A new experimental and theoretical approach for viscosity Iranian heavy crude oils based on tuning friction theory and friction volume theory parameters

Abstract

In this research work, Friction Theory and Free Volume Theory are applied to live oil characterized based on SARA TEST for viscosity modeling and make a new model in combination with two equation of state (PR and PC-SAFT). Parameters for pseudo-components are obtained by tuning the viscosity at atmospheric pressure and temperatures of 10, 20, and 40 ℃. A new fitting approach is suggested where the number of fitting parameters is 17 and 12 for FT and FVT model, respectively. These parameters are tuned using the Genetic Algorithm and Particle Swarm Optimization and make eight new models. The results show that PC-SAFT provides viscosity predictions for all models with less deviation from experimental viscosity. The FT and FVT models have less error for oils with API > 40 and API < 40, respectively. The PC-SAFT + PSO improves the accuracy in viscosity modeling for both FT and FVT models. PSO can play a significant role even more than PC-SAFT.