Petrophysical and capillary pressure properties of the upper Triassic Xujiahe Formation tight gas sandstones in western Sichuan,China

作     者：Ye Sujuan Lu Zhengxiang Li Rong Ye Sujuan~1,L(u|¨) Zhengxiang~1 and Li Rong~2 1 Exploration and Production Research Institute,Sinopec Southwest Company,Sichuan 610081,China 2 Chengdu Institute of Geology and Mineral Resources,Sichuan 610081,China

作者机构：Exploration and Production Research InstituteSinopec Southwest CompanySichuan 610081China Chengdu Institute of Geology and Mineral ResourcesSichuan 610081China 

出 版 物：《Petroleum Science》 (石油科学（英文版）)

年 卷 期：2011年第8卷第1期

页      面：34-42页

核心收录：

学科分类：0709[理学-地质学] 0819[工学-矿业工程] 0808[工学-电气工程] 07[理学] 08[工学] 0820[工学-石油与天然气工程] 070901[理学-矿物学、岩石学、矿床学] 0707[理学-海洋科学] 0817[工学-化学工程与技术] 0818[工学-地质资源与地质工程] 0708[理学-地球物理学] 0807[工学-动力工程及工程热物理] 0815[工学-水利工程] 0816[工学-测绘科学与技术] 0827[工学-核科学与技术] 0813[工学-建筑学] 0703[理学-化学] 0814[工学-土木工程] 0825[工学-航空宇航科学与技术] 0704[理学-天文学] 082002[工学-油气田开发工程] 

基　　金：supported by the Important National Science&Technology Specific Project (2008ZX05002-004) 

主　　题：Western Sichuan upper Triassic Xujiahe Formation tight sandstones permeability porosity pore throat radius regression analysis artificial neural network 

摘      要：The tight sandstones of the Upper Triassic Xujiahe Formation（T_3x） constitute important gas reservoirs in western *** Xujiahe sandstones are characterized by low to very low porosity （av.5.22%and 3.62%） for the T_3x^4 and T_3x^2 sandstones,respectively）,extremely low permeability（av. 0.060 mD and 0.058 mD for the T_3x^4 and T_3x^2 sandstones,respectively）,strong heterogeneity,micronano pore throat,and poor pore throat *** a result of complex pore structure and the occurrence of fractures,weak correlations exist between petrophysical properties and pore throat size,demonstrating that porosity or pore throat size alone does not serve as a good permeability *** improved correlations can be obtained between permeability and porosity when pore throat radii are incorporated. Correlations between porosity,permeability,and pore throat radii corresponding to different saturations of mercury were established,showing that the pore throat radius at 20%mercury saturation（R_（20）） is the best permeability *** regression analysis and artificial neural network（ANN） methods were used to establish permeability prediction models and the unique characteristics of neural networks enable them to be more successful in predicting permeability than the multivariate regression *** addition, four petrophysical rock types can be identified based on the distributions of R_（20）,each exhibiting distinct petrophysical properties and corresponding to different flow units.