Comparative Analysis of Surfactant-Polymer Flooding Dynamics Across Diverse Reservoir Simulators

Abstract

Abstract Our study investigates recent advancements in modeling surfactant-polymer processes using both commercial and open-source simulators, focusing specifically on UTCHEM, CMG-STARS, and the coupled MRST-IPhreeqc due to their widespread global use. The main objective is to examine the latest polymer and surfactant models integrated into these simulation tools. Additionally, we performed a comprehensive history-matching analysis using experimental data to thoroughly assess and compare their effectiveness in modeling chemical EOR processes. The polymer models integrated into the simulators offer a wide range of functionalities, accurately representing polymer viscosities across different salinity levels and concentrations. They effectively capture non-Newtonian behavior and consider phenomena such as adsorption and permeability reduction. Notably, UTCHEM and the coupled MRST-IPhreeqc also excel at managing polymer viscoelasticity and its impact on oil recovery. In contrast, in terms of surfactant modeling, UTCHEM demonstrates more advantageous capabilities, particularly in correlating microemulsion viscosity, interfacial tension, and surfactant phase behavior. On the other hand, CMG-STARS and the coupled MRST-IPhreeqc have limitations in accurately predicting surfactant behavior in porous media. Core-scale simulations of polymer flooding underscored the significance of properly determining inaccessible pore volume and polymer adsorption to capture representative polymer propagation in porous media. It was affirmed that polymer adsorption hinders polymer propagation, whereas inaccessible pore volume facilitates it. Another crucial factor influencing polymer flooding effectiveness was polymer viscosity, which was modeled differently across simulators. Specifically, it was found that polymer rheology impacts pressure predictions, and employing shear-thinning models for viscoelastic polymer flooding in simulators might lead to an underestimation of observed pressure drops during experiments. Furthermore, the coupled MRST-IPhreeqc demonstrated superior performance in modeling fluid front propagation during polymer flooding simulations. This was attributed to the more accurate modeling of polymer adsorption in the coupled simulator, which incorporated geochemical reactions. While UTCHEM and CMG-STARS can also model geochemistry, accessing and utilizing the geochemical packages in those simulators was not feasible in our study. This highlighted the significance of incorporating geochemical considerations into simulators to achieve better alignment with experimental data. Furthermore, surfactant flood simulations using UTCHEM and CMG-STARS closely matched the experimental data. To align CMG-STARS with UTCHEM's IFT correlations, corresponding tables were prepared. While UTCHEM comprehensively modeled microemulsion viscosity, CMG-STARS employed a non-linear mixing model for this purpose. Sensitivity analysis on SP slug size revealed that increasing the slug size generally boost oil recoveries, albeit with a diminishing impact considering financial and technical complexities.