Modelling asphaltene precipitation with solvent injection using cubic-PR solid model (Article, 2019) [WorldCat.org]
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Modelling asphaltene precipitation with solvent injection using cubic-PR solid model
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Modelling asphaltene precipitation with solvent injection using cubic-PR solid model

Author: Aktham E Shoukry Affiliation: Petroleum Department, Faculty of Engineering, Cairo University, Giza, Egypt;; Ahmed H El-Banbi Affiliation: Petroleum Department, Faculty of Engineering, Cairo University, Giza, Egypt;; Helmy Sayyouh Affiliation: Petroleum Department, Faculty of Engineering, Cairo University, Giza, Egypt;
Edition/Format: Article Article
Publication:Petroleum Science and Technology, v37 n8 (20190418): 889-898
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Document Type: Article
All Authors / Contributors: Aktham E Shoukry Affiliation: Petroleum Department, Faculty of Engineering, Cairo University, Giza, Egypt;; Ahmed H El-Banbi Affiliation: Petroleum Department, Faculty of Engineering, Cairo University, Giza, Egypt;; Helmy Sayyouh Affiliation: Petroleum Department, Faculty of Engineering, Cairo University, Giza, Egypt;
ISSN:1091-6466
Unique Identifier: 8523107066
Notes: research-article
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Abstract:

Cubic equation-of-state solid models are commonly-used to predict asphaltene precipitation behavior. Thermodynamic parameters are needed to model this behavior under different pressures and temperatures, and are usually obtained through fitting the model to multi asphaltene onset experiments. This paper introduces an empirical linear relation (tested on six oil samples) relating Asphaltene Onset Pressure (AOP) with injected solvent amount. In addition, waxes and aromatics correlations are utilized to obtain the thermodynamic parameters within the model. The two modifications decrease the number of tuning parameters of the model, as well as reduce the number of lab measurements needed to apply it. The model is tested on two oil samples, with previously published data, to predict AOPs. Using aromatics correlations provided more rational trends for AOP than waxes correlations. Besides, both correlations create a practical domain inside which the laboratory AOP values lie. The new additions enhance the prediction capabilities of the model in the lack of asphaltene experiments.

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