A Geomechanical Modeling Method for Shale Oil Reservoir Cluster Well Area Based on GridSearchCV
In response to the challenges posed by the close proximity of Changqing shale oil well factory to water sources, forest sources, and other environmental protection zones, as well as the low efficiency and lack of geomechanical understanding in traditional well factory models, this study proposes and...
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| Format: | Article |
| Language: | zho |
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Editorial Office of Well Logging Technology
2023-08-01
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| Series: | Cejing jishu |
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| Online Access: | https://www.cnpcwlt.com/#/digest?ArticleID=5508 |
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| author | HUANG Lei QI Yin CHEN Weihua DU Xianfei MA Bing TANG Jizhou |
| author_facet | HUANG Lei QI Yin CHEN Weihua DU Xianfei MA Bing TANG Jizhou |
| author_sort | HUANG Lei |
| collection | DOAJ |
| description | In response to the challenges posed by the close proximity of Changqing shale oil well factory to water sources, forest sources, and other environmental protection zones, as well as the low efficiency and lack of geomechanical understanding in traditional well factory models, this study proposes and implements a new cluster well factory model (sectorial wells and conventional wells). Using the shale oil reservoir in block H as a case study, this research initially carries out the adjustment of reservoir physical properties and rock mechanical parameters, derived from the comprehensive analysis of well logging data. Subsequently, it integrates with a three-dimensional mesh Kriging interpolation model and optimize the Kriging interpolation parameters through GridSearchCV, which is a gridsearch and K-folder cross-validation method in the Scikit-learn machine learning. Finally, it establishes a three-dimensional geomechanical model considering reservoir lithofacies, physical properties, and geomechanical characteristics, and then predicts the geomechanical parameters of a certain cluster well factory. The reliability of the three-dimensional geomechanical model is validated by comparing numerical simulation results with well logging interpretation results. This study is a rapid and efficient geomechanical modeling method to optimize the data required for fracturing site operations. |
| format | Article |
| id | doaj-art-b4ecfa47b9f54f38b2ccc6ba7d16cbc9 |
| institution | OA Journals |
| issn | 1004-1338 |
| language | zho |
| publishDate | 2023-08-01 |
| publisher | Editorial Office of Well Logging Technology |
| record_format | Article |
| series | Cejing jishu |
| spelling | doaj-art-b4ecfa47b9f54f38b2ccc6ba7d16cbc92025-08-20T01:55:22ZzhoEditorial Office of Well Logging TechnologyCejing jishu1004-13382023-08-0147442143110.16489/j.issn.1004-1338.2023.04.0051004-1338(2023)04-0421-11A Geomechanical Modeling Method for Shale Oil Reservoir Cluster Well Area Based on GridSearchCVHUANG Lei0QI Yin1CHEN Weihua2DU Xianfei3MA Bing4TANG Jizhou5School of Ocean and Earth Science, Tongji University, Shanghai 200092, ChinaOil and Gas Technology Research Institute, PetroChina Changqing Oilfield Company, Xi’an, Shaanxi 710021, ChinaEngineering Technology Research Institute of Southwest Oil & Field Company, Chengdu, Sichuan 610017, ChinaOil and Gas Technology Research Institute, PetroChina Changqing Oilfield Company, Xi’an, Shaanxi 710021, ChinaOil and Gas Technology Research Institute, PetroChina Changqing Oilfield Company, Xi’an, Shaanxi 710021, ChinaSchool of Ocean and Earth Science, Tongji University, Shanghai 200092, ChinaIn response to the challenges posed by the close proximity of Changqing shale oil well factory to water sources, forest sources, and other environmental protection zones, as well as the low efficiency and lack of geomechanical understanding in traditional well factory models, this study proposes and implements a new cluster well factory model (sectorial wells and conventional wells). Using the shale oil reservoir in block H as a case study, this research initially carries out the adjustment of reservoir physical properties and rock mechanical parameters, derived from the comprehensive analysis of well logging data. Subsequently, it integrates with a three-dimensional mesh Kriging interpolation model and optimize the Kriging interpolation parameters through GridSearchCV, which is a gridsearch and K-folder cross-validation method in the Scikit-learn machine learning. Finally, it establishes a three-dimensional geomechanical model considering reservoir lithofacies, physical properties, and geomechanical characteristics, and then predicts the geomechanical parameters of a certain cluster well factory. The reliability of the three-dimensional geomechanical model is validated by comparing numerical simulation results with well logging interpretation results. This study is a rapid and efficient geomechanical modeling method to optimize the data required for fracturing site operations.https://www.cnpcwlt.com/#/digest?ArticleID=5508shale oilcluster wellgeological modelrock mechanical parametergridsearchcvhyperparameter tuning |
| spellingShingle | HUANG Lei QI Yin CHEN Weihua DU Xianfei MA Bing TANG Jizhou A Geomechanical Modeling Method for Shale Oil Reservoir Cluster Well Area Based on GridSearchCV Cejing jishu shale oil cluster well geological model rock mechanical parameter gridsearchcv hyperparameter tuning |
| title | A Geomechanical Modeling Method for Shale Oil Reservoir Cluster Well Area Based on GridSearchCV |
| title_full | A Geomechanical Modeling Method for Shale Oil Reservoir Cluster Well Area Based on GridSearchCV |
| title_fullStr | A Geomechanical Modeling Method for Shale Oil Reservoir Cluster Well Area Based on GridSearchCV |
| title_full_unstemmed | A Geomechanical Modeling Method for Shale Oil Reservoir Cluster Well Area Based on GridSearchCV |
| title_short | A Geomechanical Modeling Method for Shale Oil Reservoir Cluster Well Area Based on GridSearchCV |
| title_sort | geomechanical modeling method for shale oil reservoir cluster well area based on gridsearchcv |
| topic | shale oil cluster well geological model rock mechanical parameter gridsearchcv hyperparameter tuning |
| url | https://www.cnpcwlt.com/#/digest?ArticleID=5508 |
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