Reservoir Fluid Identification Method Based on Multi-Feature Fusion
The resistivity of tight sandstone reservoirs in Sulige gas field is greatly affected by the mineralization degree of formation water and siliceous cementation, resulting in the phenomenon of “high resistivity water layer” and difficulty in identifying reservoir fluids. We extract frequency domain i...
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| Format: | Article |
| Language: | zho |
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Editorial Office of Well Logging Technology
2024-12-01
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| Series: | Cejing jishu |
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| Online Access: | https://www.cnpcwlt.com/#/digest?ArticleID=5674 |
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| author | JIANG Guoqiang WU Youbin LAI Fuqiang HUANG Zhaohui YI Hongmei LI Quan LI Xu WANG Qi LUO Rongtao |
| author_facet | JIANG Guoqiang WU Youbin LAI Fuqiang HUANG Zhaohui YI Hongmei LI Quan LI Xu WANG Qi LUO Rongtao |
| author_sort | JIANG Guoqiang |
| collection | DOAJ |
| description | The resistivity of tight sandstone reservoirs in Sulige gas field is greatly affected by the mineralization degree of formation water and siliceous cementation, resulting in the phenomenon of “high resistivity water layer” and difficulty in identifying reservoir fluids. We extract frequency domain information from well logging curves using time-frequency analysis methods, construct a set of time-frequency images, and extract local binary pattern (LBP) and histograms of oriented gradients (HOG) features from time-frequency image data to construct a fused feature matrix of LBP and HOG. Based on support vector machine (SVM), the fluid information of the fused feature matrix is recognized, and a reservoir fluid recognition method based on fused multiple features is established. This method has a good recognition effect on the properties of gas and water fluids, with an average recognition accuracy of 83.2% on the test set. Field applications have shown that compared with the optimized logging interpretation method and the time-frequency analysis method alone, the reservoir fluid identification method based on fused multiple features improves the accuracy of fluid identification in tight sandstone reservoirs, with an average identification accuracy of 90.4%, verifying the feasibility of using this method to identify fluids. The reservoir fluid identification method based on fusion of multiple features has improved the accuracy of gas water identification in tight sandstone reservoirs, and can effectively identify the fluid properties of tight sandstone reservoirs. |
| format | Article |
| id | doaj-art-a5805f9355ea4fa7a08c4d9b73e738b4 |
| institution | DOAJ |
| issn | 1004-1338 |
| language | zho |
| publishDate | 2024-12-01 |
| publisher | Editorial Office of Well Logging Technology |
| record_format | Article |
| series | Cejing jishu |
| spelling | doaj-art-a5805f9355ea4fa7a08c4d9b73e738b42025-08-20T03:08:18ZzhoEditorial Office of Well Logging TechnologyCejing jishu1004-13382024-12-0148680581310.16489/j.issn.1004-1338.2024.06.0091004-1338(2024)06-0805-09Reservoir Fluid Identification Method Based on Multi-Feature FusionJIANG Guoqiang0WU Youbin1LAI Fuqiang2HUANG Zhaohui3YI Hongmei4LI Quan5LI Xu6WANG Qi7LUO Rongtao8Geological Research Institute, China National Logging Corporation, Xi'an, Shaanxi 710077, ChinaGeological Research Institute, China National Logging Corporation, Xi'an, Shaanxi 710077, ChinaCollege of Petroleum and Natural Gas Engineering, Chongqing University of Scienceand Technology, Chongqing 401331, ChinaCollege of Petroleum and Natural Gas Engineering, Chongqing University of Scienceand Technology, Chongqing 401331, ChinaGeological Research Institute, China National Logging Corporation, Xi'an, Shaanxi 710077, ChinaGeological Research Institute, China National Logging Corporation, Xi'an, Shaanxi 710077, ChinaGeological Research Institute, China National Logging Corporation, Xi'an, Shaanxi 710077, ChinaGeological Research Institute, China National Logging Corporation, Xi'an, Shaanxi 710077, ChinaGeological Research Institute, China National Logging Corporation, Xi'an, Shaanxi 710077, ChinaThe resistivity of tight sandstone reservoirs in Sulige gas field is greatly affected by the mineralization degree of formation water and siliceous cementation, resulting in the phenomenon of “high resistivity water layer” and difficulty in identifying reservoir fluids. We extract frequency domain information from well logging curves using time-frequency analysis methods, construct a set of time-frequency images, and extract local binary pattern (LBP) and histograms of oriented gradients (HOG) features from time-frequency image data to construct a fused feature matrix of LBP and HOG. Based on support vector machine (SVM), the fluid information of the fused feature matrix is recognized, and a reservoir fluid recognition method based on fused multiple features is established. This method has a good recognition effect on the properties of gas and water fluids, with an average recognition accuracy of 83.2% on the test set. Field applications have shown that compared with the optimized logging interpretation method and the time-frequency analysis method alone, the reservoir fluid identification method based on fused multiple features improves the accuracy of fluid identification in tight sandstone reservoirs, with an average identification accuracy of 90.4%, verifying the feasibility of using this method to identify fluids. The reservoir fluid identification method based on fusion of multiple features has improved the accuracy of gas water identification in tight sandstone reservoirs, and can effectively identify the fluid properties of tight sandstone reservoirs.https://www.cnpcwlt.com/#/digest?ArticleID=5674tight sandstonetime-frequency analysissupport vector machinelocal binary patternhistogram of oriented gradients |
| spellingShingle | JIANG Guoqiang WU Youbin LAI Fuqiang HUANG Zhaohui YI Hongmei LI Quan LI Xu WANG Qi LUO Rongtao Reservoir Fluid Identification Method Based on Multi-Feature Fusion Cejing jishu tight sandstone time-frequency analysis support vector machine local binary pattern histogram of oriented gradients |
| title | Reservoir Fluid Identification Method Based on Multi-Feature Fusion |
| title_full | Reservoir Fluid Identification Method Based on Multi-Feature Fusion |
| title_fullStr | Reservoir Fluid Identification Method Based on Multi-Feature Fusion |
| title_full_unstemmed | Reservoir Fluid Identification Method Based on Multi-Feature Fusion |
| title_short | Reservoir Fluid Identification Method Based on Multi-Feature Fusion |
| title_sort | reservoir fluid identification method based on multi feature fusion |
| topic | tight sandstone time-frequency analysis support vector machine local binary pattern histogram of oriented gradients |
| url | https://www.cnpcwlt.com/#/digest?ArticleID=5674 |
| work_keys_str_mv | AT jiangguoqiang reservoirfluididentificationmethodbasedonmultifeaturefusion AT wuyoubin reservoirfluididentificationmethodbasedonmultifeaturefusion AT laifuqiang reservoirfluididentificationmethodbasedonmultifeaturefusion AT huangzhaohui reservoirfluididentificationmethodbasedonmultifeaturefusion AT yihongmei reservoirfluididentificationmethodbasedonmultifeaturefusion AT liquan reservoirfluididentificationmethodbasedonmultifeaturefusion AT lixu reservoirfluididentificationmethodbasedonmultifeaturefusion AT wangqi reservoirfluididentificationmethodbasedonmultifeaturefusion AT luorongtao reservoirfluididentificationmethodbasedonmultifeaturefusion |