A modified cell-to-cell simulation model to predict oil-gas minimum miscibility pressure

Abstract

AbstractCalculating the minimum miscibility pressure (MMP) between crude oil and carbon dioxide (CO2) is critical for optimizing injection parameters, designing schemes, and predicting production capacity in CO2 injection projects for enhancing oil recovery. However, an accurate approach for obtaining this parameter is not yet established. In order to tackle this issue, a novel approach is suggested, based on the original cell-to-cell model, to determine the MMP and the 97% oil recovery rate as the standard. Using the volume-transformed Peng-Robinson equation of state enhances the precision of fluid volume estimation, as it mainly relies on predicting fluid volume within each cell. Furthermore, to ensure a precise estimation of the ultimate oil recovery rate, it is imperative to employ a total cell count of 500 in all simulations to avoid the problem of numerical dispersion. Finally, a second-order polynomial equation more accurately predicts the infinite-cell oil recovery factor. The accuracy of the modified model is verified by comparing MMP values from five oil and gas systems in the literature. The computational results of the modified multiple-mixing-cell (MMC) approach exhibit a higher level of concordance with the MMPs in the literature. The average relative error is less than 3.96%. The improved MMC algorithm can quickly determine the miscibility mechanism and visually represent the dynamic miscibility process involving multiple oil-gas contacts in a slim tube. This study provides a theoretical and practical basis for addressing the critical scientific issues of CO2-safe storage technology.