Shale gas reservoirs have fine-grained textures and high organic contents,leading to complex pore structures.Therefore,accurate well-log derived pore size distributions are difficult to acquire for this unconventional...Shale gas reservoirs have fine-grained textures and high organic contents,leading to complex pore structures.Therefore,accurate well-log derived pore size distributions are difficult to acquire for this unconventional reservoir type,despite their importance.However,nuclear magnetic resonance(NMR)logging can in principle provide such information via hydrogen relaxation time measurements.Thus,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,respectively.Thus the number of the NMR peaks,their relaxation times and amplitudes were analyzed to characterize pore size distributions and lithofacies.Seven pore size distribution classes were distinguished;these were verified independently with Pulsed-Neutron Spectrometry(PNS)well-log data.This 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.展开更多
基金National Natural Science Foundation of China(41902145)Natural Science Basic Research Plan in Shaanxi Province of China(2020JQ-594)+2 种基金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 Governmentsupported 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.
文摘Shale gas reservoirs have fine-grained textures and high organic contents,leading to complex pore structures.Therefore,accurate well-log derived pore size distributions are difficult to acquire for this unconventional reservoir type,despite their importance.However,nuclear magnetic resonance(NMR)logging can in principle provide such information via hydrogen relaxation time measurements.Thus,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,respectively.Thus the number of the NMR peaks,their relaxation times and amplitudes were analyzed to characterize pore size distributions and lithofacies.Seven pore size distribution classes were distinguished;these were verified independently with Pulsed-Neutron Spectrometry(PNS)well-log data.This 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.
