EVALUATION OF DIFFERENT POLYMER

This study explores Optimal Injection Strategies for Enhanced Oil Recovery (EOR) by employing computational modeling and optimization methods to maximize oil recovery, reduce operational expenses, and improve environmental sustainability. The research evaluates various injection techniques, such as water injection, CO₂ injection, and chemical flooding, through reservoir simulation models. Critical reservoir properties, including porosity (0.18), permeability (200 mD), and oil saturation (70%), were analyzed to determine their influence on recovery efficiency. Optimization approaches like Genetic Algorithms (GA) and Particle Swarm Optimization (PSO) were applied to refine injection parameters. CO₂ injection emerged as the most effective approach, delivering 85% oil recovery over a 10-year timeframe, while reducing operational costs by 12% compared to waterflooding. Sensitivity analysis revealed that higher permeability enhances CO₂ injection efficiency, although increased injection rates, despite their benefits, led to premature water breakthrough and elevated costs.Furthermore, CO₂ injection supported greenhouse gas sequestration, contributing to environmental sustainability. The findings underscore the importance of computational optimization in EOR strategies. Future research should focus on real-time monitoring and adaptive optimization methods to improve field application and optimize reservoir performance further.