Low Salinity Polymer (LSP) flooding is a breakthrough hybrid enhanced oil recovery (EOR) technique with excellent synergic capability. Laboratory experiments have demonstrated remarkable enhancement in displacement efficiency, polymer rheology, polymer viscoelasticity, and injectivity during the LSP process. Nonetheless, in order to model LSP flooding, the Polymer-Brine-Rock (PBR) interactions must be accurately captured in a mechanistic predictive model, which can be highly challenging. Thus, this study employs the coupled MATLAB Reservoir Simulation Toolbox (MRST) with the geochemical software IPhreeqc to provide more insight into PBR geochemical interactions occurring during LSP flooding. This coupled MRST-IPhreeqc simulator captures the polymer physics including the Todd-Longstaff mixing model parameter, inaccessible pore volume, permeability reduction, polymer adsorption, and the effects of viscosity and shear rate on polymer viscosity. This is added to the interrelated geochemical reactions. The objective of this study is to conduct a sensitivity analysis examining the effects of changes in water-salinities, rock-forming minerals, and temperatures on polymer viscosity during LSP flooding. In addition, as a de-risking measure, the anticipated viscosity loss was also evaluated for the different salinities, rock types, and temperatures based on the charge ratio (CR) analysis.

The outcomes of this study show that during LSP flooding, the 2-times spiked salinity case (1246 ppm) is more beneficial compared to 2-times diluted salinity case (311.5 ppm) for anticipating lower viscosity losses (i.e., 53% compared to 56% viscosity loss). Concerning the effect of rock-forming minerals on the polymer viscosity, the dolomite mineral demonstrated the highest viscosity loss of 56% followed by the combined dolomite with calcite with 53% viscosity loss, and calcite exhibited the lowest viscosity loss of 50%. Regarding temperature effect on the LSP solution viscosity, the highest viscosity loss of 59 and 58% were observed for 20 and 40℃ temperatures, respectively. On the other hand, the LSP solution viscosity losses for 100, 120 and 150℃ temperatures were 48, 44, and 40%, respectively. Consequently, the 150℃-temperature model is the most beneficial since it results in the lowest viscosity losses of 40%. According to the CR calculation, a CR > 1 indicates a negligible viscosity loss in the polymer solution, which corresponds to a cation concentration of 130 ppm in this work, whereas a CR < 0.3 is very likely to cause a substantial viscosity loss for the polymer solution. Further, for 0.3 < CR < 1, additional analysis of the viscosity loss risk in the LSP solution is required. The study shows the capability of the coupled simulator as a unified instrument, which is logical, accurate, and flexible. The coupled simulator enables the description of essential reactions for mechanistic modeling of LSP flooding precisely. This contribution is one of the few works that enunciates the mechanistic geochemical modeling for low-salinity polymer flooding method. With the aid of the coupled simulator, up-to-date perceptions of the mechanisms governing LSP flooding have been defined. The geochemical capacity of IPhreeqc simulator unifies with the fundamental characteristics that outline the LSP flow and the compositional effects interrelated to it. It is expected that the findings of this work will lay the groundwork for numerous successful designs for LSP field pilots.

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