Speaker
Description
Carbon capture and storage (CCS) in geological formations is a promising approach to mitigating CO₂ emissions, with mineralization providing a stable, long-term solution. In this process, CO₂ dissolves in brine and reacts with minerals in the rock matrix, leading to the precipitation of stable carbonate phases. However, understanding the evolution of crystallization within the rock matrix is crucial, as it affects porosity, permeability, and mechanical integrity. Accurately modeling this process requires a detailed representation of fluid-mineral interactions at the pore scale while capturing the large-scale effects on storage efficiency and rock stability.
To address this challenge, we developed a high-fidelity numerical model using semi-Lagrangian methods [2,3] to simulate crystal growth within the porous matrix [1]. The methodology has been developed and validated for dissolution process in previsous work [5,4]. The semi-Lagrangian approach effectively handles advective transport in complex flow fields while tracking the evolution of mineral precipitation. This method allows us to resolve moving phase boundaries and capture intricate interactions between fluid flow, reactive transport, and crystal nucleation. By leveraging direct numerical simulations (DNS), we can obtain detailed insights into the dynamic evolution of mineral structures within geological formations, offering a predictive tool for assessing long-term storage performance.
Building on this framework, we have now coupled our model with the linear elasticity of the rock matrix to evaluate the mechanical stability of the storage reservoir. We compute the Von Mises stress criterion to assess whether crystallization-induced stresses exceed the rock’s failure threshold, which is critical for maintaining the integrity of the formation. This approach enables us to predict potential fracturing or mechanical weakening caused by mineral growth and ensures that the CCS process remains safe and effective. By integrating fluid-mineral interactions with rock mechanics, our model provides a comprehensive tool for optimizing CO₂ mineral storage strategies in deep geological formations.
| References | [1] Perez S., Etancelin J.-M., Poncet P., A semi-Lagrangian method for the direct numerical simulation of crystallization and precipitation at the pore scale, Frontiers in Earth Science, 13, 1493305 (2025). [2] Perez S., Moonen P., Poncet P., On the Deviation of Computed Permeability Induced by Unresolved Morphological Features of the Pore Space, Transport in Porous Media, 141, 151-184 (2022). [3] Hume L., Poncet P., A velocity-vorticity method for highly viscous 3D flows with application to digital rock physics, Journal of Computational Physics, 425, 109910 (2021). [4] Molins S., Soulaine C., Prasianakis N. I., Abbasi A., Poncet P., et al., Simulation of mineral dissolution at the pore scale with evolving fluid-solid interfaces: review of approaches and benchmark problem set, Computational Geosciences, 25, 1285-1318 (2021). [5] Etancelin J.-M., Moonen P., Poncet P., Improvement of remeshed Lagrangian methods for the simulation of dissolution processes at pore-scale, Advances in Water Resources, 146, 103780 (2020). |
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| Country | France |
| Student Awards | I would like to submit this presentation into the Earth Energy Science (EES) and Capillarity Student Poster Awards. |
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