Numerical Analysis of Enhanced Oil Recovery using Nanofluids

This study presents a comprehensive investigation into enhanced oil recovery (EOR) techniques utilizing nanofluids, specifically focusing on CuO, SiO2, Al2O3, and TiO2 nanoparticles. The objective was to develop a validated numerical model to assess the effectiveness of different nanofluids in EOR applications. The research methodology encompassed various pivotal stages. Initially, a meticulous selection process was employed to identify an appropriate base model for validation, ensuring accuracy and reliability throughout the study. Subsequently, nanofluids containing the aforementioned nanoparticles were selected, and their properties were characterized to enable accurate simulations. ANSYS Fluent, augmented with User-Defined Functions (UDF), was employed to simulate nanofluid displacement within the reservoir. Python and Minitab were used to support data analysis and validation. Mesh independence and saturation tests confirmed model stability. Key parameters such as velocity and interfacial tension were notably influential in affecting recovery performance. The RSM model predicted a theoretical maximum oil recovery of 105% for SiO₂ nanofluid under ideal conditions within the selected parameter range. Validation through saturation testing yielded an average recovery of 78.92%, closely matching the 75% reported in experimental studies. This demonstrates the model’s strong potential as a predictive tool for optimizing nanofluid applications in real-world EOR operations.