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Subsurface geological formations can be utilized to safely store large-scale (TWh) renewable energy in the form of green gases such as hydrogen. Successful implementation of this technology involves estimating feasible storage sites, including rigorous mechanical safety analyses. Geological formations are often highly heterogeneous and entail complex nonlinear inelastic rock deformation physics when utilized for cyclic energy storage. In this work, we present a novel scalable computational framework to analyse the impact of nonlinear deformation of porous reservoirs under cyclic loading. The proposed methodology includes three different time-dependent nonlinear constitutive models to appropriately describe the behavior of sandstone, shale rock and salt rock. These constitutive models are studied and benchmarked against both numerical and experimental results in the literature. An implicit time-integration scheme is developed to preserve the stability of the simulation. In order to ensure its scalability, the numerical strategy adopts a multiscale finite element formulation, in which coarse scale systems with locally-computed basis functions are constructed and solved. Further, the effect of heterogeneity on the results and estimation of deformation is analyzed. Lastly, the Bergermeer test case—an active Dutch natural gas storage field—is studied to investigate the influence of inelastic deformation on the uplift caused by cyclic injection and production of gas. The present study shows acceptable subsidence predictions in this field-scale test, once the properties of the finite element representative elementary volumes are tuned with the experimental data.

The efficient solution of the systems of equations arising from coupled consolidation problems is a matter of concern worldwide. The fixed-stress splitting scheme is an effective approach for solving these equations either in a sequential manner or as a preconditioner for a fully coupled approach. Recent studies show that it is possible to improve the convergence rate of the fixed-stress approach by choosing a proper tuning parameter. In this work, we present an optimization algorithm that dynamically searches for the optimal tuning parameter for each time step of the simulation, hence the denomination of real-time optimization.The numerical examples show that the optimal tuning parameter indeed can change during the simulation, which highlights the importance of the dynamic search provided by the optimization algorithm. In some situations, the optimized fixed-stress algorithm proposed in this work is able to reduce the total number of iterations by up to 70% compared to the non-optimized version.

Successful transition to renewable energy supply depends on the development of cost-effective large-scale energy storage technologies. Renewable energy can be converted to (or produced directly in the form of) green gases, such as hydrogen. Subsurface formations offer feasible solutions to store largescale compressed hydrogen. These reservoirs act as seasonal storage or buffer to guarantee a reliable supply of green energy in the network. The vital ingredients that need to be considered for safe and efficient underground hydrogen storage include reliable estimations of the in-situ state of the stress, especially to avoid failure, induced seismicity and surface subsidence (or uplift). Geological formations are often highly heterogeneous over their large (km) length scales, and entail complex nonlinear rock deformation physics, especially under cyclic loading. We develop a multiscale simulation strategy to address these challenges and allow for efficient, yet accurate, simulation of nonlinear elastoplastic deformation of rocks under cyclic loading. A coarse-scale system is constructed for the given finescale detailed nonlinear deformation model. The multiscale method is developed algebraically to allow for convenient uncertainty quantifications and sensitivity analyses.

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