LAUSR

Abstract Numerical modeling plays an essential role in both identifying and assessing sub-surface reservoirs that might be suitable for future carbon capture and storage projects. Accuracy of flow simulations is tested by benchmarking against historic observations from on-going CO2 injection sites. At the Sleipner project located in the North Sea, a suite of time-lapse seismic reflection surveys enables the three-dimensional distribution of CO2 at the top of the reservoir to be determined as a function of time. Previous attempts have used Darcy flow simulators to model CO2 migration throughout this layer, given the volume of injection with time and the location of the injection point. Due primarily to computational limitations preventing adequate exploration of model parameter space, these simulations usually fail to match the observed distribution of CO2 as a function of space and time. To circumvent these limitations, we develop a vertically-integrated fluid flow simulator that is based upon the theory of topographically controlled, porous gravity currents. This computationally efficient scheme can be used to invert for the spatial distribution of reservoir permeability required to minimize differences between the observed and calculated CO2 distributions. When a uniform reservoir permeability is assumed, inverse modeling is unable to adequately match the migration of CO2 at the top of the reservoir. If, however, the width and permeability of a mapped channel deposit are allowed to independently vary, a satisfactory match between the observed and calculated CO2 distributions is obtained. Finally, the ability of this algorithm to forecast the flow of CO2 at the top of the reservoir is assessed. By dividing the complete set of seismic reflection surveys into training and validation subsets, we find that the spatial pattern of permeability required to match the training subset can successfully predict CO2 migration for the validation subset. This ability suggests that it might be feasible to forecast migration patterns into the future with a degree of confidence. Nevertheless, our analysis highlights the difficulty in estimating reservoir parameters away from the region swept by CO2 without additional observational constraints.