On prediction of asphaltene precipitation in different operational conditions utilization of LSSVM algorithm |
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Authors: | Milad Sedaghat Karim Rouhibakhsh |
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Affiliation: | 1. Department of Petroleum Engineering, Marvdasht branch, Islamic Azad University, Marvdasht, Fars, Iran;2. Department of Petroleum Engineering, School of chemical, petroleum and Gas Eng., Shiraz University, Shiraz, Fars, Iran |
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Abstract: | Asphaltene which is known as one of the fractions of oil, can cause the important problems during production of crude oil in reservoir, tubing and surface facilities so these problems can influence the production cost and time. In order to predicting and solving asphaltene problems, a powerful Least squares support vector machine (LSSVM) algorithm were developed for asphaltene precipitation estimation as function of dilution ratio, temperature, precipitant carbon number, asphaltene content and API of oil. A total number of 428 measured data were utilized to train and test of LSSVM algorithm. The average absolute relative deviation (AARD), the coefficient of determination (R2) and root mean square error (RMSE) were determined as 7.7569, 0.98552 and 0.26312 respectively. Based on these statistical parameters and graphical analysis it can be concluded that the predicting algorithm has enough reliability and accuracy in prediction of asphaltene precipitation. |
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Keywords: | asphaltene precipitation LSSVM predicting algorithm operational conditions |
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