Prediction of dynamic viscosity of n-alkanes at high pressures using a rigorous approach

Abstract

An adaptive neuro-fuzzy interference system has been developed for estimating the dynamic viscosity of n-alkanes in a wide range of operating conditions. In this study, for the first time, a simple predictive model is proposed for viscosity prediction of n-pentane, n-octane, n-nonane, n-decane and dodecane at various pressures and temperatures, especially at high pressures, without needing to measurement or estimation of density. This tool predicts the dynamic viscosity of the n-alkanes as function of pressure, temperature and n-alkanes' molecular weight. The obtained results of the model were in an excellent agreement with experimental data with an acceptable coefficient of determination of 0.999 for both training and testing datasets. Moreover, the validity of the proposed model for viscosity trends prediction at various conditions was demonstrated and it showed a very good match with actual data. This model is simple to use and can be of massive evaluation for better understanding the behavior of fluids under reservoir conditions.