Tracking CO₂ plume migration during geologic sequestration using a probabilistic history matching approach

Abstract

Tracking the migration of the CO₂ plume is essential in order to better manage the operation of geologic sequestration of CO₂. However, the large cost of most monitoring technologies, such as time-lapse seismic, limits their application. We investigated the application of a probabilistic history matching methodology using routine measurements of injection data, which are affected by the presence of large-scale heterogeneities, as an inexpensive alternative to track the migration of CO₂ plume in an aquifer. The approach is demonstrated first through a synthetic example in which the ability to detect the presence of flow barriers was tested. In a second example, we applied our method to the In Salah field, one of the largest geological sequestration projects in the world, where the main direction of high permeability features was inferred. The accuracy and reproducibility of the results show that our approach for assisted history matching is an economic and viable option for plume monitoring during geologic CO₂ sequestration.