In this work, a modified form of the SRK EOS is used to predict asphaltene precipitation using SARA fractions as pseudo-components. Asphaltenes were divided into several fractions using the Schultz-Zimm molar mass distribution function and were treated as polymer-like compounds where high molar mass asphaltenes are aggregates of monodisperse asphaltene monomers. Using group contribution methods, the SRK EOS was changed to a polymeric form where the average number of asphaltene monomers per aggregate, r, characterized asphaltene aggregates. The critical properties of aggregates were directly related through the value of r to the monomer critical properties and hence only monomer properties were required as inputs. The saturate, aromatic and resin fractions were treated as pseudo-components in the same manner as the standard SRK EOS. Liquid-liquid equilibrium was assumed between an oil phase and an asphaltene-rich phase. The model was tuned using a single data set and was then applied to other data sets with no additional fitting of parameters. The model predicted measured amounts of asphaltene precipitation in solvent mixtures, and mixtures of solvent and crude oil to within 30% over the full range of precipitation and to within 10% at fractional yields above 50%.
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