Asphaltene precipitation modeling with PR and PC-SAFT equations of state based on normal alkanes titration data in a Multisolid approach

Reservoir fluid Asphaltenes show different precipitation behavior during titration with different normal paraffins, reminding a polydisperse nature. In this respect, the precipitated Asphaltene is increased with decreasing the solvent carbon number. Titration experimental data can be used to improve the precipitation model flexibility. In this study, an improved thermodynamic model is developed to calculate the Asphaltene precipitation conditions. The main focus of this work is on the maximum use of experimental data to increase the accuracy of Asphaltene precipitation calculation using perturbed chain statistical associating fluid theory (PC-SAFT) and Peng-Robinson (PR) equations of state (EOS) (including volume shift) in a Multisolid framework. To do so, at first, PR and PC-SAFT Asphaltene parameters are regressed to bubble point pressure, precipitation onset pressure and the amount of precipitated Asphaltene using the published experimental data on titration of dead oil using normal pentane as a solvent in atmospheric conditions. Afterwards, to follow the polydisperse behavior, the Asphaltene component is divided into three pseudo-components based on the precipitating solvents and the calculations are repeated to adjust the parameters of the EOSs of the new Asphaltene parts. Finally, the results for monodisperse and polydisperse Asphaltene are compared with experimental date of two types of Mexican crude oil samples from reliable published literature and the modeling results with statistical associating fluid theory for the potentials of variable attractive range (SAFT-VR) used by Buenrostro-Gonzalez et al. [1]. The maximum and minimum deviations from the experimental data to calculate the weight percent of the precipitated Asphaltene after dilution are obtained by PR EOS for monodisperse and by PC-SAFT EOS for polydisperse Asphaltene. For one of the oil samples the maximum and minimum mean percent deviation by PR and PC-SAFT EOSs are 9.1079 and 1.7279, respectively, while for the other oil sample they are 3.6674 and 1.0845, respectively.