Deep Learning-Based Prediction of Subsurface Oil Reservoir Pressure Using Spatio-Temporal Data
Author:
Affiliation:
1. Shenyang Institute of Automation, Chinese Academy of Sciences,State Key Laboratory of Robotics,Shenyang,China
2. Luleå University of Technology,Department of Computer Science, Electrical and Space Engineering,Luleå,Sweden
Funder
National Natural Science Foundation of China
State Key Laboratory of Robotics of China
Natural Science Foundation of Liaoning Province
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10311571/10311610/10312480.pdf?arnumber=10312480
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1. Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involing nonlinear partial differential equations;raissi;Journal of Computational Physics,2019
2. Solving inverse problems using conditional invertible neural networks
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1. Residual-Enhanced Physics-Guided Machine Learning With Hard Constraints for Subsurface Flow in Reservoir Engineering;IEEE Transactions on Geoscience and Remote Sensing;2024
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