Evaluates A PVT Correlation to Estimate Dead Oil Viscosity for Libyan Crudes Using 104 Samples from Different Reservoirs

Abstract

Viscosity is defined as the resistance of the fluid to flow. It plays a very significant role in most oil and gas engineering applications. The measured viscosity for any crude oil at surface condition is called by the dead oil viscosity, where the dead oil viscosity is a function in any correlation to calculate the viscosity of the crude oil. Thus, the dead oil viscosity is important in most applications related to the petroleum engineering. Accordingly, a new mathematical and artificial neural network (ANN) dead oil viscosity correlations were developed for Libyan crudes and compared with renowned dead oil viscosity correlations using 104 samples from different reservoirs. The evaluation in this study has been done by statistical and graphical error analysis. The results shown that the ANN model has proven to be a useful tool for predicting where the ANN model has given the best result with low error AAD was 14.40509 % and R^{^2} was 95.91%. The ANN model and mathematical model gave the lowest error when they compared with different empirical correlations.