Heavy oil characterization method for PC-SAFT

Abstract

Oil characterization is a crucial step in modeling heavy oil systems. Since heavy oil consists of thousands of components, for modeling purpose it is required to lump hydrocarbons into pseudocomponents. New generation equation of state (EoS), Perturbed-Chain Statistical Associating Fluid Theory (PC-SAFT), has shown promising results for modeling heavy oil systems. However, single carbon number type characterization approach has been lacking for PC-SAFT until now. The characterization method presented in this paper is based on sorting the pseudocomponents according to their boiling points. Further, each boiling point cut is split into saturate, aromatic and polyaromatic fractions. Asphaltenes are treated as a single pseudocomponent. For calculations, the PC-SAFT parameters were obtained for each pseudocomponent. The characterization procedure was validated by predicting densities for two heavy oils, three heavy oil cuts and propane+Athabasca bitumen (AB) and CO2+propane+AB systems and comparing the results with measured data (109 data points). The relative average deviation was at its highest 2.1 % for density. In addition, saturation pressures were predicted for propane+AB and CO2+propane+AB systems (57 data points). The saturation pressure predictions were as good as predicted earlier in the literature with Peng–Robinson EoS (in this work: the relative average deviations were 7.2 % and 2.0 % for propane+AB and CO2+propane+AB systems). The calculations demonstrated that densities and gas solubilities for heavy oil systems can be accurately predicted with PC-SAFT without any adjustable PC-SAFT parameters if the distillation curve is available.