Engineering Visual Presentation E05 The transition to a low-carbon energy system demands large-scale, dependable energy storage solutions, with hydrogen emerging as a key enabler due to its versatility, dispatchability, and high energy density. Underground hydrogen storage (UHS) in depleted hydrocarbon reservoirs (DHRs) offers strong potential, leveraging proven geological containment, existing infrastructure, and substantial storage capacity. This study evaluates the feasibility and performance of UHS through dynamic numerical simulations in Eclipse 300, focusing on hydrogen migration, diffusion, cushion-gas interactions, and long-term seal integrity. A systematic review was undertaken to identify critical knowledge gaps in UHS, including diffusion modelling, sorption behaviour, microbial interactions, and caprock performance. Simulated scenarios were designed to assess hydrogen behaviour under varying pressure and temperature conditions, the role of nitrogen as a cushion gas, and the influence of geological heterogeneity on plume evolution and recovery. Results show that hydrogen mobility and storage efficiency are highly sensitive to reservoir architecture, with heterogeneity exerting a dominant control on plume geometry and trapping. Nitrogen proved to be an effective, low-cost cushion gas, stabilising pressure, improving withdrawal performance, and limiting contamination. Elevated pressures enhanced containment by suppressing buoyancy effects, while higher temperatures increased plume ascent and mixing. Long-term simulations demonstrated that competent caprock can retain hydrogen over extended timescales, provided diffusion remains moderate. Overall, the study confirms that DHRs represent viable candidates for UHS when supported by appropriate operational design and thorough characterisation. These findings contribute essential insights into hydrogen migration, containment, and optimisation strategies, supporting hydrogen’s integration into future decarbonised energy systems. To access the Visual Presentation click on 'Supplementary data' below. To read the full paper click here
Callum Martin (2026) studied this question.