Multiscale simulation frameworks are essential to quantify the CO 2 trapping and migration in large-scale saline aquifers, which entail highly-resolved fine-scale heterogeneous properties. However, classical upscaling approaches which aim to define effective properties on larger grid sizes can lead to significant and systematic overestimation of the solubility and residual trapping mechanisms. Reliable assessment of these two trapping mechanisms is crucial to ensure the integrity of the storage process and properly mitigate the leakage risks. Therefore, it is essential to develop advanced simulation technologies that are both accurate and efficient (i.e., scalable) for simulation of complex CO 2 plume dynamics within large-scale heterogeneous reservoir models. To overcome this challenge, in this work three advanced strategies are developed and investigated: Effective Values (EV) for parameters, Local Grid Refinement (LGR) and Algebraic Dynamic Multilevel (ADM). The numerical investigations specially include a set of consistent models in the Ponta Aguda saline aquifer, with a total area of 40,000 km 2 , located offshore the Brazilian coast. The results indicate that the ADM is a promising method, delivering stable and robust results in a representative section of the field. This encourages further extensions of this method for real-field deployment. Specially, LGR and EV are found to be limited in their scopes for field simulations, since they depend on a matching pre-procedure (against a reference solution) for their upscaled parameters before any new simulations can be run. In addition, 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. • Multiscale methods enable CO2 storage simulation in giant aquifers. • Novel multiscale framework applied to Santos Basin saline aquifer. • Four simplification strategies compared across scales. • Equivalent Values and Algebraic Dynamic Multilevel best represent trapping mechanisms.
Erdtmann et al. (Fri,) studied this question.