Heavy oils are sometimes diluted with petroleum solvents for pipeline transportation, and it is necessary to ensure that the selected solvent does not precipitate asphaltenes from the oil. The modified regular solution (MRS) model can predict asphaltene precipitation from heavy oil diluted with pure n-alkanes but has not yet been applied to petroleum solvents. To do so, asphaltene precipitation data were measured for bitumen diluted with petroleum solvents including gas condensates, diesels, kerosene, and naphtha and their blends with n-heptane. The petroleum solvents were characterized into single carbon number (SCN) fractions on the basis of gas chromatography assays. New correlations were proposed for the molecular weight, density, and solubility parameters of the SCN fractions. The MRS model with the characterization and correlations matched asphaltene precipitation data with an average absolute deviation of 0.7 wt % for petroleum solvents with relatively low contents of pure aromatic and cyclic components (<3 wt %), that is, condensates, diesels, and kerosenes. The model failed to match asphaltene precipitation data from the naphtha which contained a significant fraction of pure aromatic and cyclic components (>10 wt %). Hence, the proposed model is currently limited to solvents similar to condensates, diesels, and kerosenes.
Models are required to predict the onset and precipitation of asphaltenes from mixtures of heavy oil and solvents for a variety of heavy oil applications. The regular solution approach is well suited for this objective but has not yet been tested on solvent mixtures. To do so, the onset and amount of asphaltene precipitation were measured and modeled for mixtures of heavy oil with solvent blends made up from n-alkanes, cyclohexane, and toluene at temperatures of 21 and 180 °C and pressures of 0.1 and 10 MPa. Temperature dependent binary interaction parameters (BIP) between the cyclohexane/asphaltene and toluene/asphaltene pseudo-component pairs were proposed to match the data. All other BIP were set to zero. The model with BIP determined from asphaltene precipitation in heavy oil and binary solvents predicted asphaltene precipitation from heavy oil and ternary solvent blends, generally to within the experimental error.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.