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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Main Authors: HUANG Lei, QI Yin, CHEN Weihua, DU Xianfei, MA Bing, TANG Jizhou
Format: Article
Language:zho
Published: Editorial Office of Well Logging Technology 2023-08-01
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.
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institution OA Journals
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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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