Applying SVM scheme for modeling of natural gas dew point

ABSTRACT

Hydrate formation and water accumulation during transmission process can be prevented by effective dehydration of gas streams. This study investigates the application of support vector machine to estimate natural gas dew point temperature using contactor temperature and TEG purity as independent variables. A data set comprised of 173 data points is extracted from the literature. The proposed model is considered a great help for engineers to have precise dew point temperature predictive tool in wide ranges of concerning variables. Results obtained from the proposed model show R-squared and mean square error of 0.992 and 5.556, respectively. Accordingly, the remarkable agreement between predicted and experimental values is observed.

KEYWORDS:

• Support vector machine
• transmission process
• temperature
• modeling
• learning approach