Secondary polymer flooding can significantly improve oil recovery over that obtained by waterflooding. This is achieved principally by improving the water-oil mobility ratio and thus reducing channelling. There are, however, several polymer-specific mechanisms (such as adsorption, mixing, permeability reduction, non-Newtonian flows) that make it more difficult to model numerically compared with waterflooding. Upscaling reservoir properties for reservoir simulation is one of the most important steps in the workflow for building robust dynamic simulation models. It is necessary to reduce computing time and resources when it is not possible to run multiple high resolution models (e.g. as in evaluating the impact of geological uncertainty). This is normally achieved by modifying the inputs to reservoir simulation to represent the influence of sub-grid block heterogeneities on large scale flow and also to compensate for numerical dispersion. At the time of writing there are no accepted methods for upscaling polymer flooding. This paper focuses on the upscaling of relative permeability and adsorption to better represent sub-grid block heterogeneity and compensate for numerical dispersion. This is achieved in a three step process. First we upscale absolute permeability to represent the effects of geological heterogeneity on pressure. Next we use traditional dynamic pseudo relative permeabilities to represent the influence of these heterogeneities on flood front conformance and to compensate for numerical dispersion. Finally we upscale the adsorption isotherm to better represent the average polymer concentration distribution in the reservoir. The methods are demonstrated on a series of 2D heterogeneous models with aggregation ratios between fine and coarse grid simulations of 25:1.


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