Qiangqiang Mao

Reinforcement Learning for Optimized Well Placement in Underground Hydrogen Storage

Abstract Well placement design for underground hydrogen storage (UHS) faces the challenge of balancing hydrogen recovery, costs, and operational constraints. This study develops a rule-guided reinforcement learning (RL) framework to jointly optimize well count and well locations for a depleted gas reservoir in Alberta,...