Surfactant flooding is an enhanced oil recovery process used to mobilize the residual oil by lowering the interfacial tension (IFT) between oil and water. When surfactants are mixed with brine and oil, oil in water, water in oil microemulsions could be formed with region of ultra low IFT. The ability to predict the number of phases formed, their relative amount, and compositions at a particular reservoir brine concentration is crucial for successful CEOR planning.
Equations of state (EOS) such as the Peng-Robinson (PR) and Soave-Redlich-Kwong (SRK) are usually used to predict the phase equilibrium. They require critical properties and accentric factors of the components. However, since oil and surfactants are not pure substances, they are treated as pseudo-components for which the pseudo critical properties must be estimated. Also, PR and SRK EOS are originally developed for non-ionic, non-polar and non-associating hydrocarbons. These pose some limitations in their application to surfactant/Brine/Oil mixture.
This study presents a new computational model to estimate surfactant/brine/oil ternary phase behaviour using PR EOS. In this study we have adopted group contribution model (GCM) using information from the molecular structure of the pseudo components for the estimation of their critical properties. A numerical solution is developed for solving the system of nonlinear equations governing the phase equilibrium by means of Newton-Raphson iterative procedure.
Phase behavior experiments were conducted at temperature of 50°C using Alfa Olefin Sulfonate (AOS) surfactant, decane and brine. Brine concentrations were varied at each temperature and phase relative amount and compositions were determined. The laboratory results were compared with the results predicted by the model. The study shows the level of reliability of our new predictive model. The model developed can be used in compositional simulation of surfactant flooding operations and should prove to be an invaluable tool in planning and evaluation of surfactant flooding processes.