Modeling of asphaltene precipitation and arterial deposition

The potential problem produced by asphaltene deposition during oil production has motivated the development of several experimental techniques and theoretical models, trying to understand and predict the asphaltene behavior. Despite the work devoted to understanding this subject, asphaltene deposition still represents a challenging unresolved problem. Predicting asphaltene flow assurance issues requires the ability to model phase behavior of asphaltenes as a function of temperature, pressure, and composition. It has been previously shown that the Perturbed Chain form of the Statistical Associating Fluid Theory equation of state (PC-SAFT EOS) accurately predicts crude oil bubble point and density as well as asphaltene precipitation conditions. This approach has been used to examine the effects of gas injection, oil based mud contamination, and asphaltene polydispersity on the phase behavior of asphaltenes. In this work, a new application of the PC-SAFT EOS in studying the effect of carbon dioxide injection reveals an interesting dual effect of this compound in inducing or preventing asphaltene precipitation, depending on the operating conditions. Novel tools for understanding and predicting properties of hydrocarbon and crude oil systems are also presented and discussed. These tools include the One-Third Rule---a correlation between refractive index and mass density---, a revised solubility parameter modeling approach that includes an improved mixing rule for solubility parameters, and the development of a general method for modeling asphaltene stability. The development of a simulation tool that simultaneously accounts for asphaltene precipitation, aggregation and deposition is also presented and discussed. The thermodynamic modeling using the PC-SAFT EOS is coupled with kinetic models and transport equations. The mechanism for asphaltene precipitation and deposition proposed in this work has been found to be consistent with various experiments and field observations. Furthermore, it also provides an explanation to some paradoxes, such as why some asphaltene precipitation inhibitors worsen asphaltene deposition or why strong asphaltene precipitants, such as propane, produce less amount of deposit. The work presented in this dissertation will contribute in the development of a foundation for oil sample analysis and simulations that can predict the likelihood of asphaltene deposition in the newly found oil fields worldwide