Ali S. Al-Khaqani

This study aims to evaluate and optimize the performance of miscible CO2 injection in the heterogeneous Mishrif carbonate reservoir, with the objective of enhancing oil recovery and improving reservoir production performance. A compositional reservoir model was developed using CMG-GEM to accurately represent fluid behavior and phase transitions. Fluid characterization and PVT data matching were performed using WinProp with the Soave–Redlich–Kwong (SRK) equation of state. History matching of production and pressure data was also carried out to validate the reliability of the reservoir model. A natural depletion scenario was adopted as a base case for comparison, after which miscible CO2 injection was implemented, and an optimization study was conducted using CMOST based on Latin Hypercube Sampling (LHS) and a proxy model to identify optimal operating conditions. The results of the natural depletion case showed a continuous decline in reservoir pressure, with a final recovery factor of only 2.74%. In contrast, CO2 injection improved reservoir performance and increased the recovery factor to 4.22% in the optimized case, with delayed gas breakthrough and a reduced gas-oil ratio compared to the base case. The study confirms that miscible CO2 injection is an effective enhanced oil recovery technique for the Mishrif reservoir, offering a significant increase in production while improving reservoir management and maintaining pressure support.

Accurate estimation of permeability is essential for reliable reservoir characterization and simulation. However, core data are often limited due to their high cost and operational constraints, leading to significant uncertainty in uncored intervals. This study aims to reduce the dependence on core data for permeability estimation by integrating electrofacies derived from well logs and flow zone indicator analysis in the Mishrif Formation, Nasiriyah oil field. Electrofacies were generated using dynamic clustering based on the log data from 13 wells. This led to the identification of five electrofacies units that represent intervals with similar log responses, formed by merging 75 electrofacies, where flow zone indicators analysis identified hydraulic flow units based on the porosity and permeability data from cored wells. The resulting model was applied to uncored wells to predict the permeability along the reservoir. The predicted permeability showed high coincidence with measured core data, with a coefficient of determination (R2=0.85168), demonstrating that the integrated electrofacies-Flow Zone Indicators approach provides a reliable and cost-effective method for characterizing heterogeneous carbonate reservoirs and supporting improved reservoir modelling and field development planning.