Accurate modeling of thermophysical
properties of solvent/bitumen
mixtures is critical for proper design and implementation of thermal-
and solvent-based bitumen recovery processes. In this study, three
generalized correlations were developed for prediction of solubility,
density, and viscosity of light hydrocarbon/bitumen mixtures. The
generalized correlations were developed using symbolic regression
based on genetic programming and employing a 10-year set of comprehensive
phase behavior experimental studies conducted under the SHARP research
program on solvent-aided thermal recovery of bitumen. The data set
comprised Surmont, JACOS, Mackay River, and Cold Lake bitumen samples
and five light hydrocarbon solvents including methane, ethane, propane,
n
-butane, and
n
-pentane. The developed
correlations are valid for gaseous solvents. Finally, the developed
correlations for solubility, density, and viscosity were validated
against a large data set of experimental measurements collected from
the literature. The validation demonstrates that the developed correlations
are able to accurately predict the available experimental data of
solubility, density, and viscosity reported in the literature.