Graphene Oxide Nanofluids for Heavy-Oil Recovery: Experimental Evaluation and Field-Scale Numerical Simulation of...

Increasing the recovery factor in oil fields is a critical task for improving reservoir performance and energy sustainability. This study investigates the novel application of graphene oxide (GO) nanoparticles as an enhanced oil recovery (EOR) agent in heavy oilfields, with an integrated multiscale approach combining laboratory experiments and numerical reservoir simulation. The nanofluids were optimized by evaluating the influence of salinity (300-900 ppm), pH (4-8), and GO concentrations (0.03-0.09 wt %) on interfacial tension (IFT) and wettability. Under optimal conditions (900 ppm brine, pH 8, and 0.09 wt % GO), the IFT decreased from 32.5 to 15.8 mN/m, and the contact angle shifted from 140° (oil-wet) to 90° (intermediate). Coreflooding tests confirmed the EOR potential of GO nanofluids, achieving 63.60% oil recovery compared to 56.72% with conventional waterflooding, an incremental gain of 7%. Relative permeability curves and advanced wettability indices (Lak and modified Lak) validated wettability alteration effects. To evaluate the scalability of this technology, the experimental data were incorporated into a numerical simulation using CMG-STARS. First, a history-matched core-scale model was developed to reproduce laboratory results. Then, a conceptual reservoir model was constructed using representative petrophysical properties from Colombian fields. The reservoir-scale simulation showed that nano-GO injection could yield an additional 402,431 barrels of oil over a 20-year period compared to conventional waterflooding, while maintaining a more favorable water cut. These findings highlight the potential of GO nanofluids as a viable and scalable EOR strategy for heavy-oil reservoirs. Future studies will focus on field-scale validation, economic feasibility, and environmental impact.