Computational fluid dynamics for ameliorating oil recovery using silicon-based nanofluids and ethanol in oil-wet reservoirs

Impulsive emulsion formation, porous media wettability alteration, and interfacial tension (IFT) reduction are a list of advantages gained from the application of nanoparticles for enhanced oil recovery (EOR). However, low displacement efficiency (DE) coupled with in-effective mixing of the injected nanofluid to redeem the immobile volume of crude oil subsurface present a major challenge to the petroleum industry. The molecular chemistry of ethyl alcohol (ethanol) solvent enables the genesis of strong covalent bonds/mixing with the dense oil. As a result, the fastening converts the aromatic state of the crude oil to a lighter component to ease the flow. In this paper, we numerically investigated the potential for improving dead oil recovery in a heterogeneous rock setting using a blend of ethanol and silicon-based nanofluids to describe the EOR fluid. Herein, silica, silane and silicon carbide nanofluids were studied for their DE with ethanol as the co-solvent. A 2D heterogeneous pore-model was created and discretized to define the computational domain. Computational fluid dynamics code (ANSYS Fluent) facilitated the induction and analysis of interfacial property dynamics within the modelling space. The simulation was performed using the improved delayed detached-eddy simulation method, whereas the continuum surface-force equation with the Euler–Euler mixture multiphase method was used to model the fluid–wall and fluid–fluid adhesions at interfaces. Findings revealed that, silica nanofluid performed optimally compared to its counterpart. Furthermore, approximately 55.34% of the immobile oil was recovered using the optimal blend formulation comprising of equal proportion of silica nanofluid and ethanol. The increase in disjoining pressure and water molecules concentration at the fluid–wall​ contact, and the reduction in interfacial tension due to the evolution of in-situ surface acting agents (surfactants) from the chemical reaction kenetics accounts for this increase. In addition, the blend demonstrated good thermal stability for typical reservoir temperatures of around 400 K due to high intrinsic thermal resilence of silica nanoparticles present in the mixture.