Prediction of Viscosity for Characterized Oils and Their Fractions Using the Expanded Fluid Model

A methodology has been developed to predict the viscosity of crude oils and their fractions from a distillation-based oil characterization. The maltenes were characterized as a set of pseudo-components with properties determined from established generalized correlations. The asphaltene fraction was characterized as a single component and its properties were measured. The viscosities of the pseudo-components, asphaltenes, whole oils, and their fractions were determined with the Expanded Fluid (EF) viscosity model. The inputs for the model are the pressure, the density of the fluid at a given pressure and temperature, the dilute gas viscosity calculated from established generalized correlations, and three fluid-specific parameters: c₂, ρ_s^°, and c₃. Densities were calculated using the modified Rackett correlation with the Tait-COSTALD compressibility correction. The c₃ parameter was determined from a previously developed correlation. New correlations were developed for the c₂ and ρ_s^° parameters of the maltene pseudo-components, as a function of their boiling point and specific gravity. The parameters for the asphaltene fraction were estimated based on the measured viscosity of molten asphaltenes. The EF parameters for the whole oil, or any oil fraction, were determined with mass-based mixing rules and binary interaction parameters, calculated from a previously developed correlation. To develop and test the proposed approach, density and viscosity data were collected for 40 distillation cuts from 6 oils, 7 maltenes, 2 asphaltenes, 3 partially deasphalted oils, and 14 dead oils. Using this model to predict crude oil viscosity under any conditions requires the distillation assay data, the asphaltene mass content, and the specific gravity and molecular weight of the oil. The approach was tested on a development and test dataset of 4 crude oils (this study) and an independent test dataset of 4 oils from the literature with overall average absolute relative deviation (AARD) values of 41% and 43%, respectively. Single multiplier tuning of the c₂ parameter to one viscosity data point halved the error. Tuning both the c₂ and ρ_s^° parameters using two viscosity data points reduced the AARD to <8% in both cases.