Insights into the fractional flow of low salinity water flooding in the light of solute dispersion and effective salinity interactions

Abstract

The objective of Low Salinity Water Flooding (LSWF) is to improve oil recovery. While a significant number of laboratory tests have been carried out to investigate the impact of LSWF, field scale modelling is often reported in the form of sector models with relatively coarse cells. This paper assesses the impact of simulating flow at very fine scales and informs on the properties that should be captured at the coarse scale to avoid numerical errors. We have found that the weighting function that is used to control changes to fluid mobility combines with numerical and physical diffusion to induce a retardation/acceleration effect. This is a physical effect rather than part of a chemical reaction.In this study, numerous simulations of LSWF have been carried out at the reservoir scale to investigate flow behaviour for various salt concentration (salinity) weighting functions and dispersion coefficients. We have examined the effective salinity range over which the weighting function is applied as well as considering various shapes. Dispersion was varied to represent physical and numerical effects. These have been compared to analytical solutions from fractional flow theory.We also observed that the fractional flow of the oil bank will be same for both the secondary and tertiary flooding. We point out the relative importance of various parts of the relative permeability curves. An important finding of this work is that by spreading the salinity front through dispersion and setting a low value at which salinity impacts mobility, we saw the injected low salinity front advance more slowly while the high salinity front of formation water moves more quickly. This is an effective retardation effect. We related this to an effect equivalent to adsorption in the fractional flow theory and could measure it in a similar way. We were also able to develop a prediction of the effect using the analytical solution to the advection-diffusion equation.The outcome is that we can estimate a corrective term for the flow behaviour in situations where the dispersion is quite strong, particularly in numerical simulations. We consider that this enable corrections to be made for numerical dispersion effects in field scale models.