Journal
JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING
Volume 135, Issue -, Pages 201-205Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.petrol.2015.09.002
Keywords
Asphaltene precipitation; Titration data; Support vector regression (SVR); Scaling equation; Imperialist competitive algorithm (ICA)
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Precipitation of asphaltene largely affects the production rate of crude oil owing to the clogging of transportation pipeline as well as formation damage. Therefore, it is imperative to search for a robust method for the modeling of asphaltene precipitation. This paper aims to propose a new mathematical model for computing asphaltene precipitation as a function of titration data including dilution ratio, temperature, and molecular weight of solvent. This model is constructed based on integrating the support vector regression with the imperialist competitive algorithm. Optimization increases the performance of support vector regression by virtue of determining the optimal values of their parameters. The constructed model is applied to experimental data and its performance is compared with scaling equation which is traditionally employed for modeling of asphaltene precipitation. The results of this study show that the integration of imperialist competitive algorithm and support vector regression has a better performance than the scaling equation. This paper offers that the support vector regression optimized by virtue of the imperialist competitive algorithm is a reliable model for modeling asphaltene precipitation. (C) 2015 Elsevier B.V. All rights reserved.
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