Petroleum Science2025，Vol.22Issue(10)：P.4240-4253,14.DOI:10.1016/j.petsci.2025.06.007
Physics-informed graph neural network for predicting fluid flow in porous media
Hai-Yang Chen 1Liang Xue 1Li Liu 2Gao-Feng Zou 3Jiang-Xia Han 4Yu-Bin Dong 4Meng-Ze Cong 4Yue-Tian Liu 1Seyed Mojtaba Hosseini-Nasab5
作者信息
- 1. State Key Laboratory of Petroleum Resources and Engineering,China University of Petroleum,Beijing,102249,China Department of Oil-Gas Field Development Engineering,College of Petroleum Engineering,China University of Petroleum,Beijing,102249,China
- 2. Research Institute of Exploration and Development,Sinopec Jianghan Oilfield Branch Company,Wuhan,430223,Hubei,China
- 3. Department of Oil-Gas Field Development Engineering,College of Petroleum Engineering,China University of Petroleum,Beijing,102249,China Research Institute of Exploration and Development,Sinopec Jianghan Oilfield Branch Company,Wuhan,430223,Hubei,China
- 4. Department of Oil-Gas Field Development Engineering,College of Petroleum Engineering,China University of Petroleum,Beijing,102249,China
- 5. School of Chemical Engineering,Petroleum and Gas Engineering Iran University of Science and Technology,Tehran,1684613114,Iran Department of Geoscience&Engineering,Petroleum Engineering Group,Delft University of Technology,Netherlands
- 折叠
摘要
关键词
Graph neural network(GNN)/Deep-learning/Physical-informed neural network(PINN)/Physics-informed graph neural network(PIGNN)/Flow in porous media/Perpendicular bisectional grid(PEBI)/Unstructured mesh分类
信息技术与安全科学引用本文复制引用
Hai-Yang Chen,Liang Xue,Li Liu,Gao-Feng Zou,Jiang-Xia Han,Yu-Bin Dong,Meng-Ze Cong,Yue-Tian Liu,Seyed Mojtaba Hosseini-Nasab..Physics-informed graph neural network for predicting fluid flow in porous media[J].Petroleum Science,2025,22(10):P.4240-4253,14.基金项目
supported by the National Natural Science Foundation of China (No. 52274048) （No. 52274048）
Beijing Natural Science Foundation (No. 3222037)。 （No. 3222037）
