Reservoir and lithofacies shale classification based on NMR logging
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 (...
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| Format: | Article |
| Language: | English |
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KeAi Communications Co., Ltd.
2020-09-01
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| Series: | Petroleum Research |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2096249520300193 |
| _version_ | 1818791460666867712 |
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| author | Hongyan Yu Zhenliang Wang Fenggang Wen Reza Rezaee Maxim Lebedev Xiaolong Li Yihuai Zhang Stefan Iglauer |
| author_facet | Hongyan Yu Zhenliang Wang Fenggang Wen Reza Rezaee Maxim Lebedev Xiaolong Li Yihuai Zhang Stefan Iglauer |
| author_sort | Hongyan Yu |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-18T15:11:42Z |
| format | Article |
| id | doaj.art-e4e4d4f35ac4417cbc43958faa19628c |
| institution | Directory Open Access Journal |
| issn | 2096-2495 |
| language | English |
| last_indexed | 2024-12-18T15:11:42Z |
| publishDate | 2020-09-01 |
| publisher | KeAi Communications Co., Ltd. |
| record_format | Article |
| series | Petroleum Research |
| spelling | doaj.art-e4e4d4f35ac4417cbc43958faa19628c2022-12-21T21:03:39ZengKeAi Communications Co., Ltd.Petroleum Research2096-24952020-09-0153202209Reservoir and lithofacies shale classification based on NMR loggingHongyan Yu0Zhenliang Wang1Fenggang Wen2Reza Rezaee3Maxim Lebedev4Xiaolong Li5Yihuai Zhang6Stefan Iglauer7State Key Laboratory of Continental Dynamics, National and Local Joint Engineering Research Center for Carbon Capture Utilization and Sequestration, Department of Geology, Northwest University, Xi’an, 710069, China; WA School of Mines: Minerals, Energy and Chemical Engineering, Curtin University, 26 Dick Perry Avenue, 6151, Kensington, Australia; Corresponding author. State Key Laboratory of Continental Dynamics, National and Local Joint Engineering Research Center for Carbon Capture Utilization and Sequestration, Department of Geology, Northwest University, Xi’an, 710069, China.State Key Laboratory of Continental Dynamics, National and Local Joint Engineering Research Center for Carbon Capture Utilization and Sequestration, Department of Geology, Northwest University, Xi’an, 710069, ChinaInstitute of Shaanxi Yanchang Petroleum Group Co.,Ltd, Xi’an, Shaanxi, 710075, ChinaWA School of Mines: Minerals, Energy and Chemical Engineering, Curtin University, 26 Dick Perry Avenue, 6151, Kensington, AustraliaWA School of Mines: Minerals, Energy and Chemical Engineering, Curtin University, 26 Dick Perry Avenue, 6151, Kensington, AustraliaState Key Laboratory of Continental Dynamics, National and Local Joint Engineering Research Center for Carbon Capture Utilization and Sequestration, Department of Geology, Northwest University, Xi’an, 710069, ChinaDepartment of Earth Science and Engineering, Imperial College London, London, SW7 2BP, United KingdomShool of Engineering, Edith Cowan University, 270 Joondalup Drive, WA, 6027, AustraliaShale 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.http://www.sciencedirect.com/science/article/pii/S2096249520300193Shale gasNMR loggingPore size distributionComposition |
| spellingShingle | Hongyan Yu Zhenliang Wang Fenggang Wen Reza Rezaee Maxim Lebedev Xiaolong Li Yihuai Zhang Stefan Iglauer Reservoir and lithofacies shale classification based on NMR logging Petroleum Research Shale gas NMR logging Pore size distribution Composition |
| title | Reservoir and lithofacies shale classification based on NMR logging |
| title_full | Reservoir and lithofacies shale classification based on NMR logging |
| title_fullStr | Reservoir and lithofacies shale classification based on NMR logging |
| title_full_unstemmed | Reservoir and lithofacies shale classification based on NMR logging |
| title_short | Reservoir and lithofacies shale classification based on NMR logging |
| title_sort | reservoir and lithofacies shale classification based on nmr logging |
| topic | Shale gas NMR logging Pore size distribution Composition |
| url | http://www.sciencedirect.com/science/article/pii/S2096249520300193 |
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