Abstract

Summary Several laboratory experiments demonstrated that the use of sodium hydroxide could increase the solution pH and reduce the adsorption of anionic surfactants. However, a better understanding of rock-oil-brine interactions and their effect on surfactant adsorption during alkaline-surfactantpolymer (ASP) flooding is needed for realistic and representative estimations of surfactant adsorption levels. Therefore, this study presents a novel approach to capture these interactions and better predict their effect on surfactant adsorption as well as effluent concentrations of surfactant and various aqueous species using the Phreeqc simulator. Currently, surface complexation models (SCMs) consider rock-brine, oil-brine, and surfactant-brine reactions. In this work, four new surface complexation reactions with intrinsic stability constants that honor oil-surfactant interactions have been proposed for the first time and then validated against experimental data reported in the literature. In addition, we analyzed the effect of various parameters on surface adsorption under harsh conditions of high temperature and high salinity using the proposed SCM. The results showed that the developed surfactant-based SCM is capable of estimating surfactant adsorption and its concentration in the effluent during chemical floods. The model was validated against two sets of ASP corefloods from the literature including single-phase and two-phase dynamic surfactant adsorption studies. The findings highlighted that oil-surfactant surface complexation reactions are important and should be captured for a more representative and accurate estimation of surfactant adsorption during chemical flooding. Moreover, the detailed and comprehensive analysis showed that surfactant adsorption increased and its concentration in the effluent decreased with the increase in temperature of the chemical flood. The latter shows that the adsorption process is endothermic and it is more of chemisorption as opposed to physio-adsorption. It was also showed that a decrease in water total salinity decreases the surfactant adsorption on the rock surface, which is related to the increase in the repulsive forces between the rock surface and adsorbed species. Additionally, with the increase in surfactant concentration in the chemical flood, surfactant concentration in the effluent increases, with a slight increase in surfactant adsorption. This slight increase in adsorption can be neglected compared with the injected and produced masses of the surfactant that are proportional. Moreover, the effect of sulfate spiking is significant where the increase in sulfate concentration reduces the surfactant adsorption. Furthermore, it is worth highlighting that the lowest surfactant adsorption levels were achieved through injected water dilution; less than 0.1 mg/g of rock. This is the first study to test a novel formulation of SCM considering the oil-surfactant effect on surfactant adsorption properties. The proposed framework to estimate surfactant adsorption is conducted for high-temperature and high-salinity reservoir conditions. Thus, it could be used in numerical reservoir simulators to estimate oil recovery due to wettability alteration by chemical flooding in carbonates, which will be investigated in our future work. The surfactant adsorption mechanisms during chemical flooding are very case-dependent and hence, the findings of this study cannot be generalized.

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