Applying LSSVM algorithm as a novel and accurate method for estimation of interfacial tension of brine and hydrocarbons

Abstract

ABSTRACTOne of the critical parameters in petroleum and chemical engineering is the interfacial tension between brine and hydrocarbon which has major effects on trapping and residual oil in reservoir pore throat so it becomes one of the interesting topics in enhancement of oil recovery in this work Least squares support vector machine (LSSVM) algorithm was applied as a novel predicting machine for prediction of interfacial tension of brine and hydrocarbons in terms of hydrocarbon carbon number, temperature, pressure and ionic strength of brine. A total number of 175 interfacial tensions were collected from literature in the purpose of training and testing of the model. The root mean squared error (RMSE), average absolute relative deviation (AARD) and the coefficient of determination (R2) were calculated overall datasets as 0.23964, 0.27444 and 0.98509 respectively. The results of study showed that predicting LSSVM machine can be applicable for estimation of interfacial tension and EOR processes.