Numerical simulation of CO2 migration in the FluidFlower using MRST

Presentation form the MRST Symposium 2023, https://www.tinyurl.com/mrst2023 Lluís Saló-Salgado (1), Malin Haugen (2), Kristoffer Eikehaug (2), Martin Fernø (2), Ruben Juanes (1) 1 - Massachusetts Institute of Technology 2 - University of Bergen Keywords: CO2 storage, two-phase flow, history matching, FluidFlower Modules: ad-core, ad-blackoil, ad-props, deckformat, linearsolvers, upr The FluidFlower is a meter-scale, quasi-2D laboratory rig with a transparent front panel and flexible injection ports. It was developed at the University of Bergen (UiB) with multiple research and outreach goals related to geologic carbon sequestration (https://fluidflower.w.uib.no). One of these goals is the generation of high-quality experimental datasets from direct visualization of subsurface CO2 migration, which can be used to benchmark simulation models. Here, we use the ad-blackoil module to simulate miscible CO2-water migration in two versions of the FluidFlower (porous media dimensions 0.897 x 0.47 x 0.0105 m and 2.86 x 1.33 x 0.019 m). In particular, we evaluate (1) the value of prior knowledge of the system, expressed in terms of local measurements of the quartz sands in the tank, to history-match the simulation model; and (2) the predictability of the matched numerical model, when applied to different injection scenarios and stratigraphic sections. We use timelapse images of the corresponding experiments to assess simulation model concordance. Results show that our model can qualitatively match CO2 plume migration and convective mixing of the experimental truth. Quantitatively, our simulations are accurate during the injection phase, but their concordance decreases with time in specific domain areas. Using local data reduces the time required to history match. Where heterogeneous structures are present, accurate deterministic estimates of CO2 migration are difficult to obtain.