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

机译:将彭罗宾逊EOS与关联术语集成,以获得更好的最小混溶性压力估算

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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.
机译:最小混溶性压力(MMP)是设计任何具有二氧化碳(CO2)气体注入方法的任何增强的溢油恢复的非常关键的参数。可以使用状态的彭罗宾逊立方方程(PR-EOS)计算MMP。在本文中,将缔章术语掺入等式中,以考虑CO 2化合物中氧和碳原子之间的共价键,以精确MMP估计。在CO 2气体注入过程中,油多组分系统和注射CO2之间的相互作用是在氧和碳原子之间表现出强烈的静电力的地方。这种有吸引力的力量不能被忽视。尽管如此,彭罗宾逊等立方式等级,仅针对诸如排斥和吸引力的物理力量。为此,引入一个关联术语以解释静电力。 Cubic Plus协会EOS(CPA-EOS)与AHMED TAREK的方法同化,考虑到油系统和CO2组合物严格估计MMP。使用PR-EOS和CPA-EOS估计MMP,并与实验值进行比较,具有非常少的绝对误差。因此,结果表明计算和实验MMP之间的密切一致。利用Ahmed Tarek提出的CPA-EOS进行MMP估计,不确定的不确定性是不确定性的。应用三个相关性以估计与实验MMP值略微高的MMP。这种高误差是由于这些相关性之间分子之间表现出的分子间力的无知。值得一提的是,这种提出的方​​法高度欣赏在CO 2和烃多组分混合物中表现出的分子间键,这导致非常可靠和准确地估计MMP。换句话说,将传统EO与关联术语集成,提供了对MMP的精确估计,以确保使用CO2喷射的增强的采油(EOR)设计有效地建模。

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