Control of Numerical Dispersion in Simulations of Augmented Waterflooding

Abstract

Abstract Augmented waterflooding is where a component is co-injected for the purpose of modifying the fractional flow curve: examples include polymer flooding, surfactant injection, low salinity waterflooding and carbonated water injection (including applications related to carbon dioxide storage). The numerical simulation of these processes is a challenge for several reasons: the appropriate physical behavior needs to be incorporated consistently into empirical models of the fractional flow, while the solutions should minimize numerical dispersion, allowing the correct and accurate tracking of compositional variations. Traditional numerical simulations of these processes give excessive front smearing, requiring many thousands of grid blocks in one dimension to resolve the fronts adequately, rendering the predictions from three-dimensional simulations dubious at best. These erroneous predictions are not caused by phase dispersion (the improper prediction of water velocity), as in black-oil simulation, where the effect is less significant, but occurs because of the coupling of compositional dispersion with fractional flow. Small errors in composition alter the fractional flow, causing the development of incorrect wave speeds. The same effect is also seen in compositional simulation of gas injection. We propose a simple method, based on the assumption of segregated flow within a grid block, that substantially reduces numerical dispersion. After comparing numerical and analytical results in one dimension, we implement the method into a three-dimensional streamline-based simulator of polymer flooding that also incorporates a physically-based model of the fluid rheology. We demonstrate that traditional simulation methods can vastly over-estimate recovery, potentially leading to poor injection design and management decisions. We demonstrate the utility of our approach by suggesting optimal strategies for the design of polymer injection based on our improved simulation technique. We also discuss extensions of the method to fully compositional displacements involving many chemical components.