An Adaptive Hybrid Vertical Equilibrium/Full-Dimensional Model for Compositional Multiphase Flow
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WaterResourcesResearch_2022_Be ...
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Department of Hydrology and Atmospheric Sciences, University of ArizonaIssue Date
2022Keywords
compositional flowhybrid model
multiphase flow
multiphysics model
porous medium
vertical equilibrium
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John Wiley and Sons IncCitation
Becker, B., Guo, B., Buntic, I., Flemisch, B., & Helmig, R. (2022). An Adaptive Hybrid Vertical Equilibrium/Full-Dimensional Model for Compositional Multiphase Flow. Water Resources Research.Journal
Water Resources ResearchRights
Copyright © 2022 The Authors. This is an open access article under the terms of the Creative Commons Attribution License.Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.Abstract
Efficient compositional models are required to simulate underground gas storage in porous formations where, for example, gas quality (such as purity) and loss of gas due to dissolution are of interest. We first extend the concept of vertical equilibrium (VE) to compositional flow, and derive a compositional VE model by vertical integration. Second, we present a hybrid model that couples the efficient compositional VE model to a compositional full-dimensional model. Subdomains, where the compositional VE model is valid, are identified during simulation based on a VE criterion that compares the vertical profiles of relative permeability at equilibrium to the ones simulated by the full-dimensional model. We demonstrate the applicability of the hybrid model by simulating hydrogen storage in a radially symmetric, heterogeneous porous aquifer. The hybrid model shows excellent adaptivity over space and time for different permeability values in the heterogeneous region, and compares well to the full-dimensional model while being computationally efficient, resulting in a runtime of roughly one-third of the full-dimensional model. Based on the results, we assume that for larger simulation scales, the efficiency of this new model will increase even more. © 2022 The Authors.Note
Open access articleISSN
0043-1397Version
Final published versionae974a485f413a2113503eed53cd6c53
10.1029/2021WR030990
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Except where otherwise noted, this item's license is described as Copyright © 2022 The Authors. This is an open access article under the terms of the Creative Commons Attribution License.