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

journal contribution

posted on 2016-08-09, 00:00 authored by F. Ramos-Pallares, S. D. Taylor, M. A. Satyro, R. A. Marriott, H. W. YarrantonA 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:

*c*_{2}, ρ_{s}^{°}, and*c*_{3}. Densities were calculated using the modified Rackett correlation with the Tait-COSTALD compressibility correction. The*c*_{3}parameter was determined from a previously developed correlation. New correlations were developed for the*c*_{2}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*c*_{2}parameter to one viscosity data point halved the error. Tuning both the*c*_{2}and ρ_{s}^{°}parameters using two viscosity data points reduced the AARD to <8% in both cases.