Prediction of Wax Appearance Temperature Using Artificial Intelligent Techniques

The paraffin particles can promote and be involved in the formation of deposits which can lead to plugging of oil production facilities. In this work, an experimental prediction of wax appearance temperature (WAT) has been performed on 59 Algerian crude oil samples using a pour point tester. In addi...

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Bibliographic Details
Published in:Arabian journal for science and engineering (2011) 2020-02, Vol.45 (2), p.1319-1330
Main Authors: Benamara, Chahrazed, Gharbi, Kheira, Nait Amar, Menad, Hamada, Boudjema
Format: Article
Language:English
Subjects:
Algorithms
Correlation coefficients
Crude oil
Engineering
Freezing
Gene expression
Humanities and Social Sciences
Mathematical models
Melting points
Model accuracy
multidisciplinary
Multilayers
Paraffins
Parameters
Regularization
Research Article - Petroleum Engineering
Science
Waxes
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Summary:The paraffin particles can promote and be involved in the formation of deposits which can lead to plugging of oil production facilities. In this work, an experimental prediction of wax appearance temperature (WAT) has been performed on 59 Algerian crude oil samples using a pour point tester. In addition, a modeling investigation was done to create reliable WAT paradigms. To do so, gene expression programming and multilayers perceptron optimized with Levenberg–Marquardt algorithm (MLP-LMA) and Bayesian regularization algorithm were implemented. To generate these models, some parameters, namely density, viscosity, pour point, freezing point and wax content in crude oils, have been used as input parameters. The results reveal that the developed models provide satisfactory results. Furthermore, the comparison between these models in terms of accuracy indicates that MLP-LMA has the best performances with an overall average absolute relative error of 0.23% and a correlation coefficient of 0.9475.
ISSN:2193-567X
1319-8025
2191-4281
DOI:10.1007/s13369-019-04290-y