Accurate and efficient multiscale simulation of CO2 storage in Giant Saline Aquifers

Giant saline aquifers (defined here as aquifers that cover areas larger than 10.000 km²) are promising candidates to scale up geological CO₂ storage. However, they present significant simulation challenges due to their vast extent, heterogeneity, and limited subsurface data. This study introduces a reliable multiscale modeling framework which is designed for these fields. The method is also applied to assess CO₂ storage in the Ponta Aguda saline aquifer (Santos Basin, Brazil, 40000 km2 area) to demonstrate its applicability in real field environments.

Our multiscale strategy is formulated such that it delivers reliable quantification of the trapped and mobile mass of CO_2, i.e., the plume migration under complex hysteretic transport physics.  Of particular interest is to preserve reliable quantification of the plume dynamics from near wellbore region (in the order of 10m horizontal resolution) all the way to the far field zones (with 1000m horizontal resolution).

Consistency checks are applied to make sure that the results from different scales are representative of the same realization and storage conditions. Our novel multiscale strategy benefits from the local saturation and global pressure physics. More precisely, the best global pressure representation is provided on the largest scale and therefore is used to provide local boundary conditions (using methods such as Fetkovich model) to the higher resolutions (smaller sub-domains). On the other hand, saturation distribution is first resolved from the smallest sub-domains (highest resolution) and upscaled to the large-scale domains. Through these analyses, it is found that classical upscaling approaches systematically overestimate the trapped amount of CO₂ on coarser models. This motivates the development of advanced reliable multiscale strategies which are efficient but also accurate while the system is being represented on coarser-resolution grids.

We present three different methods and compare them based on their accuracy of trapped amount of CO₂ in the field-scale model. These are namely: Local Grid Refinement (LGR), Effective Values (EV), and Algebraic Dynamic Multilevel (ADM). The results indicate that ADM is the most stable and robust approach among all the approaches considered for real-field applications. Especially, LGR and EV are found limited in their scopes since they depend on a matching procedure (against a reference solution) for their upscaled parameters, before any new simulations. As a result, their tuned parameters cannot be transferred from one model to another. ADM, on the other hand, does not require any upscaling procedure, as the multiscale basis functions allow for consistent mapping across resolutions. The results show the importance of scale-consistent modeling approaches for accurate CO₂ storage assessment and highlight the risks of relying on overly simplified coarse models in the design and optimization of carbon storage projects in giant saline aquifers.