An improved correlation to determine minimum miscibility pressure of CO₂–oil system

An accurate and reliable estimation of minimum miscibility pressure (MMP) of CO₂–oil system is a critical task for the design and implementation of CO₂ miscible displacement process. In this study, an improved CO₂–oil MMP correlation was developed to predict the MMP values for both pure and impure CO₂ injection cases based on ten influential factors, i.e. reservoir temperature (T_R), molecular weight of C₇₊ oil components (MW), mole fraction of volatile oil components (x_vol), mole fraction of C₂C₄ oil components (x), mole fraction of C₅C₆ oil components (x), and the gas stream mole fractions of CO₂ (y), H₂S (y_S), C₁ (y), hydrocarbons (y_HC) and N₂ (y). The accuracy of the improved correlation was evaluated against experimental data reported in literature concurrently with those estimated by several renowned correlations. It was found that the improved correlation provided higher prediction accuracy and consistency with literature experimental data than other literature correlations. In addition, the predictive capability of the improved correlation was further validated by predicting an experimentally measured CO₂–oil MMP data, and it showed an accurate result with the absolute deviation of 4.15%. Besides, the differential analysis of the improved correlation was analyzed to estimate the impact of parameters uncertainty in the original MMP data on the calculated results. Also, sensitivity analysis was performed to analyze the influence of each parameter on MMP qualitatively and quantitatively. The results revealed that the increase ofx, x and y_S lead to the decrease of MMP, while the increase of T_R, MW, x_vol, y, y, y_HC and y tend to increase the MMP. Overall, the relevance of each parameter with MMP follows the order of T_R > x > MW > x_vol > y_S > y_HC > y > y > y > x.