Economic optimization of Carbon Capture, Utilization, and Storage (CCUS) is critical to ensuring project viability amidst energy market volatility and operational uncertainties. This study develops and applies the Iterative Latin Hypercube Sampling (ILHS) method to determine the optimal CO₂ injection rate based on Net Present Value (NPV) as the objective criterion. Simulations are conducted using the PUNQ-S3 reservoir model by integrating a FORTRAN-based optimization program with the commercial CMG-GEM simulator. Three case studies varying in oil price ($70 and $30 per barrel) and discount rate (0% and 10%) are analyzed to assess NPV sensitivity. Results show that ILHS achieves rapid convergence with relatively low computational demands and yields different optimal injection rates depending on economic parameters. This study highlights the importance of incorporating dynamic economic factors in CO₂ injection strategy design and demonstrates ILHS as a robust and efficient method for field-scale CCUS optimization.
Copyrights © 2025