The effect of subsurface factors on the performance of nanofluid-assisted enhanced oil recovery: Modeling and sensitivity analysis

Abstract

Successful implementation of nanofluid-assisted enhanced oil recovery (EOR) operation mainly depends on proper determination of the main factors that control both transport and retention of nano-sized particles in porous media. In this study, a new transport scheme using the kinetic Langmuir model was first developed and validated by some experimental data from the literature. This model was then used to investigate the effect of reservoir rock type, clay content, grain size, brine type, and reservoir temperature on distribution of nanoparticles on the rock surface and in the injected fluid in relation to EOR methods. Moreover, a two-phase approach was derived to simulate the effect of these parameters on both wettability alteration and mobility control. Results confirmed that the deposition tendency of silica nanoparticles on limestone is higher than that on sandstone. By increasing clay content, both surface area and deposition sites increases and consequently more nanoparticles were found to retain. In the case of polyethylene glycol (PEG) stabilized silica nanoparticles, the amount of oil recovery increased by increasing the salinity of brine. Increasing the salinity of brine resulted in considerable deposition of silica nanoparticles on the rock surface and made them more water wet. These phenomena eventually increased the final recovery factor from 62% to 79%. Since the temperature simultaneously affects the deposition and detachment kinetics of nanoparticles and the reservoir fluid properties, its effect on oil recovery in nanoassisted-EOR technique cannot be generalized.