Reservoir and lithofacies shale classification based on NMR logging
作者机构：State Key Laboratory of Continental DynamicsNational and Local Joint Engineering Research Center for Carbon Capture Utilization and SequestrationDepartment of GeologyNorthwest UniversityXi’an710069China WA School of Mines:MineralsEnergy and Chemical EngineeringCurtin University26 Dick Perry Avenue6151KensingtonAustralia Institute of Shaanxi Yanchang Petroleum Group Co.LtdXi’anShaanxi710075China Department of Earth Science and EngineeringImperial College LondonLondonSW72BPUnited Kingdom Shool of EngineeringEdith Cowan University270 Joondalup DriveWA6027Australia
出 版 物：《Petroleum Research》 (石油研究（英文）)
年 卷 期：2020年第5卷第3期
页 面：202-209页
核心收录：
学科分类：081803[工学-地质工程] 08[工学] 0818[工学-地质资源与地质工程]
基 金：National Natural Science Foundation of China(41902145) Natural Science Basic Research Plan in Shaanxi Province of China(2020JQ-594) Young Talent fund of University Association for Science and Technology in Shaanxi,China(20180701) National and Local Joint Engineering Research Center for Carbon Capture Utilization and Sequestration at Northwest University in China.The measurements were performed using the mCT system of the National Geosequestration Laboratory(NGL)of Australia.Funding for the facilities was provided by the Australian Federal Government supported by the Pawsey Supercomputing Centre,who provided the Avizo 9.5 image processing software and workstation,with funding from the Australian Government and the Government of Western Australia
主 题：Shale gas NMR logging Pore size distribution Composition
摘 要：Shale gas reservoirs have fine-grained textures and high organic contents,leading to complex pore ***,accurate well-log derived pore size distributions are difficult to acquire for this unconventional reservoir type,despite their ***,nuclear magnetic resonance(NMR)logging can in principle provide such information via hydrogen relaxation time ***,in this paper,NMR response curves(of shale samples)were rigorously mathematically analyzed(with an Expectation Maximization algorithm)and categorized based on the NMR data and their geology,*** the number of the NMR peaks,their relaxation times and amplitudes were analyzed to characterize pore size distributions and *** pore size distribution classes were distinguished;these were verified independently with Pulsed-Neutron Spectrometry(PNS)well-log *** study thus improves the interpretation of well log data in terms of pore structure and mineralogy of shale reservoirs,and consequently aids in the optimization of shale gas extraction from the subsurface.
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