Polymers are currently used for mobility control and improving sweep efficiency in several field projects. In-situ non- Newtonian polymer rheology is the most crucial factor that affects polymer injectivity. Significant viscosity variations during polymer flood occur in the vicinities of wellbores where velocities are high. Numerical simulations are used to predict the performance and in particular the injectivities of polymer solutions since project economics are sensitive to the injection rates. In this paper, we propose an analytical injectivity model which can be easily implemented in reservoir simulators. As the size of a wellblock increases, velocity smears, and thus polymer injectivity is erroneously calculated. Because of the complex and strong coupling of polymer apparent viscosity and shear rate, empirical correlations are generally employed. In the University of Texas Chemical flooding simulator, an effective radius was introduced to capture the “grid effect”. It is assumed that polymer flux rate in a wellblock is equal to the flux rate using an effective radius. However, this radius is a complicated function of polymer rheology, grid size, and other factors. It should be determined for each well from matching injectivity of coarse-grid with that of fine-grid simulations. This becomes impractical for large-scale field simulations with several hundred wells. Another approach is to use the local grid refinement near wells but this also adds to the computational cost and limits the size of the problem. An attractive alternative to previous approaches is based on the Peaceman’s well model. An analytical model developed for both shear-thinning and shear-thickening polymers is presented. The model and its implementation in the simulator were validated by comparing results of different gridblock sizes and radial numerical simulation. Next, we tested a field case by comparing results of a fine-grid simulation and its up-scaled coarse-grid model. Finally, a pilot-scale polymer flood was simulated. The model successfully captured polymer injectivity in all of these cases with no need to introduce empirical parameters. There are several ongoing polymer injection field tests where the field injectivities differ significantly from the simulation forecasts. We have developed an analytical model to improve predictability of polymer injectivity during the field projects to help with optimum injection strategies.
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