Direct perturbation of the Peng–Robinson attraction and covolume parameters for reservoir fluid characterization

Abstract

Numerical simulation of enhanced oil recovery processes, such as gas and steam floods, requires that the reservoir fluid of interest is reliably modeled by use of an equation of state (EOS). Reservoir fluid characterization using an EOS can be challenging because of the uncertainties associated with non-identifiable heavy fractions, which are characterized as a few pseudo components.This paper presents a new method for reservoir fluid characterization that directly perturbs the attraction and covolume parameters of pseudo components from the n-alkanes’ values (direct perturbation from n-alkanes, or direct PnA). The direct PnA method systematically adjusts the attraction and covolume parameters of all pseudo components within a given reservoir fluid through a few adjustable parameters. As in our prior research, the ψ(=a/b2) parameter is used to ensure the proper interrelationship between the attraction (a) and covolume (b) parameters. A new approach to adjustment of the ψ parameters is developed with a linear relationship of ψ with molecular weight. The Peng–Robinson (PR) EOS is used throughout the research.The direct PnA method is applied to 84 different reservoir fluids, such as gas condensates, volatile oils, and heavy oils. Characterization of each fluid uses the saturation pressure and liquid density data at different pressures at the reservoir temperature. Other phase behavior data available are used to test the predictive capability of the fluid models developed using the PR EOS with the direct PnA method. Results show that the reservoir fluids tested are reliably characterized by the systematic control over phase behavior predictions in the direct PnA method. Unlike prior characterization methods, the direct PnA method does not require estimation of apparent critical parameters of non-identifiable heavy fractions.