A Predictive Thermodynamic Framework for Modeling Density and Phase Behavior of Petroleum Fluids

In a recent work, we proposed correlations relating the perturbed-chain statistical associating fluid theory (PC-SAFT) parameters for nonpolar substances to simple measurements of molecular weight and density at ambient conditions (Abutaqiya et al., I&EC Research 2020, 59­(2), 930–941). These parameter relations were shown to accurately reproduce volumetric and phase equilibrium properties for systems containing defined components. In this work, the newly developed PC-SAFT parameter correlations are used to model the thermodynamic properties of crude oils and petroleum fuels. The proposed modeling framework relies on treating the heavy fraction as a single pseudocomponent whose PC-SAFT parameters are calculated from the measured molecular weight and density at 20 °C and 1 atm. This approach does not require the saturate–aromatic–resin–asphaltene analysis or the hydrogen/carbon ratio of the fluid. In fact, the modeling approach is predictive and does not require any tuning parameters. The proposed framework is applied to 5 petroleum fuels, 3 dead oils, and 32 live oils from the literature. Density predictions for the studied hydrocarbon mixtures show an average absolute percent deviation (AAPD) of 0.8% (1230 data points), and the bubble pressure predictions for live oils and their gas blends show an AAPD of 5.02% (113 data points).