Abstract
Over the last decades, great attention has been devoted to the CO2injection to enhance oil recovery. Recycling CO2into oil reservoirs provides an excellent option to store this gas in subsurface formations and also improves oil recovery. Successful design of a miscible CO2flooding project mostly depends on accurate determination of Minimum Miscibility Pressure (MMP). In the present study, using multi-gene genetic programming together with a comprehensive sensitivity analysis, a model was developed that provides an accurate estimation of MMP for a wide range of reservoir temperatures and oil compositions. This model utilizes temperature, molecular weight of C5+compounds, and ratio of volatile to intermediate oil fractions as input parameters. Accuracy of correlation was tested versus experimental data and those of other correlations. Results show that the new model assumes a lower error than other published correlations. Based on the results of the present study, it can be asserted that the proposed model is able to predict CO2-oil MMP with a high accuracy when the experimental data are not available.
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