Presentation from the MRST Symposium 2023, [ Ссылка ]

Elyes Ahmed, Xavier Raynaud, Halvor M. Nilsen, Olav Møyner (SINTEF Digital)

Keywords: hydrogen storage, black-oil simulation, EoS, Pc-saft, PVT-data
Modules: ad-blackoil

Accurately understanding the mechanisms involved in hydrogen storage within underground H2 storage project necessitates detailed modeling of fluid flow and transport. However, employing equation-of-state (EOS) based compositional phase equilibrium methods for such modeling can result in significant computational complexity. In this study, we propose the utilization of a more efficient black-oil simulation approach, specifically tailored to the Brine-Hydrogen case, in order to alleviate the computational demands of flow simulations.

To achieve this, we use a computationally intensive ePC-Saft EOS alongside simpler explicit reduced models based on the Redlich and Kwong EOS and Henry's law. The ePC-Saft Eos and the reduced models are compared and employed to transform hydrogen-brine phase equilibrium compositional data into black-oil pressure-volume-temperature (PVT) data. Through comprehensive numerical simulations, we establish that the reduced models perform comparably to the ePC-Saft EOS in predicting the essential hydrogen-brine transport properties essential for conducting black-oil flow simulations in the context of subsurface hydrogen storage.

Our simulations encompass a range of scenarios, including standard benchmarks and conceptual challenges, such as a cyclic hydrogen injection-production process. This research contributes to advancing our understanding of hydrogen storage dynamics and underscores the feasibility of utilizing simplified models for accurate predictions in complex subsurface storage projects.

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