RESUMO
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.
RESUMO
Polymer flooding is one of the most used chemical enhanced oil recovery (CEOR) technologies worldwide. Because of its commercial success at the field scale, there has been an increasing interest to expand its applicability to more unfavorable mobility ratio conditions, such as more viscous oil. Therefore, an important requirement of success is to find a set of design parameters that balance material requirements and petroleum recovery benefits in a cost-effective manner. Then, prediction of oil recovery turns out to handle more detailed information and time-consuming field reservoir simulation. Thus, for an effective enhanced oil recovery project management, a quick and feasible tool is needed to identify projects for polymer flooding applications, without giving up key physical and chemical phenomena related to the recovery process and avoiding activities or projects that have no hope of achieving adequate profitability. A detailed one-dimensional mathematical model for multiphase compositional polymer flooding is presented. The mathematical formulation is based on fractional flow theory, and as a function of fluid saturation and chemical compositions, it considers phenomena such as rheology behavior (shear thinning and shear thickening), salinity variations, permeability reduction, and polymer adsorption. Moreover, by setting proper boundary and initial conditions, the formulation can model different polymer injection strategies such as slug or continuous injection. A numerical model based on finite-difference formulation with a fully implicit scheme was derived to solve the system of nonlinear equations. The validation of the numerical algorithm is verified through analytical solutions, coreflood laboratory experiments, and a CMG-STARS numerical model for waterflooding and polymer flooding. In this work, key aspects to be considered for optimum strategies that would help increase polymer flooding effectiveness are also investigated. For that purpose, the simulation tool developed is used to analyze the effects of polymer and salinity concentrations, the dependence of apparent aqueous viscosity on the shear rate, permeability reduction, reversible-irreversible polymer adsorption, polymer injection strategies on petroleum recovery, and the flow dynamics along porous media. The practical tool and analysis help connect math with physics, facilitating the upscaling from laboratory observations to field application with a better-fitted numerical simulation model, that contributes to determine favorable scenarios, and thus, it could assist engineers to understand how key parameters affect oil recovery without performing time-consuming CEOR simulations.
