Adsorption kinetics of natural surfactants on carbonate minerals in enhanced oil recovery processes

One of the most promising methods for improving oil recovery from carbonate reservoirs is surfactant flooding in which the trapped oil can be mobilized by alteration in the wettability of rock surfaces and also reduction in the interfacial tension between oil and water. Adsorption of surfactants on carbonate minerals plays a key role in designing this process and may make it less effective for enhancing oil recovery. Natural surfactants have been proposed by many researchers since they have lower cost and also less detrimental environmental effects compared to the industrial surfactants. Well-established predictive models for predicting the adsorption of natural surfactants have some issues which need to be addressed. Therefore, developing an accurate, rapid and simple model is crucial. In this study, a least square support vector machine (LSSVM) optimized with coupled simulated annealing (CSA) algorithm is developed for accurate prediction of natural surfactants kinetic adsorption on carbonate minerals. Obtained results by this model were in a very good agreement with experimental results. Additionally, the results showed that the proposed model has the highest accuracy and performance in comparison to the previous kinetic models. Afterward, the effect of natural surfactants adsorption on the amount of oil recovery and also the quality of the produced oil was investigated via core flooding tests for showing the importance of determining the adsorption of surfactants before any surfactant flooding. Results demonstrated that lower surfactants adsorption yields higher oil recovery factor and oil with higher viscosity.