Application of LSSVM algorithm as a novel tool for prediction of density of bitumen and heavy n-alkane mixture

Abstract

ABSTRACTThe most of oil reservoirs in the world are heavy oil and bitumen reservoirs. Due to high viscosity and density of these types of reservoirs the production has problems so importance of enhanced oil recovery (EOR) processes for them is clear. The injection of solvents such as tetradecane is known as one of methods which improve oil recovery from bitumen reservoirs. In the present investigation, the Least squares support vector machine (LSSVM) algorithm was used to estimate density of Athabasca bitumen and heavy n-alkane mixture in term of temperature, pressure and weight percent of the solvent. The Root mean square error (RMSE), average absolute relative deviation (AARD) and the coefficient of determination (R2) for total dataset are determined 0.033466, 0.0025686 and 1 respectively. The predicted results indicate that the LSSVM algorithm has potential to be a predicting machine for the bitumen-heavy alkane mixture density prediction.