Passive destabilization of enhanced oil recovery nanofluid emulsions using wettability patterning of microfluidic platforms

With the continuous increase in energy demand, enhanced oil recovery (EOR) methods employ advanced approaches to maximize the extraction of limited crude oil reserves, leading to significant economic benefits. Recently, nanoparticle flooding has been considered as a promising technology among EOR methods. Although nanofluids can improve the efficiency of oil recovery by stabilizing the oil–water emulsions during the extraction stage, they have an adverse effect on the subsequent oil–water separation process. This study investigates the use of wettability-tuned microchannels as a novel approach for the passive destabilization of EOR effluent nanofluid emulsions, highlighting the importance of efficient separation techniques in the oil and gas industry. Using graphene oxide (GO)-patterned microfluidic devices, we examined the effects of various process variables, including GO pattern width, droplet velocity, GO concentration, silica nanofluid (SNF) concentration, and the number of GO coatings. Our findings reveal a droplet coalescence mechanism characterized by trapping, fusion, and detachment of droplets. Notably, while the width of GO patterns did not significantly affect the number of fused droplets, droplet velocity and GO concentration were critical in determining detached droplet size. Additionally, an increase in GO coating layers was found to destabilize droplets at higher critical adhesion velocities, which can enhance the efficiency of the separation process. This work provides a proper understanding of the stability and dynamics of SNF emulsions in the presence of GO and offers theoretical guidance for the further development of highly efficient microscale-based destabilizers that can be utilized in EOR processes to enhance separation efficiency.