Determination of relative permeability curve under combined effect of polymer and surfactant

Relative permeability of surfactant-polymer (SP) flooding is determined by an inversion method based on numerical simulation and unsteady-state coreflooding experiment. Compared with the common methods, this method is more time-saving and simpler than steady-state method, and considers more physicochemical properties (adsorption and diffusion) of SP than unsteady-state method based on Buckley-Leverett theory. It is also more applicable to reservoir engineering than pore-scale simulation. After the reliability is confirmed, the superiority of the method is strongly proved by studying the influence of adsorption and diffusion of SP on relative permeability. Comparing relative permeability with and without effect of adsorption and diffusion of SP, the findings show adsorption and diffusion of SP significantly reduce the average inversion error of relative permeability curve from 11.9 to 3.7 for oil and from 10.7 to 1.8 for water. On this basis, the variations of SP flooding relative permeability under the effect of polymer and surfactant are discussed in turn. In the existing researches, the quantitative characterization of variation of SP-flooding relative permeability curves is limited by curve crossing and endpoint saturation changes. In this work, normalized relative permeability is introduced to eliminate the adverse effect caused by curve crossing and endpoint saturation changes. The findings show that although the rise of aqueous-phase viscosity reduces water relative permeability, it has little effect on normalized water relative permeability. Normalized oil and water relative permeability increase in logistic functions with the decrease of IFT in semi-logarithmic plot. Water relative permeability at residual oil endpoint decreases linearly as aqueous-phase viscosity increases, and increases exponentially as IFT decreases in semi-logarithmic plot. Ultimately, the functional models based on normalized relative permeability and cubic B-spline are built through multiple regression, which can calculate relative permeability of SP flooding in term of IFT and aqueous-phase viscosity.