Revisiting the PC-SAFT characterization procedure for an improved asphaltene precipitation prediction

Asphaltene precipitation and subsequent deposition are responsible for one of the major flow assurance concerns in the oil industry. Recent experimental evidence found on the mechanisms of asphaltene precipitation and aggregation is in conceptual agreement with the modeling approach for phase stability based on the PC-SAFT equation of state (EoS). It has been already proven that the PC-SAFT EoS can provide very accurate predictions of the phase stability of asphaltenes, bubble point of the oil, density of gas and liquid phases, Gas-Oil-Ratio, composition of liberated gas and even asphaltene compositional grading that can induce in extreme cases the formation of tar-mats. In this work, we present an enhanced PC-SAFT characterization methodology that is applied to various reservoir fluids from three different fields in the Middle East region. The new method simplifies the process of parameter estimation by reducing to two, and in some cases to one, the number of adjustable parameters for asphaltenes. Thus, the computational time required for optimization is reduced significantly, without compromising the accuracy of predictions. Moreover, the proposed model has more physical basis for explaining the phase behavior of asphaltenes in crude oils, which also enables a potential extension to include asphaltene polydispersity in the modeling framework. (C) 2013 Elsevier Ltd. All rights reserved.