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).