Abstract

Viscosity is one of the most important governing parameters of the fluid flow, either in the porous media or in pipelines. So it is important to use an accurate method to calculate the oil viscosity at various operating conditions. In the literature, several empirical correlations have been proposed for predicting crude oil viscosity. However these correlations are not able to predict the oil viscosity adequately for a wide range of conditions. In present work, an extensive experimental data of oil viscosities from different samples of Iranian oil reservoirs was applied to develop an artificial neural network (ANN) model to predict and calculate the oil viscosity. Validity and accuracy of these models has been confirmed by comparing the obtained results of these correlations and with experimental data for Iranian oil samples. It was observed that there is an acceptable agreement between ANN model results with the experimental data.

Key words: Property, artificial neural network, petroleum.