Complementary testing and machine learning techniques for the characterization and prediction of middle Permian tight gas sandstone reservoir quality in the northeastern Ordos Basin, China  

作　　者：Zi-Yi Wang Shuang-Fang Lu Neng-Wu Zhou Yan-Cheng Liu Li-Ming Lin Ya-Xin Shang Jun Wang Guang-Shun Xiao 

机构地区：[1]State Key Laboratory of Deep Oil and Gas,China University of Petroleum(East China),Qingdao,266580,China [2]Sanya Offshore Oil&Gas Research Institute,Northeast Petroleum University,Sanya,572025,Hainan,China [3]Key Laboratory of Continental Shale Hydrocarbon Accumulation and Efficient Development,Ministry of Education,Northeast Petroleum University,Daqing,163318,Heilongjiang,China [4]China United Coalbed Methane Corporation Ltd.,Beijing,100083,China

出　　处：《Petroleum Science》2024年第5期2946-2968,共23页石油科学（英文版）

基　　金：financially supported by the National Natural Science Foundation of China (No. 42272156);research on efficient exploration and development technology for tight stone gas of China United Coalbed Methane Corporation (No. ZZGSECCYWG 2021-322)。

摘　　要：In this study, an integrated approach for diagenetic facies classification, reservoir quality analysis and quantitative wireline log prediction of tight gas sandstones(TGSs) is introduced utilizing a combination of fit-for-purpose complementary testing and machine learning techniques. The integrated approach is specialized for the middle Permian Shihezi Formation TGSs in the northeastern Ordos Basin, where operators often face significant drilling uncertainty and increased exploration risks due to low porosities and micro-Darcy range permeabilities. In this study, detrital compositions and diagenetic minerals and their pore type assemblages were analyzed using optical light microscopy, cathodoluminescence, standard scanning electron microscopy, and X-ray diffraction. Different types of diagenetic facies were delineated on this basis to capture the characteristic rock properties of the TGSs in the target formation.A combination of He porosity and permeability measurements, mercury intrusion capillary pressure and nuclear magnetic resonance data was used to analyze the mechanism of heterogeneous TGS reservoirs.We found that the type, size and proportion of pores considerably varied between diagenetic facies due to differences in the initial depositional attributes and subsequent diagenetic alterations;these differences affected the size, distribution and connectivity of the pore network and varied the reservoir quality. Five types of diagenetic facies were classified:(i) grain-coating facies, which have minimal ductile grains, chlorite coatings that inhibit quartz overgrowths, large intergranular pores that dominate the pore network, the best pore structure and the greatest reservoir quality;(ii) quartz-cemented facies,which exhibit strong quartz overgrowths, intergranular porosity and a pore size decrease, resulting in the deterioration of the pore structure and reservoir quality;(iii) mixed-cemented facies, in which the cementation of various authigenic minerals increases the micropores, resulting in a poor pore

关 键 词：Diagenetic facies Reservoir quality Wireline log prediction Machine learning techniques Tight gas sandstones 

分 类 号：TE37[石油与天然气工程—油气田开发工程] TP181[自动化与计算机技术—控制理论与控制工程]