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The accuracy and robustness of numerical models of geologic CO$_2$sequestration are almost never quantified with respect to direct observationsthat provide a ground truth. Here, we conduct CO$_2$ injection experiments inmeter-scale, quasi-2D tanks with porous media representing stratigraphicsections of the subsurface, and combine them with numerical simulations ofthose experiments. We evaluate (1) the value of prior knowledge of the system,expressed in terms of ex-situ measurements of the tank sands' multiphase flowproperties (local data), to obtain an accurate simulation; and (2) thepredictive capability of the matched numerical models, when applied todifferent settings. We match three different simulation models-each with accessto an increasing level of local data-to a CO$_2$ injection experiment in tank 1(89.7$\times$47$\times$1.05 cm). Matching is based on a quantitative comparisonof CO$_2$ migration at different times from timelapse image analysis. Next, wesimulate a different injection scenario in tank 1, and, finally, a differentinjection scenario in tank 2 (2.86$\times$1.3$\times$0.019 m), which representsan altogether different stratigraphic section. Our models can qualitativelymatch the CO$_2$ plume migration and convective mixing of the experimentaltruth. Quantitatively, simulations are accurate during the injection phase buttheir performance decreases with time. Using local data reduces the timerequired to history match. The predictive capability of matched models,however, is found to be similar. The sand-water-CO$_{2(\mathrm{g})}$ system isvery sensitive to effective permeability and capillary pressure changes; whereheterogeneous structures are present, accurate deterministic estimates ofCO$_2$ migration are unlikely.

Direct comparison of numerical simulations and experiments of CO$_2$  injection and migration in geologic media: Value of local data and  predictability