4.7 Article

Asphaltene flocculation parameter in Brazilian crude oils and synthetic polar and nonpolar mixtures: Experimental and modeling

Journal

FUEL
Volume 199, Issue -, Pages 606-615

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.fuel.2017.03.024

Keywords

Solubility parameter; Oil compatibility; Modeling; Asphaltene

Funding

  1. Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior (CAPES)
  2. Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq)
  3. Petrobras

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The experimental method used to predict solubility parameter of Brazilian crude oils takes into account the critical solubility parameter assumption. In this work, experimental ratifications to this assumption were found for both crude oils and nonpolar asphaltene mixtures. This is an important matter since the oil compatibility is estimated from this assumption. Models based on the Regular Solution and Flory-Huggins theories were used to estimate the solubility data of least-soluble asphaltenes. Thereby, it was observed that the employment of Kikic modification of the Flory-Huggins combinatorial term plus the replacement of the traditional Hildebrand solubility parameter by the Hansen solubility parameter in the energetic term greatly improved the performance of these models and led to the best correlation, even for polar and associative solvents. In addition, the impact of asphaltene blending on Brazilian oil stability was evaluated from two asphaltene fractions sequentially extracted. The results point out that the asphaltene subfractionation should be taken into account in the solubility modeling. From these results, a critical solubility parameter for Brazilian oils (16.8 MPa1/2) is proposed to be used as a universal input parameter in the experimental methodology of predicting solubility parameter of crude oils based on asphaltene stability. The predicted solubility parameter was fully compatible with the calculations from three empirical models that also correlate this property with other experimental data of crude oils. (C) 2017 Elsevier Ltd. All rights reserved.

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