Compositional Streamline-Based Modeling of Polymer Flooding Including Rheology, Retention, and Salinity Variation

[Image: see text] The chemical enhanced oil recovery (CEOR) technology that is most used worldwide is polymer flooding due to its proven commercial success at field scale, maturity, and versatility to combine with other technologies. So, there has been an increasing interest in expanding its applicability to more unfavorable mobility ratio conditions and adverse environments (such as high-temperature, high-salinity carbonate reservoirs, pH-sensitive polymers, and formations with active clays). Therefore, a requirement for successful field application is to find the design parameters of the process that balance material requirements and oil recovery benefits in a cost-effective manner, which is usually done through reservoir modeling. Polymer flooding predictive tools normally require detailed information and are based on time-consuming field reservoir simulations. Thus, for effective project management, a quick and sound tool is needed to screen for polymer flooding applications without giving up key physical–chemical phenomena that govern the oil recovery. In this research, we developed a two-dimensional polymer flooding model based on the streamlines approach. This is an alternative to having a multidimensional practical tool thoroughly representing the physical and chemical behavior of polymer flooding by considering key phenomena such as rheology behavior (shear thinning and shear thickening), salinity variations, permeability reduction, and polymer adsorption. Previously published streamline multidimensional models for polymer flooding lack the integrated modeling of the above-mentioned key phenomena. Additionally, the models to represent rheology and retention phenomena in the proposed tool consider a more complete description than the present streamline-based simulators. For the construction of streamlines, we considered a black oil formulation to estimate the pressure and saturation 2D distribution by applying the implicit in pressure and explicit in saturation method, coupled with an explicit formulation for the 2D composition computation. For saturation-composition along the streamlines, the 1D practical tool incorporated represents the polymer flooding key phenomena. The numerical algorithm used by the streamline-based tool is supported by laboratory experiments for waterflooding in homogenous porous media, analytical results for waterflooding in heterogeneous media, polymer flooding field scale simulation cases, and a CMG-STARS model built as a reference for waterflooding in both media (homogenous and heterogeneous) and for polymer flooding. The practical tool developed contributes to simplifying the upscaling from laboratory observations to field applications with better fitted numerical simulation models and to determining favorable scenarios; thus, it could assist in understanding how key parameters affect oil recovery without performing time-consuming CEOR simulations.