Optimization of miscible CO2 injection in the Nasiriyah oil field using a history-matched compositional reservoir model

Authors

DOI:

https://doi.org/10.31699/IJCPE.2026.3.8

Keywords:

Proxy Model; Miscible CO2; Latin Hypercube Sampling; Optimization; CMOST; Enhanced oil recovery

Abstract

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.

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Published

2026-09-30

How to Cite

Al-Khaqani, A. S., & Al-Obaidi, D. A. (2026). Optimization of miscible CO2 injection in the Nasiriyah oil field using a history-matched compositional reservoir model. Iraqi Journal of Chemical and Petroleum Engineering, 27(3), 97-106. https://doi.org/10.31699/IJCPE.2026.3.8