Prediction of the interfacial tension between hydrocarbons and carbon dioxide

In the recent years due to increasing demand for energy and declination of reservoir production, an impressive notice on enhancement of oil recovery has been found. The gas injection especially carbon dioxide injection due to low cost and friendly environmentally of this approach the special attention to CO2 injection increased. The miscibility is known as key factor which effects on enhancement of recovery. The miscibility is controlled by interfacial tension of hydrocarbons and carbon dioxide so the importance of investigation of the interfacial tension becomes highlighted. in this investigation by using radial basis function (RBF) artificial neural network (ANN) as a novel approach the interfacial tension of hydrocarbons and carbon dioxide in terms of pressure, temperature, liquid and gas densities and molecular weight of alkane. The graphical and statistical results illustrated the fact that RBF- ANN algorithm is applicable for estimation of interfacial tension between hydrocarbons and carbon dioxide with great accuracy.