Aggregation thermodynamics of asphaltenes: Prediction of asphaltene precipitation in petroleum fluids with NRTL-SAC

Md Rashedul Islam, Yifan Hao, Chau Chyun Chen

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Based on the aggregation thermodynamics established for asphaltene precipitation in binary solvents (Wang et al., AIChE J., 2016. 62 (4), 1254–64; Islam et al., Fluid Phase Equilibria, 2018. 473, 255–261), this work extends the aggregation thermodynamics for asphaltene precipitation in blending of heavy oils with light hydrocarbons. In lieu of the commonly accepted pseudocomponents approach for petroleum fluid characterization, the petroleum fluids are characterized in terms of model molecules and their compositions (Chen and Que, U.S. Patent No. 9,934,367 B2, April 3, 2018). Solvent power of the petroleum fluids is further quantified with the conceptual segment-based NRTL-SAC activity coefficient model (Chen and Song, Ind. Eng. Chem. Res., 2004, 43 (26), 8354–62). We show the aggregation thermodynamics with the NRTL-SAC model successfully predicts asphaltene precipitation from crude oils upon blending with normal alkanes.

Original languageEnglish
Article number112655
JournalFluid Phase Equilibria
Volume520
DOIs
StatePublished - Oct 1 2020

Keywords

  • Aggregation thermodynamics
  • Asphaltene precipitation
  • Molecule-based characterization
  • NRTL-SAC
  • Petroleum fluids

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