Aggregation thermodynamics for asphaltene precipitation

Date

2017-08

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Abstract

Asphaltene precipitation has been a major concern for petroleum industry due to its adverse effect upon upstream production, midstream transportation, and downstream refining. Pressure induced asphaltene precipitation reduces the well productivity. Blending of incompatible crude oils triggers asphaltene precipitation and subsequent blockage of intricate pipeline of crude supply chain. Asphaltene deposition lowers the efficiency of unit operations and disrupts the refining operations. To determine fluid compatibility and forecast precipitation conditions, the oil and gas industry has shown high interest in predicting the onset of asphaltene precipitation. As a complex phenomenon involving solubility, aggregation, and clustering, asphaltene precipitation has been extensively investigated and correlated with empirical models and equations.

Asphaltene molecules are composed of polycyclic aromatic hydrocarbon (PAH) accompanied by peripheral alkyl chains and hetero atoms. Asphaltene precipitation is driven by self-association of asphaltene molecules to form nanoaggregates and subsequent formation of clusters from nanoaggregates (Mullins, O.C., Energy & Fuels, 2010, 24(4), 2179-2207). Based on this hierarchical structure of asphaltenes, a novel thermodynamic frame for asphaltene precipitation is developed, wherein onset of precipitation involves the transition of asphaltene molecules to nanoaggregates. The thermodynamic formulation accounts for asphaltene aggregation driving force, i.e., change in Gibbs free energy, as a two-step process: 1) molecular asphaltene forming imaginary “nanocrystals,” and 2) “nanocrystals” re-dissolving as colloidal nanoaggregates. The Gibbs free energies are calculated from inherent molecular structure of asphaltene molecules and nanoaggregates. The proposed precipitation model is named as aggregation thermodynamics. Employing UNIFAC model, aggregation thermodynamics yields semi-qualitative predictions of asphaltene precipitations from 13 binary solvents of hydrophobic and polar nature. Furthermore, a computational chemistry-based COSMO-SAC model is applied with aggregation thermodynamics in an attempt to cover precipitation prediction from highly polar and hydrophilic solvents. With the introduction of proper modification to the combinatorial part of COSMO-SAC model and incorporation of conceptual segment based apparent sigma profile of asphaltene molecules, asphaltene precipitations from the desired augmented solvent set are achieved. In the course of the improvement of prediction quality and ease of handling hydrocarbon molecules, NRTL-SAC (Chen, C. C. and Song, Y., I&ECR, 2004, 43(26), 8354-8362) model together with aggregation thermodynamics is applied to calculate asphaltene precipitation from all the 15 binary solvents. The strength of NRTL-SAC allows representation of wide range of molecules in terms of conceptual segments: hydrophobic, polar attractive, polar repulsive, and hydrophilic. The results further show that asphaltene molecules are composed of hydrophobic and polar conceptual segments, as expected from its molecular structure. The ability to predict asphaltene precipitation in the 15 diverse binary solvents with NRTL-SAC paves the way to tackle thermodynamic modeling of asphaltene precipitation in petroleum fluids. The application of NRTL-SAC model in predicting asphaltene precipitation has been extended from binary solvents to multicomponent hydrocarbon mixture, i.e., crude oils. Asphaltene precipitations are calculated from three different heavy oils: Athabasca, Cold Lake, and Peace River. In lieu of the commonly accepted pseudo-components approach, a novel real molecule-based characterization technique (U.S. Application No. 13/740,095) is used to identify make-up molecular compositions of the petroleum fluids. Solvent power of the petroleum fluids is further quantified with the conceptual segment concept of NRTL-SAC model. We show the aggregation thermodynamics model with NRTL-SAC successfully predicts asphaltene precipitation in mixing n-heptane with the crude oils.


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Keywords

Asphaltene Precipitation, Aggregation Thermodynamics, Molecule-based Characterization

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