A rigorous approach to predict nitrogen-crude oil minimum miscibility pressure of pure and nitrogen mixtures

Nitrogen has been appeared as a competitive gas injection alternative for gas-based enhanced oil recovery (EOR) processes. Minimum miscibility pressure (MMP) is the most important parameter to successfully design N2 flooding, which is traditionally measured through time consuming, expensive and cumbersome experiments. In this communication, genetic programming (GP) and constrained multivariable search methods have been combined to create a simple correlation for accurate determination of the MMP of N2-crude oil, based on the explicit functionality of reservoir temperature as well as thermodynamic properties of crude oil and injection gas. The parameters of the developed correlation include reservoir temperature, average critical temperature of injection gas, volatile and intermediate fractions of reservoir oil and heptane plus-fraction molecular weight of crude oil. A set of experimental data pool from the literature was collected to evaluate and compare the results of the developed correlation with pre-existing correlations through statistical and graphical error analyses. The results of this study illustrate that the proposed correlation is more reliable and accurate than the pre-existing models in a wide range of thermodynamic and process conditions. The proposed correlation predicts the total data set (93 MMP data of pure and N2 mixture streams as well as lean gases) with an average absolute relative error of 10.02%. Finally, by employing the relevancy factor, it was found that the intermediate components of crude oil have the most significant impact on the nitrogen MMP estimation.