35 citations · 35 across the 2 of their papers we have counts for
2 papers
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…
eess.SP2020
Deep Reinforcement Learning for Field Development Optimization
Yusuf Nasir
The field development optimization (FDO) problem represents a challenging mixed-integer nonlinear programming (MINLP) problem in which we seek to obtain the number of wells, their…