화학공학소재연구정보센터
Energy & Fuels, Vol.21, No.3, 1248-1255, 2007
Thermodynamic solubility models to predict asphaltene instability in live crude oils
This paper describes a thermodynamic solubility model to predict the asphaltene stability/instability of live crude oil systems under reservoir conditions. The model uses the Hildebrand solubility parameter of stock tank oil to predict the solubility parameter of the live oil under reservoir conditions by incorporating the dissolved gas composition along with the pressure-volume-temperature (PVT) properties of the live oil. Precipitation and deposition of asphaltenes from crude oils resulting from changes in pressure, temperature, and composition have a huge economic impact on the oil industry. Due to the uncertainty in mitigating and preventing asphaltene problems, an accurate prediction of asphaltene instability could help to minimize asphaltene remediation costs. While the Hildebrand solubility parameter concept has been previously used to determine the onset point of asphaltene precipitation in the stock tank oils, it does not capture the effect of dissolved gases on the onset solubility parameter. An empirical correlation between the onset solubility parameter and the molar volume of precipitants has been used to estimate the effect of dissolved gas on the onset solubility parameter of live oil. However, extrapolation of this correlation to higher temperatures and pressures is only valid over a very limited range. Consequently, a model was developed to predict the onset solubility parameter under live oil conditions based on the thermodynamic partial Gibbs free energy rule. Solubility parameters of the stock tank oil were determined and coupled with the equation of state models based on the PVT data of the live oils to predict the asphaltene instability of a live system. To validate the model, high temperature and high pressure experiments were performed using blends of live oil and miscible injection gases and the onset points of asphaltenes were determined. This model is capable of predicting asphaltene instability under live conditions over a wide range of temperatures and pressures.