CO2-Oil Minimum Miscibility Pressure Predicting Model

Eissa Mohamed El-M. Shokir, King Saud University, College of Engineering, Petroleum Department, P.O. Box 800, Riyadh 11421, Saudi Arabia, riyadh Saudi Arabia, phone: +9661-4676882, fax: +966-1-4674422, shokir@ksu.edu.sa

The CO2-oil minimum miscibility pressure (MMP) is an important parameter for screening and selecting reservoirs for CO2 injection projects. For the highest recovery, a candidate reservoir must be capable of withstanding an average reservoir pressure greater than the CO2-MMP. Knowledge of the CO2-oil MMP is also important when selecting a model to predict or simulate reservoir performance as a result of CO2 injection. This paper, presents a new alternating conditional expectation “ACE” - based model for estimating CO2-oil MMP. The ACE algorithm, estimate the optimal transformations that maximizes the correlation between the transformed dependent variable “CO2-oil MMP” and the sum of the transformed independent variables, that represent reservoir temperature, and different components of oil composition. Predicted values of the CO2-oil MMP from the developed ACE-based model were compared with the experimental and calculated values from the most common correlations, which reported in the literature for CO2-oil MMP prediction. The results displayed that the ACE-based model is superior to other commonly used correlations. Regarding to other correlations, the ACE-based model yielded the highest correlation coefficient (0.9878), the lowest average relative error (0.7428 %), and the lowest standard deviation of error (1.2265).

CO2 Sequestration – Concepts and Future Plans (EMD/DEG)
2006 AAPG International Conference and Exhibition, (November 5-8, 2006) Technical Program