Multi-Objective Optimization of Underground Hydrogen Storage Operation in a Depleted Gas Reservoir Using Smart Proxy Models

Document Type : Research Paper

Authors

Department of Chemical and Petroleum Engineering, Sharif University of Technology, Tehran, Iran

Abstract

Global warming and climate change, driven by rising greenhouse gas emissions, are among the most critical challenges of our time. To address this, various solutions have been developed, including net-zero carbon strategies such as carbon capture and storage, as well as energy transition efforts to reduce or replace fossil fuels with renewable sources. However, the intermittent nature of clean energy production necessitates large-scale storage systems to ensure a stable energy supply. Hydrogen, as an energy carrier, presents a promising solution, with underground hydrogen storage (UHS) offering the potential for sustainable energy supply during peak demand. Due to hydrogen’s unique characteristics and dynamic behavior in porous media, complex compositional modeling and time-intensive physics-based simulations are required to determine optimal storage scenarios. This paper first simulates UHS in a depleted gas reservoir, then based on simulation results a proxy model is developed and utilized for multi-objective optimization. Given the presence of remaining gas and the complex phase behavior of reservoir fluids, hydrogen recovery factor and purity were selected as decision variables for optimization. The design of experiment methods, such as Latin hypercube sampling, generated the necessary training and testing subsets for an artificial neural network model. The feed-forward model, incorporating 10 neurons and a sigmoid activation function as a smart proxy, achieved the highest accuracy—0.97 for training and 0.94 for testing—in predicting hydrogen purity and recovery factor, effectively guiding multi-objective optimization of decision variables via a genetic algorithm. Furthermore, Pareto front analysis of optimal solutions revealed nitrogen gas as the dominant component in the injected cushion gas composition, consisting of 75% nitrogen, 20% carbon dioxide, and 5% methane. The results also identified production from top perforations and hydrogen injection in lower perforations as optimal conditions. The approach outlined in this study can support UHS field applications and facilitate rapid decision-making in large-scale energy storage operations.

Keywords

Main Subjects

References

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Journal of Petroleum Research
Volume 35, 1404-1 - Serial Number 140
Special Issue on the Development of the Hydrogen TechnologyChain
May and June 2025
Pages 37-54

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