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Parallel Automatic History Matching Algorithm Using Reinforcement Learning.
- Source :
- Energies (19961073); Jan2023, Vol. 16 Issue 2, p860, 27p
- Publication Year :
- 2023
-
Abstract
- Reformulating the history matching problem from a least-square mathematical optimization problem into a Markov Decision Process introduces a method in which reinforcement learning can be utilized to solve the problem. This method provides a mechanism where an artificial deep neural network agent can interact with the reservoir simulator and find multiple different solutions to the problem. Such a formulation allows for solving the problem in parallel by launching multiple concurrent environments enabling the agent to learn simultaneously from all the environments at once, achieving significant speed up. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 19961073
- Volume :
- 16
- Issue :
- 2
- Database :
- Complementary Index
- Journal :
- Energies (19961073)
- Publication Type :
- Academic Journal
- Accession number :
- 161434928
- Full Text :
- https://doi.org/10.3390/en16020860