Viscosity Modeling of Heavy Crude Oil Using the Friction Theory Combined with PC-SAFT

Abstract

Small changes in temperature or pressure can lead to crude oil phase separation and multiple orders of magnitude change in viscosity. The one-parameter friction theory framework using the SARA-based method with the perturbed-chain statistical association fluid theory (PC-SAFT) EoS has proven to have high accuracy in viscosity predictions of light oil. However, it failed for heavy crude oil. In this work, the above model is modified in two aspects to enhance the accuracy of heavy crude oil viscosity prediction: to include the effect of asphaltene polydispersity and to include the temperature effect to the friction theory parameter. The average absolute relative deviation of the four studied heavy oils is reduced by 16.81, 24.26, 97.31, and 87.75% compared to the one-parameter f-theory SARA-based PC-SAFT model. The f-theory parameter K c is modified as a function of temperature fitted to the viscosity at normal temperature and pressure. Following the simplicity of the expansion of the method, it is recommended to use this methodology when dealing with heavy crude oils such as those with viscosity more than 20,000 cP at 25 °C.