Integrating Peng Robinson EOS with Association Term for Better Minimum Miscibility Pressure Estimation

Abstract

Abstract Minimum miscibility pressure (MMP) is a very critical parameter to design any enhanced oil recovery affiliated with carbon dioxide (CO2) gas injection methodology. MMP can be computationally estimated using the Peng Robinson Cubic Equation of State (PR-EOS). In this paper, an association term was incorporated into the equation to account for covalent bonds between oxygen and carbon atoms in a CO2 compound for accurate MMP estimation. During the CO2 gas injection process, interactions between the oil multicomponent system and injected CO2 are in place where strong electrostatic force is exhibited between oxygen and carbon atoms. This attractive force cannot be neglected. Nevertheless, a Cubic Equation of State, such as Peng Robinson, accounts only for physical forces such as repulsion and attraction forces only. For this, an association term is introduced to account for electrostatic forces. Cubic plus Association EOS (CPA-EOS) was assimilated with Ahmed Tarek's methodology to estimate MMP rigorously in consideration of oil system and CO2 compositions. MMP was estimated using both PR-EOS and CPA-EOS, and compared against the experimental value with a very minimal absolute error. Therefore, the results showed a close agreement between calculated and experimental MMP. The uncertainty was immensely reduced when utilizing CPA-EOS proposed by Ahmed Tarek for MMP estimation. Three correlations were applied to estimate MMP with a slightly high deviation from the experimental MMP values. This high error is due to the ignorance of the intermolecular forces exhibited between molecules among these correlations. It is worth mentioning that this proposed method is highly appreciating the intermolecular bonding exhibited in CO2 and hydrocarbon multicomponent mixture, which results in a very reliable and accurate estimation of MMP. In other words, integrating conventional EOS with the association term provides accurate estimation of MMP to ensure effective modeling of an enhanced oil recovery (EOR) design with CO2 injection.