Asphaltene precipitation modeling in dead crude oils using scaling equations and non-scaling models: comparative study

Abstract

This research study aims to conduct a comparative performance analysis of different scaling equations and non-scaling models used for modeling asphaltene precipitation. The experimental data used to carry out this study are taken from the published literature. Five scaling equations which include Rassamadana et al., Rassamdana and Sahimi, Hu and Gou, Ashoori et al., and log–log scaling equations were used and applied in two ways, i.e., on full dataset and partial datasets. Partial datasets are developed by splitting the full dataset in terms of Dilution ratio (R) between oil and precipitant. It was found that all scaling equations predict asphaltene weight percentage with reasonable accuracy (except Ashoori et al. scaling equation for full dataset) and their performance is further enhanced when applied on partial datasets. For the prediction of Critical dilution ratio (Rc) for different precipitants to detect asphaltene precipitation onset point, all scaling equations (except Ashoori et scaling equation when applied on partial datasets) are either unable to predict or produce results with significant error. Finally, results of scaling equations are compared with non-scaling model predictions which include PC-Saft, Flory–Huggins, and solid models. It was found that all scaling equations (except Ashoori et al. scaling equation for full dataset) either yield almost the same or improved results for asphaltene weight percentage when compared to best case (PC-Saft). However, for the prediction of Rc, Ashoori et al. scaling equation predicts more accurate results as compared to other non-scaling models.