Simulation based dimensionless waterflood performance curves for predicting recovery

Abstract

Predicting waterflood recovery with simulation based dimensionless performance curves has advantages over the more traditional approaches in certain applications. This work discusses the advantages of the type curve approach in moderately mature fields where high resolution history matches are required. The method also has advantages when uncertainty analyses is important. The dimensionless type curve methodology can be applied to many different fields. A case study of a large, complex field is presented to show how the curves are created and how they can be applied. In this field, a study of the geology and stratigraphy indicated that reservoir continuity, permeability variance, and effects of faulting were the most important drivers of recovery efficiency. Simulations were performed on 45 datasets to describe waterflood performance over the range of variation. A spreadsheet program was created to predict recovery of any description, based on interpolations of the simulation results. The dimensionless curves can be used to predict full-field performance, as the basis of an integrated evaluation tool and/or for comparing actual performance to predicted performance. Using correlations to predict recoveries allows for ease of sensitivity analyses, and ease of application by casual users in an organization.