Qiuhao Chang, David Dempsey, Guilong Xu, Liehui Zhang, Yulong Zhao
Hydrogen leakage through abandoned wells represents a critical risk for underground hydrogen storage (UHS) in depleted gas reservoirs, potentially leading to safety hazards and economic losses. Although reservoir-scale numerical simulations can capture leakage processes in detail, their computational cost limits their use in rapid scenario screening and early-stage design assessment. In this work, a probabilistic surrogate framework is developed to evaluate leakage likelihood under varying geological and operational conditions. The framework is intended as an early-stage screening tool to identify configurations that may pose a leakage risk and therefore warrant further detailed investigation. The surrogate is constructed using multiphase reservoir simulation results and incorporates six continuous variables together with ten families of H 2 -water relative permeability curves spanning a range of low to high mobility that collectively represent structural uncertainty in gas–water flow. Validation against an independent simulation dataset shows that the surrogate achieves an overall prediction accuracy of 0.967 with an area under the ROC curve (AUC) of 0.995. Results indicate that, within the investigated ranges and under homogeneous reservoir conditions, well spacing and injection rate are the principal controls on leakage probability. Formation permeability does not show a stable directional influence under relatively high-permeability conditions (100–1000 mD), while reservoir depth and porosity are negatively associated with leakage probability. In addition, variability in relative permeability significantly affects predicted risk, with high-mobility curve families increasing leakage likelihood relative to intermediate conditions. This framework provides an efficient basis for leakage-aware screening and supports risk-informed evaluation during the early design stage of UHS deployment.