most citedDeep Reinforcement Learning for Constrained Field Development Optimization in Subsurface Two-phase Flow

35 citations · 35 across the 1 of their papers we have counts for

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1 paper

cs.LG2021★ 35 cited

Deep Reinforcement Learning for Constrained Field Development Optimization in Subsurface Two-phase Flow

Yusuf Nasir, Jincong He, Chaoshun Hu +3

We present a deep reinforcement learning-based artificial intelligence agent that could provide optimized development plans given a basic description of the reservoir and rock/flui…