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Efficient Geothermal Well-Control Optimization via Diffusion-Surrogate Reinforcement Learning

arXiv · AI, language, vision and robotics · article · Aug 28, 2026 · UTC

Real-time decision-making for enhanced geothermal systems (EGS) is challenging because long-term production periods involve high-dimensional control spaces and a large number of time-consuming high-fidelity hydrothermal simulations. Reinforcement learning provides a natural framework for state-dependent sequential control, but direct policy training with numerical simulators is computationally expensive. To address this issue, we propose a diffusion-surrogate guided reinforcement learning framework for long-horizon EGS well-control optimization. The reservoir temperature and pressure fields ar

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