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 TiO nanoparticles. The objective was to develop a validated numerical model to assess th effectiveness of different nanofluids in EOR applications. The research methodolog encompassed various pivotal stages. Initially, a meticulous selection process was employed t identify an appropriate base model for validation, ensuring accuracy and reliability throughou the study. Subsequently, nanofluids containing the aforementioned nanoparticles wer selected, and their properties were characterized to enable accurate simulations. ANSYS Fluent, augmented with User-Defined Functions (UDF), was employed to simulate nanoflui displacement within the reservoir. Python and Minitab were used to support data analysis an validation. Mesh independence and saturation tests confirmed model stability. Key parameter such as velocity and interfacial tension were notably influential in affecting recover performance. The RSM model predicted a theoretical maximum oil recovery of 105% for SiO nanofluid under ideal conditions within the selected parameter range. Validation throug saturation testing yielded an average recovery of 78.92%, closely matching the 75% reported i experimental studies. This demonstrates the model’s strong potential as a predictive tool fo optimizing nanofluid applications in real-world EOR operations.