Machine Learning-Driven Multi-Scale Modeling and Digital Twin Evolution for Geothermal Reservoirs and Underground Thermal Storage
This review systematically evaluates machine learning as a foundational paradigm for overcoming computational and scale-bridging challenges in geothermal energy and underground thermal storage, highlighting physics-informed machine learning (PIML) and hybrid architectures that embed conservation laws as strict constrai...