Applying fractional flow theory to evaluate CO2 storage capacity of an aquifer

In this paper, an application of fractional flow theory is used to evaluate CO2 storage capacity of an aquifer because of two trapping mechanisms: capillary snap-off and gas dissolution. The capillary snapoff and CO2 dissolution into the resident aqueous phase are two major trapping mechanisms of the CO2 sequestration in geological formations over intermediate time-scale. In practice, numerical simulations are used to assess the CO2 storage capacity of a geological formation and evaluate various trapping mechanisms; however, the simulations are complex and timeconsuming and they require detailed inputs. Whereas, the presented method requires limited inputs and provides fast results in agreement with the simulation that makes it suitable tool to compare and screen the CO2 storage potential of various formations. The notion of optimal solvent-water-slug size is adopted as the ultimate CO2 storage capacity for a given permeable medium. A combined graphical solution of multiple geochemical front propagation and fractional flow theory is used to determine the CO2 storage capacity of one-dimensional (1D) models; i.e. the largest slug of injected CO2 that is trapped because of the capillary trapping and the CO2 dissolution. Injecting larger amount of CO2 than the optimum slug size causes the CO2 breakthrough (over capacity) while smaller slugs leaves the aquifer unfilled (under-capacity). We use numerical simulation to validate the accuracy of the predicted optimal slug size. Next, we incorporate gravity override as the governing two-dimensional (2D) phenomenon affecting the storage capacity. The impact of 2D effects is applied via a multiplying factor that reduces the ultimate storage capacity and depends on the reservoir aspect ratio and buoyancy number. In practice, the proposed method provides an efficient screening method to assess the CO2 storage capacity of aquifers and significantly reduces the simulation costs while providing an interesting insight. (C) 2014 Elsevier B.V. All rights reserved.