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Reservoir and lithofacies shale classification based on NMR logging

Petroleum Research 2020年第3期5卷 202-209页

作者： Hongyan Yu Zhenliang Wang Fenggang Wen Reza Rezaee Maxim Lebedev Xiaolong Li Yihuai Zhang stefan iglauer State Key Laboratory of Continental Dynamics National and Local Joint Engineering Research Center for Carbon Capture Utilization and SequestrationDepartment of GeologyNorthwest UniversityXi’an710069China WA School of Mines:Minerals Energy and Chemical EngineeringCurtin University26 Dick Perry Avenue6151KensingtonAustralia Institute of Shaanxi Yanchang Petroleum Group Co. LtdXi’anShaanxi710075China Department of Earth Science and Engineering Imperial College LondonLondonSW72BPUnited Kingdom Shool of Engineering Edith Cowan University270 Joondalup DriveWA6027Australia

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.

关键词： Shale gas NMR logging Pore size distribution Composition

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