structure imaging, etc.

Study on the Optimization of Fractures Layout in Horizontal Wells of Tight Gas Reservoirs Zhaozhong Yang, Qian Chen(&), and Xiaogang Li National Key Laboratory of Reservoir Geology and Development Engineering, Southwest Petroleum University, Chengdu, China [email protected]

Abstract. Hangjinqi block in the Ordos Basin belongs to low-porosity and low-permeability gas reservoir, which contains abundant natural gas resources. The productivity prediction of post-fracturing and fractures layout optimization are the difficulties. Considering the threshold pressure gradient, the mutual interference between the fractures, and finite diversion in fracture, on the basis of the point sink discretization method and the potential superposition principle, the unsteady productivity calculation model of fracturing horizontal well in tight gas reservoirs is built. From the fracture propagation result, the morphology of fracture may be curved due to stress disturbance, which can also be discretized into several points. Prepare the corresponding productivity software, which can calculate not only the production of the straight fractures, but also the production of the curved fractures. Take the Jin 58 well block box of three layers as a calculation example, discuss the influence of different fracture morphology and different fracture parameters on horizontal well productivity, and then obtain the best fracture layout according to the production. It is recommended that the total fracture length is as large as possible in the economic scope, and the outer fracture is better to be longer than the middle fracture in each perforation. Besides, the spacing of each fracture is the same. The results of this study provide a reference for horizontal well productivity calculations and guide the fracturing design. Keywords: Tight gas reservoir fractures
Fractures layout


Horizontal well
Multi-fracturing
Curved

Copyright 2018, Shaanxi Petroleum Society. This paper was prepared for presentation at the 2018 International Field Exploration and Development Conference in Xi’an, China, 18–20 September, 2018. This paper was selected for presentation by the IFEDC Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the IFEDC Committee and are subject to correction by the author(s). The material does not necessarily reflect any position of the IFEDC Committee, its members. Papers presented at the Conference are subject to publication review by Professional Committee of Petroleum Engineering of Shaanxi Petroleum Society. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of Shaanxi Petroleum Society is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of IFEDC. Contact email: [email protected]. © Springer Nature Singapore Pte Ltd. 2020 J. Lin (ed.), Proceedings of the International Field Exploration and Development Conference 2018, Springer Series in Geomechanics and Geoengineering, https://doi.org/10.1007/978-981-13-7127-1_50

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1 Introduction The multistage fracturing technology has been widely used to improve well performance in tight gas reservoir. Hangjinqi block located in the Ordos Basin has typical characteristics of low porosity and low permeability. At present, the field adopts the open-hole packer fracturing technique to improve the stimulation [1]. The production prediction in fracturing horizontal well is an effective way to assess the fracturing effect, and it is necessary to optimize the fracture parameters and the fracture layout with the output target. The performance prediction in horizontal well becomes a top issue for researchers. Giger et al. [2] established a mathematical model for the first time to study the horizontal well productivity of fracturing, but its model has problems in the coupling of fluid flow. On the basis of Giger, Soliman and Hunt [3] considered the flow in the fracture as the radial flow, and the output of a single fracture is obtained. Then, the productivity of multiple fractures can be obtained by adding the output. Raghava and Joshi [4] divided the fracture into several microelements, and each microelement is considered as a point sink. A semi-analytical production prediction model of multifracturing horizontal well is given by using superposition principle. Ozkan et al. [5] studied the analytical method of the single fracture according to the superposition principle. However, this approach simplified the fractures in the horizontal wellbore; that is, the hydraulic fracture spacing was equal, and the mutual interference between the fractures was ignored. Clarkson and Pedersen [6] divided the flow in the fracturing horizontal well into four stages, including early linear flow, early radial flow, late linear flow, and late radial flow, set up four horizontal well productivity prediction models during different periods, and made productivity prediction more systematic. Xu et al. [7] took advantage of the theory of reduction potential and the principle of potential superposition to build a new model for calculating the productivity of fracturing horizontal wells. Zeng et al. [8] considered the nonuniform flow rate of fracturing horizontal wells, mass flow in the fracture, and the mutual interference between the fractures. An unsteady output calculation model was presented for reservoir seepage and fracture flow in low-permeability reservoirs using space and time discrete technology. Hu et al. [9] used the power law model to calculate and predict the horizontal well unsteady production and analyzed the influence factors on productivity. He et al. [10] obtained the single fracturing horizontal well and multiple fracturing horizontal well productivity calculation system of linear equations on the basis of principle of superposition of potential and the matrix transformation method in the infinite formation. Zhao et al. [11] presented the semi-analytical mathematical modeling for gas productivity calculation of multistaged horizontal wells in fractured tight sandstone gas reservoirs that emphatically considers the impact of flow in fracture network (natural fracture system). Due to the low permeability and porosity, there exists the threshold pressure gradient in the matrix. Wang et al. [12] presented that in the low-permeability media, the threshold pressure gradient can briefly describe a low-speed non-Darcy seepage. Seepage equation of the threshold pressure gradient is a complement to the classic Darcy’s law, which is the theoretical foundation of the effective development of low-

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permeability reservoir. Guo and Wang [13] established the productivity model of horizontal well based on the seepage characteristics of low-permeability gas reservoir by means of transformation method, and the effects of stress sensitivity and threshold pressure gradient were taken into account. These papers focused on analytical model and made some idealized hypotheses of fractures, so the models or methods cannot describe the real condition of the formation and MFHWs. In this paper, considering the threshold pressure gradient and the mutual interference between the fractures, according to the potential theory and potential superposition principle, dispersing the hydraulic fractures, coupling reservoir seepage and fracture flow, the unsteady productivity calculation model of fracturing horizontal well in tight gas reservoir is derived. In some cases, the hydraulic fractures are not straight. Due to the stress interferes, the fracture morphology is curved [14]. Because the curved fracture can be discretized into several points, the production prediction model is also applicable. And the fracture parameters’ influence is discussed on daily output and cumulative production. Now, there is hardly mature productivity calculation software for fracturing horizontal wells for on-site use. Therefore, based on the hydraulic fracture morphology and seepage process of tight sandstone reservoirs, the model is established to meet the actual production of horizontal well fracturing, and a simple and efficient production calculation software is prepared.

2 Methodology 2.1

Physical Model

According to the characteristics of fluid flow in a tight gas reservoir, the fluid flows in the fractured horizontal well through three regions. The first one is non-Darcy’s flow in matrix far from the fractures, existing a threshold pressure gradient. Elliptic flow from the matrix to the fractures is the second flow region. At last, the fluid flows linearly into the wellbore through the fractures. The fracturing horizontal well productivity model is assumed to be as follows: (1) The infinite formation is homogeneous and isotropic, where the bottom is closed, and the horizontal wellbore is located in the middle of the gas reservoir; (2) There exists a threshold pressure gradient in the gas seepage in the matrix, while the fluid flow conforms to Darcy’s law in the fractures; (3) The hydraulic fractures are perpendicular to the horizontal wellbore and completely penetrate the production layer; (4) The gas only flows through the fractures to the horizontal wellbore isothermally, ignoring it flows directly from the matrix to the wellbore. In the previous research, the fractures are considered to be straight. However, the results of fracture propagation show that due to the stress interferes, the fracture morphology is not straight, but curved (Fig. 1). The different fracture morphology and layout have a great influence on horizontal well productivity, which will be discussed later.

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Fig. 1. Curved fracture diagram

2.2

Mathematical Model

According to the established physical model, a pressure decline model in the infinite formation is used in the fundamental theory. The unsteady seepage differential equations are derived. 8 2 @ p 1 @p 1 @p > > > @r2 þ r @r ¼ g @t < pðr;0Þ ¼ pi @p > r j ¼ ql > > : @rp r¼rw¼ p2pKh i ðr;tÞ

ð1Þ

On the basis of the above differential equations, and considering gas pseudo-pressure function, the pressure drop formula of the flow point transfer in the infinite reservoir can be obtained as follows: wi  wðx;y;tÞ

" !# Gl ð x  x0 Þ 2 þ ð y  y0 Þ 2 Ei  ¼ 4pKi h 4gt

ð2Þ

where wi is the initial reservoir pseudo-pressure, Pa=ðPa sÞ; wðx;y;tÞ is the pseudopressure at point (x, y) in the reservoir, Pa=ðPa sÞ; G is the mass flow rate, kg/s; l is the fluid viscosity, ðPa sÞ; Ki is the reservoir permeability, m2; h is the reservoir thickness, m; g ¼ Ki =ðulCt Þ, which is the diversion coefficient; t is the production time, s; (x0, y0) are the coordinates of the point sink.

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Due to the low permeability and porosity, the threshold pressure gradient is considered in the tight gas reservoir. Equation (2) is changed to: Zre wi  wðx;y;tÞ  "

0

2P Gdx lZ

Gl ðx  x0 Þ2 þ ðy  y0 Þ2 ¼ Ei  4pKi h 4gt

!#

R re 2P

0 lZ Gdx

ð3Þ

The horizontal wellbore and the fracture are, respectively, the x-direction coordinate and the y-direction coordinate (Fig. 2). And the hydraulic fractures are discretized into n segments (Fig. 3). Regardless of the shape of the fracture, it is possible to obtain the pressure drop of a point in the reservoir by the coordinates of each point. According to the superposition principle and potential theory, the pressure drop at any point (x, y) in the reservoir from the n-point sink on the N fractures at t moment is derived. 1   2P @wi  wðx;y;tÞ  A Gdx  lZ  0 N "  2  2 ! # N X n X x  xfij þ y  yfij Gfij l Ei  ¼ 4pKi h 4gt i¼1 j¼1 0

Zre

Fig. 2. Coordinate diagram

ð4Þ

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Fig. 3. Discrete fracture diagram

where N is the fracture number and n is the each fracture’s point number. Before submitting the point sink into the equations, the coordinates of the n points ð1  j  nÞ of each fracture ð1  i  NÞ must be prepared. And the coordinate position of the first point on the left wing can be expressed as ðxfi1 ; yfi1 Þ, and the pressure of the fracture’s left tip is obtained by: 0 1  Zre  2P @wi  wðx ;y ;tÞ  A Gdx  fi fi lZ  0 N ð5Þ "  2  2 ! # N X n X xfi1  xfij þ yfi1  yfij Gfij l Ei  ¼ 4pKi h 4gt i¼1 j¼1 Similarly, the coordinate position of the nth point on the right wing can be expressed as ðxfin ; yfin Þ. The pressure of the fracture’s right tip is obtained by: 1   2P @wi  wðx ;y ;tÞ  A Gdx  fi fi lZ  0 N "  2  2 ! # N X n X xfin  xfij þ yfin  yfij Gfij l Ei  ¼ 4pKi h 4gt i¼1 j¼1 0

Zre

ð6Þ

The average pressure value of the ith fracture’s tip is obtained by means of the average pressure of the left and right sides of the fracture.

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1   @wi  wðx ;y ;tÞ  2P GdxA  fi fi lZ  0 N " "  2  2 !# N X n X xfi1  xfij þ yfi1  yfij 1 Gfij l Ei  ¼ 2 i¼1 j¼1 4pKi h 4gt "  2  2 !## N X n X xfin  xfij þ yfin  yfij Gfij l Ei  þ 4pKi h 4gt i¼1 j¼1 0

Zre

ð7Þ

Considering the real gas, the pseudo-pressure function is transformed into the pressure expression. 

  P2i  P2ðxfi ;yfi ;tÞ  Pi
G
re  N " "  2  2 ! # N X n X xfi1  xfij þ yfi1  yfij 1 Qfij l PSC ZT ¼ E i  2 i¼1 j¼1 4pnKi h TSC 4gt "    2 !## 2 N X n X xfin  xfij þ yfin  yfij Qfij l PSC ZT Ei  þ 4pnKi h TSC 4gt i¼1 j¼1

ð8Þ

The gas flow from the fracture tip to the wellbore can be deemed as a radial flow. At the ith fracture, there are the flowing radius ri, formation thickness wi, the boundary pressure (the same as the fracture tip pressure) Pðxfi ;yfi ;tÞ , and the flowing bottom hole pressure (the same as pressure in the horizontal borehole) Pwfi. There is skin damage around the wellbore, and the skin coefficient is introduced. 0 qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi P2ðxfi ;yfi ;tÞ  P2wfi

Qfi l PSC ZT @ ¼ ln pKf wi TSC

ðLfli þ Lfri Þh p

rw

1 þ SA

ð9Þ

where Qfi is the flow rate of the fracture i, m3/s; Kf is the fracture permeability, m3; wi is the fracture width, m; PSC is the pressure under the standard conditions, Pa; TSC is the temperature under the standard conditions, °C; Z is the natural gas deviation factor; T is the reservoir temperature, °C; Lfli is the left wing length of the fracture i, m; Lfri is the right wing length of the fracture i, m; S is the skin factor. Coupling fluid flow from the reservoir to the fracture, and the fracture to the wellbore pressure drop formula, the well productivity prediction model is revised.

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 2  Pi  P2wfi  Pi
G
re N 0 qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 1 ðLfli þ Lfri Þh Qfi l PSC ZT @ p ¼ ln þ SA pKf wi TSC rw " "  2  2 ! # N X n xfi1  xfij þ yfi1  yfij 1 X Qfij l PSC ZT Ei  þ 2 i¼1 j¼1 4pnKi h TSC 4gt "    2 !## 2 N X n X xfin  xfij þ yfin  yfij Qfij l PSC ZT Ei  þ 4pnKi h TSC 4gt i¼1 j¼1

ð10Þ

The production of each fracture can be obtained by the above equation. And the prediction model of fracturing horizontal wells in tight sandstone gas reservoir is established, which constitutes an N linear system of equations with N unknowns. Finally, the total output of the fracturing horizontal well is added up by the output of each fracture. Q¼

N X

Qfi

ð11Þ

i¼1

where Q is the total productivity of the horizontal well, m3/s.

3 Discussion and Analysis 3.1

Application

Jin 58 well zone of Hangjinqi block in the Ordos Basin is taken as a calculation example. The reservoir basic data are as follows. The initial reservoir pressure is 26 MPa, the effective reservoir thickness is 10 m, the reservoir porosity is 8.56%, and the matrix permeability is 0.45 mD. The formation temperature is 94 °C, and the coefficient of rock compressibility is 3  10−4 MPa−1. The gas viscosity is 0.02 MPa s, and the gas deviation factor is 0.957. In each perforation section of horizontal well, there are three fractures. If the fractures do not turn due to the stress interference, they form a normal straight one. The contrast between straight and curved fractures is shown in Fig. 4. The total length of the two kinds of fractures is equal in the x and y planes, and the height of the fractures is equal to the thickness of the reservoir [15]. The production prediction model established in this paper is used to calculate the yield of curved crack and straight fractures, respectively. From the simulation results, it can be seen that the daily output difference between the curved fractures and the straight fractures is within 20,000 m3, and the yield of the bending fractures is higher than the straight fractures (Fig. 5). As production goes on, the daily output difference between the curved and straight fractures becomes smaller, which is stable at around 5000 m3. And the cumulative production (Fig. 6) shows that at the early stage, the difference between the two kinds of fracture is small, and then,

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Fig. 4. Contrast morphological diagram of curved fracture and straight fracture

the differential amplitude increases gradually. After half a year, the total yield of the curved fractures is 9.89% higher than that of straight fractures. Therefore, the stimulation effect of the curved fractures in horizontal well is better than the traditional straight fractures. The more complex the fracture morphology, the larger the effective transformation volume, the higher the output. The predecessors’ idealized assumptions about fractures led to a small calculation.

daily output/(10 4 m 3 )

13

curved fracture

12

straight fracture

11 10 9 8 7 6 5 4

0

30

60

90

120

150

180

time/d Fig. 5. Three fractures’ daily output graph

3.2

Optimization of the Facture Layout

The fracture morphology and layout have a great impact on the horizontal well production. Therefore, based on site condition and theory study, the fracture conductivity, the total fracture length, the fracture length ratio, and the spacing ratio are selected to discuss, then get the optimal fracture layout of three fractures in the perforation section.

cumulative production/(10 4 m 3 )

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curved fractures straight fractures

1200 1000 800 600 400 200 0

0

30

60

90

120

150

180

time/d Fig. 6. Cumulative output of three fractures in half a year

Orthogonal design test is a design method to study multifactors. Through the analysis of the results of orthogonal design test, the influence of the main fracture parameters on the productivity of fracturing horizontal wells can be obtained. The fracture parameters are given in Table 1. Lf1/Lf2 is the length ratio of outer fracture and middle fracture. And d1/d2 is the spacing ratio as shown in Fig. 7. According to the above fracture parameters, the four-factor three-level hybrid orthogonal test scheme is presented in Table 2. Table 1 Fracture parameter list Fracture parameters The total length (m) Conductivity (D cm) Length ratio Spacing ratio

Values 300 30 0.5 1

400 40 1 2

Fig. 7. Length ratio and the spacing ratio of three fractures

500 50 2

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Test Test Test Test Test Test Test Test Test

1 2 3 4 5 6 7 8 9

Conductivity (D cm) 30 30 30 40 40 40 50 50 50

Total length (m) 300 400 500 300 400 500 300 400 500

Length ratio 2 1 0.5 1 0.5 2 0.5 2 1

Spacing ratio 2 1 2 2 2 1 1 2 2

cumulative production/(104m3)

The cumulative production calculation results of nine sets of orthogonal tests in half a year are shown in Fig. 8. It can be seen that the cumulative yield of the sixth test is the highest. That means with three fractures in each section, when the total seam is 500 m long, the conductivity is 40 D cm, the length ratio is 2, and the spacing ratio is 1, fracturing horizontal well works the best. Therefore, the fracture layout of test 6 is recommended for the horizontal well in Hangjinqi reservoir. The daily output and cumulative production under the scheme are shown in Fig. 9, and the cumulative gas output after half a year is about 1.17  107 m3. 1200 1150 1100 1050 1000 950 900 test1 test2 test3 test4 test5 test6 test7 test8 test9

Fig. 8. Cumulative output of three fractures under different schemes

Different fracture parameters impacting the horizontal well are shown in Fig. 10. The effect of each parameter factor level on the target can reflect the order of the primary and secondary factors; that is, the first one is the total seam long, and the second factor is length ratio, following the conductivity and the spacing ratio.

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daily production/(104m3)

cumulative production/(104m3)

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time/d

cumulative production/(104m3)

Fig. 9. Optimal combination of output graph

conductivity total length length ratio spacing ratio

parameter level Fig. 10. Effect curve

From the above fracture parameters’ analysis, the fracture length is a key parameter to improve well production. The longer the fractures, the higher the production of single horizontal well. However, the total length is related to the economic cost, so it is not necessary to increase the yield of the long seam. Under certain economic conditions, the appropriate increase of the fracture length can effectively increase the yield. Moreover, it can be seen from the length ratio that when the length of the outer fracture is longer than the middle of three fractures in each perforation section, the production is greater. Besides, this calculation model takes into account the influence of interstitial interference, so the smaller the fracture spacing, the more serious the disturbance, and then, the stimulation effect is worse. From the production results, the fracturing effect is better when the spacing between the three fractures is equal. All in all, each fracture parameter has an optimal value under the different condition.

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4 Conclusion According to the superposition principle and the potential theory, considering the effect of start-up pressure gradient and mutual interference between the fractures in the lowpermeability tight gas reservoir, the fracturing horizontal well unsteady productivity calculation model is established by dispersing fracture, which can calculate not only the yield of the straight fracture, but also the yield of the curved fracture due to stress disturbance. Therefore, the model established in this paper is more extensive and accurate. As for different morphology, we compare the daily output and cumulative yield of the straight and curved fractures in the fracturing horizontal well formed in the third layer of Jin 58 well zone in Hangjinqi block of the Ordos Basin. The results show that the yield of curved fracture is higher and the stimulation effect is better. The predecessors’ idealized assumptions about fractures led to a small production. Nine sets of orthogonal design tests have been established to analyze the factor influencing fractures on the poor effect of target. The results show that the total fracture length has the greatest effect on the staged fracturing horizontal well productivity, following the length ratio and the spacing ratio, and the fracture conductivity is in the middle. Optimize the best fracture layout of the Hangjinqi block, namely, when fracture number is 3 in each section, the total length is 500 m long, the fracture conductivity is 40 D cm, the length ratio is 2, and the spacing ratio is 1. Acknowledgements. The research was supported by the National Science and Technology Major Project of China (2016ZX05002-005-011).

References 1. Lian LM, Qin JS, Yang SY, et al. Evaluation and development direction of seepage model of horizontal well. Oil Gas Geol. 2013;34(06):821–6. 2. Giger FM, Resis LH, Jourdan AP. The reservoir engineering aspects of horizontal drilling. SPE 13024. 1984. 3. Soliman MY, Hunt JL. Fracturing aspects of horizontal we1ls. J Petrol Technol. 1990;42(8): 66–73. 4. Raghvan R, Joshi SD. Productivity of multiple drainholes or fractured horizontal wells. SPE Form Eval. 1993;8(1):1–16. 5. Ozkan E, Al-Kobaisi M, Raghavan R. A hybrid numerical/analytical model of a finiteconductivity vertical fracture intercepted by a horizontal well. SPE Res Eva Eng. 2006;9(4): 345–55. 6. Clarkson CR, Pedersen PK. Tight oil production analysis: adaptation of existing ratetransient analysis techniques. In: Canadian unconventional resources and international petroleum conference. SPE. 2010. 7. Xu YB, Qi T, Yang FB, et al. New model of horizontal well productivity prediction after fracturing. Acta Petrol Sin. 2006;27(1):89–92. 8. Zeng FH, Cheng XZ, Guo JC. The calculation of unsteady output of fracturing horizontal well in low permeability reservoir with non-uniform flow of fracture surface. J Cent South Univ Nat Sci Ed. 2016;47(04):1353–8.

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9. Hu JH, Zhang Chong, Rui ZH, et al. Fractured horizontal well productivity prediction in tight oil reservoirs. J Petrol Sci Eng. 2017;151:159–68. 10. He J, Fan ZF, Zhao L. Fan, Lun Zhao, The application of point transfer discrete method in fracturing horizontal well productivity evaluation. Nat Gas Geosci. 2016;27(01):134–41. 11. Zhao JZ, Pu X, Li YM, et al. A semi-analytical mathematical model for predicting well performance of a multistage hydraulically fractured horizontal well in naturally fractured tight sandstone gas reservoir. J Nat Gas Sci Eng. 2016;32:273–91. 12. Wang XD, Hao MQ, Han YX. The meaning and response of starting pressure gradient. Acta Petrol Sin. 2013;34(01):188–91. 13. Guo X, Wang Y. Effect of starting pressure gradient and stress sensitivity on horizontal well productivity of low permeability gas reservoir. Oil Gas Geol. 2007;04:539–43. 14. Yang ZZ, Yi LP, Li XG, et al. Pseudo-three-dimensional numerical model and investigation of multi-cluster fracturing within a stage in a horizontal well. J Petrol Sci Eng. 2018;162: 190–213. 15. Hu YQ, Pu XY, Zhao JZ, et al. Simulation of fracturing complex fractures in horizontal wells of shale gas reservoirs. Nat Gas Geosci. 2016;27(08):1367–73.

Shale Gas Potential of Goldwyer Formation in Canning Basin, Australia Wenguang Zhao(&), Yuxia Ma, and Houqin Zhu PetroChina Research Institute of Petroleum Exploration & Development, Beijing, China {zhaowenguang,mayx,zhuhouqin}@petrochina.com.cn

Abstract. Canning Basin of Wstern Australia is one of the few large sedimentary basins with low petroleum exploration degree in Australia. The successful exploration and development of shale gas in North America has promoted shale gas exploration acitivity in the Canning Basin. EIA (World Shale Gas Resources: An Initial Assessment of 14 Regions outside the United States, EIA, 2011 [6]), EIA (World Shale Gas Resources: An Initial Assessment of 14 Regions outside the United States, EIA, 2013 [7]) has evaluated shale gas resources of Middle Ordovician Goldwyer Formation and oil companies have drilled shale gas exploratory wells in Canning Basin. The combination of structural and sedimentary studies and core geochemistry analysis is used to evaluate the shale gas potential of Goldwyer Formation in this article. 2D seismic data and well data are used to study the geological characters of Kidson Sub-basin where Goldwyer Formation mainly developed. Tectonic evolution, sedimentary facies and geochemical study of Goldwyer Formation show shale gas potential of Goldwyer is poor. Keywords: Shale gas
Exploration potential
Goldwyer formation
Canning basin
Australia

Copyright 2018, Shaanxi Petroleum Society This paper was prepared for presentation at the 2018 International Field Exploration and Development Conference in Xi’an, China, 18–20 September, 2018. This paper was selected for presentation by the IFEDC Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the IFEDC Committee and are subject to correction by the author(s). The material does not necessarily reflect any position of the IFEDC Committee, its members. Papers presented at the Conference are subject to publication review by Professional Committee of Petroleum Engineering of Shaanxi Petroleum Society. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of Shaanxi Petroleum Society is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of IFEDC. Contact email: [email protected]. © Springer Nature Singapore Pte Ltd. 2020 J. Lin (ed.), Proceedings of the International Field Exploration and Development Conference 2018, Springer Series in Geomechanics and Geoengineering, https://doi.org/10.1007/978-981-13-7127-1_51

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1 Introduction Canning Basin (400,000 km2) of Western Australia is one of the largest intracratonic basins in the world [1, 2] (Fig. 1). Canning Basin is adjacent to Precambrian Kimberley Block in the north. The south of Canning Basin is Precambrian Pilbara Block, Yeneena and Officer Basins. Amadeus Basin and Arunda Block locate in the east of Canning Basin. In the west of the sea, the offshore part of former Canning Basin is called Roebuck Basin. Canning Basin is the largest sedimentary basin in Australia, with a major structural strike of NW-SE, which is characterized by three uplifts and two depressions (Fig. 1). The northern depocentre is composed of Fitzroy trough and Gregory Sub-basin, and the southern depocentre contains Willara and Kidson Subbasins. Each depocentre is bounded by major fault systems, which separate them from the central arch and from their flanking terraces [3].

Fig. 1. General tectonic elements of Canning Basin and location of study area

Oil and gas exploration in Canning Basin began in 1922. There are about 100 wells and most of them are exploratory wells. By the end of 2015, discovered 25 petroleum reservoirs are mainly in Lennard shelf, Broome and Crossland Platforms, six of which

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are commercial. The six oil fields (Blna, Boundary, Lloyd, Kera West, and Sundown and Terrace West) in Lennard shelf have been put into production since 1980s. Affected by North American shale gas exploration and development, Australia has begun to explore shale gas. Canning, Georgina, Cooper and Maryborough Basins have shale gas exploration potential (Fig. 2).

Fig. 2. Australian shale gas basins [7]

2 Structure and Sedimentary Facies of Goldwyer Formation In Kidson Sub-basin, middle Ordovician can be divided into Nambeet, Willara, Goldwyer and Nita Formations in chronological order. There are four formations in Ordovican. In study area, the structures of Ordovician Nambeet, Willara, Goldwyer and Nita Formations are similar. Their structural inheritance is good, consistent with the current basin structural patterns (Figs. 3, 4, 5 and 6). The thickness of the Ordovician Goldwyer Formation in Canning Basin is 0–558 m (Fig. 7). The lithology of Goldwyer Formation is dominated by shale, which is divided into four members. Structural evolution study of the NW-SE trend in the Kidson Subbasin shows that the Kidson Sub-basin had not yet formed during I and II ages of

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Fig. 3. T0 contour map of the top of Nambeet Formation in study area

Fig. 4. T0 contour map of the top of Willara Formation in study area

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Fig. 5. T0 contour map of the top of Goldwyer Formation in study area

Fig. 6. T0 contour map of the top of Nita Formation in study area

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Fig. 7. Isopach map of Ordovician Goldwyer Formation in Canning Basin

Goldwyer, and started to develope at III and IV ages of the Goldwyer age at Ordovician Carribuddy epoch (Fig. 8). From Ordovician-Silurian Carribuddy epoch, Kidson Subbasin was structurally stable subsided and the main lithology is gypsum and salt rocks which indicates Kidson Sub-basin had formed and continues to today (Fig. 8 and 9). Marine transgresstion flooded and east-west seaway from Canning Basin through to Amadeus Basin from early Ordovician [4]. During Goldwyer stage, the waters of the Canning Basin were shallow, and the main sedimentary environment was tidal plat at Kidson Sub-basin. The lithology of Goldwyer in Kidson Sub-basin dominated by shale. With the sea water retreated from Canning Basin, giant salt developed in the basin (Fig. 9). Well Nicolay-1 was drilled in 2002 and it was the first exploratory well targeting Goldwyer shale gas in Kidson Sub-basin. The top depth of Goldwyer formation is 2826 m and the thickness is 293 m at well Nicolay-1. The sedimentary enviroment in Goldwyer Formation was tidal flat. Sedimentary facies of member I was

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Fig. 8. Tectonic evolution of Kidson Sub-basin

intertidal-subtidal facies with shale. Sedimentary facies of member II was intertidal facies with shale and thin-bedded limestone. Sedimentary facies of member III was intertidal-subtidal facies with shale. Sedimentary facies of member IV was intertidalsupratidal facies with shale and evaporites (Fig. 10).

3 Shale Gas Potential of Goldwyer Formation EIA evaluated shale gas resources of Canning Basin In 2011 and 2013 (Fig. 11 and 12). The Goldwyer shale gas prospective area of Canning Basin was approximately 125,000 km2 in 2011 (Fig. 11). The risked shale gas resource was 764 Tcf, and the risked technically recoverable shale gas resource was 229 Tcf. EIA evaluated Goldwyer shale hydrocarbon prospective area covered about 150,000 km2 in 2013 (Fig. 12). The risked shale oil and gas resources of Goldwyer were 243.7 billion

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Fig. 9. Isopach map of Ordovician Carribuddy Group in Canning Basin

barrelsand 1227.2 Tcf, respectively. The risked technically recoverable shale oil and gas resources were 9.9 billion barrels and 235.4 Tcf, respectively. The data of core, logging and seismic was integrated to predict TOC (Fig. 13). TOC value is less than 0.8% in most of study area which indicates the overall organic matter content of Goldwyer shale in Kidson Sub-basin was poor to fair and organic matter develops in local areas. The Barbwire and Mowla Terraces and the northern Broome Platform are excellent source rocks [5]. It proved this article view is right. The TOC content of Goldwyer Formation at Well Nicolay-1 is less than 1% which is consistent with TOC prediction (Fig. 14). Organic matter in well Nicolay-1 has a poor hydrocarbon generation potential (Fig. 14). Although well Nicolay-1 well is not tested, well logging, sedimentary facies, and geochemical analysis shows that the well and most of Kidson Sub-basin don’t have the potential for shale gas exploration and development.

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Fig. 10. Sedimentary facies of Goldwyer Formation of well Nicolay-1 in Kidson Sub-basin

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Fig. 11. Prospective shale gas and shale oil map of Goldwyer shale in Canning Basin [6]

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Fig. 12. Prospective shale gas and shale oil map of Goldwyer shale in Canning Basin [7]

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Fig. 13. TOC prediction map of Goldwyer shale in Kidson Sub-basin

Fig. 14. TOC and S1 + S2 of Goldwyer shale in well Nicolay-1, Kidson Sub-basin

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4 Conclusion During the sedimentation of the Goldyer shale, Canning Basin was still in early stage of basin development and the water body in the basin was shallow. The sedimentary facies in the study area was mainly tidal flat, which was not conducive to the preservation of organic matter. TOC value is low in most areas of the study area, as confirmed by TOC test results. This article indicates that shale gas exploration potential of Goldyer Formation in Kidson Sub-basin is not as optimistic as EIA and others’ assessments. Shale gas may develop in some areas between Kidson and Willara Subbasins and in Broome Platform close to Kidson Sub-basin. In this study, it is believed that TOC should be taken as the most important parameter to gas shale potential study for an unexplored basin and the depositional history study of basin similar to Canning Basin is nessary excluding structure and sedimentary facies analysis. If TOC meets the standards for shale gas commercial development, studies are focus on the maturity of organic matter to determine liquid proportion in shale gas and then calculate the shale gas resource. Acknowledgements. The research has been founded by the National Science and Technology Major Project of China (2016ZX05029-005).

References 1. Brown SA, Boserio JM, Jackson KS, Spence KW. The geological evolution of the Canning Basin: implications for petroleum exploration. In: Purcell PG, editors. The Canning Basin, WA: Proceedings of Geological Society of Australia/Petroleum Exploration Society of Australia Symposium, PESA; 1984), p. 85–96. 2. Eyles N, Eyles CH, Apak SN, Carlsen GM. Permian–Carboniferous tectono-stratigraphic evolution and petroleum potential of the northern Canning Basin, Western Australia, AAPG Bullitin, 2001;85(6). 3. Triche NE, Bahar M. Shale gas volumetrics of unconventional resource plays in the Canning Basin, Western Australia, SPE Unconventional Resources Conference and Exhibition-Asia Pacific, Brisbane, Australia; 2013. 4. Bradshaw MT, Bradshaw J, Murray AP, Needham DJ, Spencer L, Summons RE, Wilmot J, Winn S. Petroleum systems in west Australian Basins. In: Purcell PG, Purcell RR, editors. The sedimentary basins of Western Australia, PESA; 1994, p. 94–118. 5. Ghori KAR, Haines PW. Paleozoic petroleum systems of the Canning Basin, Western Australia: a review, 2006 AAPG international conference and exhibition. Australia: Perth; 2006. 6. EIA (U.S. Energy Information Administration). World shale gas resources: an initial assessment of 14 regions outside the United States, EIA; 2011. 7. EIA (U.S. Energy Information Administration). World shale gas resources: an initial assessment of 14 regions outside the United States, EIA; 2013.

Evaluation Method of Shale Oil Reservoirs Fracability—A Case from Seventh Member of Triassic Yanchang Formation in Ordos Basin 2018 IFEDC L. B Dou1,2(&), H. Gao2, R. Wang2, and K. Zhao2 1

2

State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum, 102249 Beijing, China [email protected] School of Petroleum Engineering, Xi’an Shiyou University, 710065 Xi’an, China

Abstract. Fracability is the capability of the shale that can be fractured effectively during hydraulic fracturing. Now, the fracability evaluation mainly focuses on shale gas reservoirs, and there are few researches on shale oil reservoirs. Taking the seventh member of Triassic Yanchang formation shale oil reservoirs in the Ordos basin as an example, the geological sweet point of shale oil reservoirs is given in the quantitative evaluation of physical property and geological characteristics of shale oil reservoirs. An evaluation method of shale oil reservoirs fracability is developed combining with the fracture index and fracture toughness based on petrophysical experiments and existing well logging data. The evaluation method is applied to more than 10 wells of Chang 7 reservoirs in which fracability profile is established. The results show that the shale oil reservoirs fracability can be accurately evaluated by the developed model which can be used to screen the fracturing engineering sweet spot. The fracture distribution and fracturing effect of each well were evaluated by combining with the fractured profiles and anisotropic production diagrams of prefrac and post-frac, and the results were compared with the actual fracturing effect of each well. Compared with the adjacent sandstone section, the Chang 7 shale oil reservoir has a lower level of natural fracture development, higher crustal stress and lower brittleness. The study provides a more accurate and

Copyright 2018, Shaanxi Petroleum Society. This paper was prepared for presentation at the 2018 International Field Exploration and Development Conference in Xi’an, China, 18–20 September, 2018. This paper was selected for presentation by the IFEDC Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the IFEDC Committee and are subject to correction by the author(s). The material does not necessarily reflect any position of the IFEDC Committee, its members. Papers presented at the Conference are subject to publication review by Professional Committee of Petroleum Engineering of Shaanxi Petroleum Society. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of Shaanxi Petroleum Society is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of IFEDC. Contact email: [email protected]. © Springer Nature Singapore Pte Ltd. 2020 J. Lin (ed.), Proceedings of the International Field Exploration and Development Conference 2018, Springer Series in Geomechanics and Geoengineering, https://doi.org/10.1007/978-981-13-7127-1_52

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Ordos basin




Fracability




Fracture toughness




Sweet

1 Introduction Shale oil refers to the mature petroleum that is stored in the nano-sized pore of shale stratum with rich organic matter [1]. It is a typical self-reserving, in situ accumulating hydrocarbon, and is an important unconventional oil and gas resource. The preliminary statistics of China’s shale oil reserves are about 30  108 * 60  108 t [1, 2], with broad development prospects. Since shale oil reservoirs have low porosity, low permeability reservoirs and have strong heterogeneity [3–5], the fracturing stimulation measures are necessary to obtain commercial oil flow. Therefore, accurate evaluation of shale oil reservoirs fracability becomes the key to whether shale oil can achieve better development results [6]. At present, the fracability evaluation mainly focuses on shale gas reservoirs, and there are few researches on shale oil reservoirs. Chong et al. [7] summarized the experience of 20 years of shale gas fracturing success in North America and proposed a method to characterize the fracability of shale gas reservoirs using brittleness, that is, to use the shale brittleness index as the only reference to evaluate shale gas reservoirs fracability, which provides insights into the fracturing evaluation of shale oil reservoirs. Based on Chong’s model, many scholars have also established fracability evaluation models for shale gas reservoirs [8]; however, the test results of partial fracturing wells in the study area show that relying solely on brittleness did not provide a comprehensive and accurate assessment of the fracability of shale reservoirs. In the paper, taking the seventh member of Triassic Yanchang Formation(or simply Chang7) in the Ordos basin as an example, evaluate the fracturing performance of shale oil reservoirs in terms of brittleness and fracture toughness of shale oil reservoirs. A shale oil reservoir fracability evaluation model was established and performed to the field application

2 Reservoir Characteristics of Chang7 Shale Oil in Ordos Basin 2.1

Physical Characteristics of Chang7 Shale Oil Reservoir

The Chang 7 lake facies shale has a large thickness and a wide distribution area, which is in line with the basic geological conditions of shale oil accumulation. Figure 1 shows the oil shale distribution and sedimentary facies.

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Fig. 1. Chang 7 oil shale distribution and sedimentary facies

The porosity and the permeability of the Chang 7 shale oil reservoir in Ordos basin are 2.82% and 0.00207  10−3 lm2, respectively. High-pressure mercury injection experiments were conducted on 20 samples in the study area and the maximum pore throat radius of the seven shale oil reservoirs is 0.02 * 2.04 um, with an average of 0.26 um. The throat mean value ranges from 9.99 to 15.63, with an average of 14.57; the sorting coefficient ranges from 0.39 to 2.58, with an average of 1.21; pore throat grading is poor, and there is a strong difference of pore and throat between samples. 2.2

Abundance Characteristics of Organic Matter

The organic matter type of Chang 7 source rock is type I * II. The lake facies shale kerogen is mainly composed of amorphous bodies, which are conducive to the production of oil. The organic matter abundance of Chang 7 section shale layer is high, the TOC content of type I shale is more than 6%, and type II shale is distributed in 2 * 6%. Ro is distributed at 0.9 * 1.2% and is in the mature stage. The two types of oil shales have strong heterogeneity in-plane distribution, thickness distribution, petromineralism characteristics, and reservoir space types. Therefore, the Chang 7

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section shale layer is not only high in organic matter content, but also in the oil generation period, and is a high-quality source rock. 2.3

Mineral Composition Characteristics

An X-ray diffraction spectra analysis experiment of core was performed in the study area, and it was concluded that the Chang 7 oil shale mineral components, including quartz, feldspar (potassic feldspar and plagioclase), carbonate (calcite and dolomite), pyrite, and clay minerals (illite, kaolinite, and chlorite), in which the quartz content ranges from 9.7 to 52.8%, with an average of 28.9%; the feldspar content ranges from 1.2 to 35.1%, with an average of 14.8%; the carbonate content is between 0 and 64.9%, with an average of 20.9%; the pyrite content ranges from 2.4 to 15.9%, with an average of 5.04%; the clay mineral content ranges from 11.2% to 52.6%, with an average of 30.27%. For the Chang 7 sandstone reservoir in Ordos Basin, the average quartz content is 41.8%, the feldspar content is 23.5%, and the clay mineral content is 17.4%. Compared to sandstone reservoirs, the average content of quartz and feldspar in shale oil reservoirs is lower, and the content of clay minerals is higher, indicating that the content of brittle minerals in oil shale in the study area is lower which leads to lower the brittleness index, and hydration expansion is prone to occur caused by higher content of clay minerals.

3 Fracturing Effect Analysis Evaluation of fracturing effects using brittleness as the only reference to evaluate fracability of shale reservoirs in existing models indicates that oil shale reservoirs in the study area are poor in brittleness and have poor fracturing performance. It is unlikely that commercial oil flow will be obtained after fracturing. However, six experimental wells in the study area were put into production after fracturing. The average daily oil output of six experimental wells reached 7.6 t/d, and an average daily output of water was 1.8 m3/d (Table 1), and commercial oil flow with development value has been obtained. In the six experimental wells, only the L70 well and the L58 well had no obvious stimulation effect by fracturing, and the remaining four experimental wells all obtained commercial oil flow, showing good development prospects; therefore, the original model could not accurately evaluate the shale oil reservoirs fracability. Therefore, a new fracability evaluation model for shale oil reservoirs was established by combining the brittleness and fracture toughness of shale oil reservoirs. And the accuracy of the model is verified by performing application on L70 and L58 wells in the study area.

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Table 1. Statistics of the production situation of six experimental wells Lithology Oil shale

Well L295 L189 L53 L70 L92 L58

Average

Test results Daily oil output (t/d) 20.5 13.2 6.6 0 5.1 0 7.6

Daily water output (m3/d) 0.0 0.0 0.0 3.0 3.2 4.4 1.8

4 Fracability Evaluation 4.1

Brittleness Index

Shale brittleness is a property that characterizes shale destroyed without apparent shape change because of the action of external forces and is the most important influencing factor of shale fracturing [9], [10]. Brittle rock is vulnerable to brittle deformation under the action of external forces, forming a network fracturing; while plastic rock is prone to plastic deformation under the action of external forces, and it is not easy to produce fractures. Therefore, the higher brittleness of shale, the higher probability of forming complicated network after fracturing, and the higher of fracability. Poisson’s ratio and Young’s modulus are the main rock mechanics’ parameters that characterize brittleness. The higher shale brittleness is caused by the smaller Poisson’s ratio and the larger Young’s modulus. Taking the Chang 7 shale oil reservoir in Ordos basin as an example, an X-ray diffraction spectra analysis experiment of core was performed in the study area, and it was concluded that the mineral composition of the Chang 7 shale oil reservoir consists of quartz, feldspar, carbonate, pyrite, and clay mineral, and the ternary diagram of the mineral composition is shown in Fig. 2 [11]. The brittleness of mineral components is mainly expressed as the ratio of brittle mineral composition in shale to total mineral content. Brittle minerals include quartz, feldspar, mica, and pyrite. As shown in the ternary diagram of mineral components (Fig. 2), the content of shale brittle minerals (quartz, feldspar, pyrite, etc.) in the Chang 7 Member of Ordos basin is slightly lower than that of the Barnett Group shale in North America. The clay mineral content in the area is slightly higher. It can be seen that the brittle minerals of the Chang 7 shale in the Ordos basin are rich in features, which lays the foundation for shale oil prospecting and evaluation, and is conducive to the storage and development of shale oil. Another method to express rock brittleness is the quantitative analysis method. The Young’s modulus and Poisson’s ratio are taken as the weighted coefficient of 0.5, respectively. There are certain differences in shale rock mechanics parameter distribution in different regions. The maximum and minimum values of Young’s modulus and Poisson’s ratio in Chang 7 shale oil reservoirs are statistically analyzed, and the Young’s

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Fig. 2. Comparison of minerals in the study area with other regions

modulus distribution of Chang 7 shale oil reservoirs is in the range of 11.25–44.1 GPa, and the Poisson’s ratio is in the range of 0.118–0.311. This value is extended upwards and downwards, respectively, to ensure its accuracy. That is, the maximum Young’s modulus is 45 GPa and the minimum value is 10 GPa; the maximum Poisson’s ratio is 0.32 and the minimum is 0.1. According to Rickman’s study [14], the formula for calculating brittleness index Brit is:

0:32  lj Ej  10 þ 0:5  Brit ¼ 0:5  ð0:32  0:1Þ 45  10

ð1Þ

where Ej is static Young’s Modulus of shale, GPa; lj is static Poisson’s ratio of shale, dimensionless. The shale static Young’s modulus and Poisson’s ratio can be calculated by an empirical formula using well logging data. The results of the calculations brought into the Eq. (1) are shown in Table 2.

Table 2. Calculation results of brittleness index Core number Depth/m Static Young’s modulus/GPa

Static Poisson’s ratio Brittleness index

L70-1 L58-1

0.271 0.200

1713 2319

16.74 28.80

0.207 0.540

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Fracture Toughness Index

The brittleness index can be used to characterize the fracability of shale oil reservoirs. It is generally believed that the higher the brittleness is, the better the fracturing performance of shale oil reservoirs can be. This method has a certain reference value, but simply relays on brittleness to evaluate the fracture properties of shale oil reservoirs, the evaluation effect is not accurate enough. For example, the L58 well has a higher brittleness index, but from the post-fracture production data (Table 1), the daily oil output of L58 well is 0, and the daily water output is 4.4 m3/d, indicating that the fracturing performance of the shale section is not ideal, fully reflecting the low accuracy of the evaluation the original model. Shale oil is an unconventional oil and gas resource. Fracturing stimulation measures are needed to obtain commercial production capacity. The fracture toughness characterizes the ease of reservoir fracturing, and reflects the ability of the fracture to maintain its forward extension after fracture initiation. Therefore, the combination of brittleness index and fracture toughness can more accurately characterize the fracability of shale oil reservoirs. Linear elastic fracture mechanics divides the deformation of the fracture front area into open mode (mode I), staggered mode (mode II), and tearing mode (mode III). In the fracturing process of shale reservoirs, fractures are mainly destroyed by mode I and mode II. Jin et al. [12, 13] established equivalent calculation methods for mode I and mode II fracture toughness based on a large number of experimental data. The formula is: Pc ¼ rh  aPp

ð2Þ

KIc ¼ 0:2176Pc þ 0:0059S3t þ 0:0923S2t þ 0:517St  0:3322

ð3Þ

KIIc ¼ 0:0956Pc þ 0:1383St  0:082

ð4Þ

where KIc is mode I fracture toughness, MPa
m0.5; KIIc is mode II fracture toughness, MPa
m0.5; Pc is confining pressure, MPa; St is rock tensile strength, MPa; a is effective stress factor, 0 * 1; Pp is formation pressure, and MPa; rh is minimum horizontal stress, MPa. The parameters, like Pc , St et al., can be calculated by using well-known empirical formulas in petroleum engineering through existing well logging data. Similar to the brittleness index, the fracture toughness can also be represented by a normalized fracture toughness index. The formula is: Kn ¼ 0:5

ðKIcmax  KIc Þ ðKIIcmax  KIIc Þ þ 0:5 ðKIcmax  KIcmin Þ ðKIIcmax  KIIcmin Þ

ð5Þ

where KIcmax and KIcmin are the maximum and minimum values of mode I fracture toughness, MPa
m0.5; KIIcmax and KIIcmin are the maximum and minimum values of mode II fracture toughness, MPa
m0.5.

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Evaluation Model of Shale Oil Reservoirs Fracability

An evaluation method of shale oil reservoirs fracability is developed combining with the fracture index and fracture toughness based on petrophysical experiments and existing well logging data. The formula is: Ffrc ¼ ð1  xÞBrit þ xKn

ð6Þ

where x is Shale reservoir fracture toughness parameter weight coefficient, dimensionless, and 0.4–0.5. The results of the shale oil reservoirs fracability are shown in Table 3. Table 3. Calculation results of fracture parameters Well L70 L58 L295

Depth/m 1713 2319 2646

Brit 0.207 0.540 0.326

KIc 4.900 7.274 15.437

KIIc 2.001 2.691 3.717

Kn 0.612 0.366 0.110

Ffrc 0.369 0.471 0.239

5 Application of Fracability Evaluation Model for Shale Oil Reservoirs Figures 3 and 5 show the fracability profiles of L70 well and L58 well, respectively, based on the model calculation results. Figures 6 and 7 show the orthogonal dipole anisotropy before and after fracturing of L58 well. As shown in the figures, the section of shale oil reservoir is represented by a black line. The log curves are characterized by the high sonic wave time difference (AC), high gamma (GR), and low density (DEN). Within the red line, the fracture height after fracturing is expanded. Figure 4 shows the results of scanning electron microscopy of core from L70 well. Overall, it shows the characteristics of low degree of micro-fracture development. 5.1

Application of Fracability Evaluation Model in L70 Well

As shown in Fig. 3, the shale reservoir section of L70 well is located within 1710 * 1730 m. At 1713 m, compared with the adjacent sandstone section, the brittleness index with fracability index is low. The brittleness index is low, and the probability of fracturing forming complicated network is low; the high ground stress leads to high fracture initiation pressure in the shale section. Figure 4 shows the results of scanning electron microscopy of L70 well. It can be seen that the fractures in micro-nanometer scale are developed and have the characteristics of orientation. However, the overall micro-fractures have a low degree of development. In the fracturing process, it is not conducive to forming fracture network in shale reservoirs section of L70 well. The high fracture toughness indicates that even if the fracture is formed, the ability to maintain the fracture forward extension is weak; the shale section has a low fracability index, which indicates that the well is not recommended to carry out fracturing stimulation in the shale section. From the actual

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Fig. 3. Fracture profile of L70 well

Fig. 4. Scanning electron microscope of L70 well

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Fig. 5. Fracture profile of L58 well

test results of the well (Table 1), the daily oil output of L58 well is 0 t/d, and the daily water output is 3.0 m3/d, indicating that the fracturing performance of the shale section is not ideal. The fracturing stimulation effect is not obvious and the fracturing performance is poor. This is in complete agreement with the calculation and analysis results of this model, which fully proves the accuracy of the model established in this paper.

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Fig. 6. Results of anisotropic transformation before fracturing in L58 well

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Fig. 7. Results of anisotropic transformation after fracturing in L58 well

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Application of Fracability Evaluation Model in L58 Well

As shown in Fig. 5, shale reservoir section of L58 well is located within 2310 * 2340 m. The brittleness index is 0.540 in the depth of 2319 m (Table 2). Compared with adjacent sandstones, shale oil reservoirs have higher effective stress and fracture toughness index, higher brittleness index, but lower fracability index. Comparing the results of the anisotropic formation transformation of the well before and after fracturing (Figs. 6 and 7), it can be seen that the anisotropy and energy difference after fracturing in the 2332.5 * 2339 m interval are significantly higher than before fracturing. The analysis of energy difference and anisotropic imaging before and after fracturing shows that the anisotropy enhancement of this interval is caused by fracture generated in the fracturing process in this section. The fracture extends upward to 2332.5 m and extends downward to 2339 m, and the fracture height is 6.5 m. The higher brittleness index indicates that the higher the probability of obtaining commercial oil flow after fracturing; the higher fracture toughness index indicates the weaker penetrating ability of hydraulic fractures on formation rocks, and the weaker ability to maintain fracture extending forward after fracture formation; the higher effective stress indicates that the crack initiation pressure is relatively large and the crack initiation is difficult; the low fracability index indicates that the oil production of the well is small after fracturing. From the actual fracturing test results of this well (Table 1), it can be seen that the daily oil output of L58 well is 0 t/d, and the daily water output is 4.4 m3/d, indicating that the well did not receive commercial oil flow after fracturing stimulation measures. The development effect is not ideal, and it is completely consistent with the model analysis results. The reason of 0 oil output is that although the fracture has been formed in the shale oil reservoir after fracturing, the fracture height is much smaller than the expected design and the natural fractures development is low. The ability to maintain the forward extension of fracture is weak and the hydraulic fracture cannot be extended to communicate with natural fractures to form fracture network, which is the root cause of its failure to produce oil. At the same time, it is also proved that the use of brittleness index alone cannot accurately evaluate the fracability of shale oil reservoirs.

6 Conclusions (1) The Young’s modulus of the Chang 7 shale oil reservoir in Ordos basin ranges from 11.25 to 44.10 GPa and the Poisson’s ratio ranges from 0.118 to 0.311. Chang 7 shale oil reservoirs have smaller Poisson’s ratio, larger Young’s modulus, and higher brittleness. (2) The method of evaluating fracability of shale oil reservoir with only brittleness as the only reference has certain reference value, but its evaluation result is not accurate enough. An evaluation method of shale oil reservoirs fracability is developed combining with the fracture index and fracture toughness based on petrophysical experiments and existing well logging data. The evaluation model can provide preliminary guidance and theoretical basis for oil shale fracturing well or section selection.

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(3) Using this model, the engineering application of L70 and L58 wells in the study area was carried out. The evaluation results were in good agreement with the actual fracturing results, which fully demonstrated the accuracy of the model. (4) It is suggested to screen the fracturing engineering sweet spot with strong brittleness, low fracture toughness, and high fracability index based on geological sweet point of shale oil reservoirs. Figures Each figure should be explicitly referred to in numerical order and should be embedded within the text at the appropriate point. Each figure should have a caption underneath. Position figures in the text as close as possible to where they are first referred to. Single column figures Acknowledgements. The research was financially supported by the Foundation of State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum, Beijing (No. PRP/open-1703), and the National Natural Science Foundation of China (No. 51604224, 51604225).

References 1. Zou CN, Zhang YJ, Tao SZ, et al. Geological feature, major discoveries and unconventional petroleum geology in the global petroleum exploration. Pet Explor Dev. 2010;37(2):129–45. 2. Zou CN, Yang Z, Cui JZ, et al. Formation mechanism, geological characteristics and development strategy of nonmarine shale oil in China. Pet Explor Dev. 2013;40(1):14–26. 3. Yang H, Niu XB, Xu LM, et al. Exploration potential of shale oil in Chang7 Member, Upper Triassic Yanchang Formation, ordos basin, NW China. Pet Explor Dev. 2016;43(4):511–20. 4. Zhao JZ, Xu WJ, Li YM, et al. A new method for fracability evaluation of shale-gas reservoirs. Nat Gas Geosci. 2015;26(6):1165–72. 5. Lu SF, Xue HT, Wang M, et al. Several key issues and research trends in evaluation of shale oil. Acta Petrolei Sinica. 2016;37(10):1309–22. 6. Tang Y, Xing Y, Li LZ, et al. Influence factors and evaluation methods of the gas shale fracability. Earth Sci Front. 2012;19(5):356–63. 7. Chong KK, Grieser WV, Passman A et al. A completions guide book to shale-play development; A review of successful approaches toward shale-play stimulation in the last two decades. In: Proceedings of Canadian unconventional resources and international petroleum conference. Calgary, Alberta, Canada; 2010, pp. 1–26. 8. Jiang TX, Bian XB, Su Y, et al. A new method for evaluating shale fracability index and its application. Pet Drilling Tech. 2014;42(5):16–20. 9. Qin XY, Wang ZL, Yu HY, et al. Geophysical well logging in brittleness evaluation based on rock mechanics characteristic—a case study from the member 7 shale of Yanchang Formation in southeast Ordos Basin. Prog Geophy. 2016;31(2):762–9. 10. Sheng QH, Li WC. Evaluation method of shale fracability and its application in Jiaoshiba area. Prog Geophy. 2016;31(4):1473–9. 11. Yuan JL, Deng JG, Zhang DY, et al. Fracability evaluation of shale-gas reservoirs. Acta Petrolei Sinica. 2013;34(3):523–7.

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12. Jin Y, Chen M, Wang HY, et al. Study on prediction method of fracture toughness of rock mode II by logging data. Chin J Rock Mechan Eng. 2008;27(S2):3630–5. 13. Jin Y, Chen M, Zhang XD. Determination of fracture toughness for deep well rock with geophysical logging data. Chin J Rock Mechan Eng. 2001;20(4):454–6. 14. Rickman R, Mullen MJ, Petre JE et al. A practical use of shale petrophysics for stimulation design optimization: all shale plays are not clones of the Barnett Shale. In: Proceedings of SPE annual technical conference and exhibition. Denver, Colorado, USA; 2008, pp. 1–11.

High-Precision Magnetic Anomaly and Geological Significance of Shale Gas in Upper Yangtze Region 2018 IFEDC Wendao Qian1, Taiju Yin1(&), Xuesen Li2, Jianping Qian2, Guowei Hou3, and Miao He3 1

2

School of Geosciences of Yangtze University, Wuhan, Hubei 430100, China [email protected] College of Earth Sciences of Guilin University of Technology, Guilin 541004, Guangxi, China 3 Shanghai Branch of CNOOC Ltd, 388# Tongxie Rd, Changning District 200335, Shanghai, China

Abstract. The accumulation pattern of the marine shale gas in South China is different from that in North America. The former has generally thin reservoirs and complex preservation conditions, so it is difficult to make a fine description of the structural features of shale formations and to reflect accurately the distribution pattern of high-quality shale by using the conventional seismic exploration technology. Based on data processing such as data correction, reduction-to-pole of magnetic data, space transforming, derivative conversion, smoothing filter and regularization filter, the magnetic anomalies were observed and analyzed, and the regional geological structure is divided in detail. The magnetic substrate obtained is the magnetic interface of metamorphic rocks equivalent to the Middle Proterozoic top boundary, with a depth of 2–4 km, reflecting the structural morphology and undulating characteristics of the metamorphic crystalline basement. The low parts on the magnetic basement provide the formation and accumulation of the Late Permian-Early Jurassic shale gas in the basin, in which favourable exploration blocks could be found. The fault structure in the study area has two layers of structure in space. The matching relationship between the sedimentary cap fracture and the basement fault controls the spatial distribution of the dominant reservoir together.

Copyright 2018, Shaanxi Petroleum Society. This paper was prepared for presentation at the 2018 International Field Exploration and Development Conference in Xi’an, China, 18–20 September, 2018. This paper was selected for presentation by the IFEDC Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the IFEDC Committee and are subject to correction by the author(s). The material does not necessarily reflect any position of the IFEDC Committee, its members. Papers presented at the Conference are subject to publication review by Professional Committee of Petroleum Engineering of Shaanxi Petroleum Society. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of Shaanxi Petroleum Society is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of IFEDC. Contact email: [email protected]. © Springer Nature Singapore Pte Ltd. 2020 J. Lin (ed.), Proceedings of the International Field Exploration and Development Conference 2018, Springer Series in Geomechanics and Geoengineering, https://doi.org/10.1007/978-981-13-7127-1_53

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Our research can guide shale gas exploration and development in this area and balance the high upstream exploration cost, and continue to push the efficient shale gas exploration and development process in China. Keywords: Shale gas
Magnetic exploration Magnetic basement
Fracture


Cap rock


1 Introduction Shale gas has caused widespread concern both at home and abroad for its wide distribution and large storage. Compared with developed countries such as the United States, however, China’s current investigation and exploration on shale gas resources is relatively low [1–3]. How to overcome various difficulties and vigorously promote the strategic investigation, exploration and development of shale gas resources has become an important and urgent strategic task in the field of oil and gas resources in China [4, 3]. All the time the geophysical methods used in oil and gas exploration is seismic exploration. However, the use of conventional seismic exploration methods are limited for the complex structure and poor seismic data quality, leading to a large difficulty to reservoir interpretation and prediction [2, 5]. The high resistivity carbonate strata block the downward penetration of seismic elastic waves, and thus it is difficult to obtain structural and stratigraphic positions, especially the reliable information in deep part [6, 7]. The two-dimensional seismic exploration in the work area also shows that the quality of the two-dimensional data collected in the field is poor and cannot satisfy the fine interpretation of the formation. In addition, the drilling failure of well TM1 in this area also shows that it is limited to infer the structural characteristics of the target layer only by seismic exploration method. Based on the above facts, it is particularly important to take a variety of geophysical exploration methods to re-understand the structural pattern of the study area.

2 Materials and Methods 2.1

Geological Setting and Samples

The Cen’gong block study area is located in the southwestern part of Tongren city in northeastern Guizhou province, covering a total area of 914 km2 in the Qianbei area (Fig. 1). The tectonic location of the study area is in the trough-like fold belt of western Hunan-Hubei province on the southeastern margin of the Upper Yangtze plate, where the structural conditions and stress fields are complicated due to multi-stage tectonic movements and deformations. The study area experienced Xuefeng (Neoproterozoic), Caledonian, Yanshanian (Jurassic-Cretaceous) and Himalayan multi-phase tectonic movements, and the Yanshanian movement laid the foundation for the current

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geological structures and landforms [8]. Complex structures are developed in the study area and are mainly NE and NNE trending. Stratigraphic from Sinian to Quaternary has different levels of development in Cen’gong shale gas block, and from older to younger they are Fanjing Mountain Group, Banxi Group and Sinian, Niutitang Formation(21n), Bianmachong Formation(21b), Palang Formation(21p), Qingxudong Formation(21q),

Fig. 1. The formation and magnetic position of the study area

Gaotai Formation(22g), Loushanguan Formation(23gls), the lower Ordovician and clay in the Quaternary [8–10] (Fig. 2). In this paper, we make a statistical study about the magnetic property of metamorphic rocks, carbonate rocks, sandstone in survey area (Table 1).The magnetic susceptibility of sedimentary rock in the Sinian system, Cambrian system, Ordovician System and Quaternary System is very weak, varying between 0 and 25  4p
10−6 SI. Rock in Upper Proterozoic mostly is shallow metamorphic rock, and magnetic

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Fig. 2. Columnar section in Cen’gong Shale Gas Block

susceptibility is generally smaller than 25  4p  10−6 SI. The Middle Proterozoic consists of palimpsest tuff, diabase and gabbro, and magnetic susceptibility varies between 12 and 1462  4p  10−6 SI, with an average value 76  4p  10−6 SI. What’s more, there is an unconformity between the Middle Proterozoic and its overlying strata. So the magnetic interface in Cen’gong shale gas block is generally considered as the Middle Proterozoic metamorphic top interface. 2.2

Method for Magnetic Field Data Processing

2.2.1 Normal Field Correction The data taken by the proton magnetometer in the Cen’gong shale gas block are the total magnetic field intensity of the observation point, denoted by T(x, y, t). To obtain the geomagnetic anomaly value DT (T) of the measurement point, the first thing to do is to correct the normal field (Fig. 3). In the data consolidation processing, the total magnetic field intensity observed by the observation points is reduced to the normal geomagnetic field T0(x, y, t), so as to obtain the geomagnetic anomaly value DT1(x, y) without the diurnal variation correction (Formula 1). This method cannot meet the requirements of modern high-precision magnetic measurement. The method we adopt is to use the international geomagnetic reference field model IGRF (International Geomagnetic Reference Field), and thus there is no need to do a horizontal gradient correction [2, 5, 11]. The mathematical model of normal field correction for magnetic measurement is as follows:

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Stratum

Quaternary Cover Ordovician

Symbol Lithology

Q O

Clay Marl, limestone, sandstone, dolomite Cambrian 2 Dolomite, limestone, sandstone, shale Upper Pt3-Z Siliceous, shale, proterozoic dolomire Pt3-Nh Shale, carbonate rock Lower Basement Pt2 Palimpsest stuff, proterozoic diabase, gabbro

Magnetic susceptibility K (4p  10−6) SI Change Means range 0–5 1 1–25 3–5

Magnetic remanence Mr (10−3A/m) Change range

Means

1–38

= 5 cp), the water cut increases after liquid increasing, but the increase extent of water cut is less than that of the original trend. When the viscosity of the crude oil is relatively small (uo