A crude oil system can become unstable because of changes in hydrocarbon composition, pressure, or temperature during normal production from the reservoir or during commingling with dissimilar crude oils. These changes can generate asphaltene particles that can result in significant production and refining problems. The generation of these particles is a two-step process: phase separation and asphaltene particle growth. Phase separation occurs when nanosize asphaltene particles from the crude oil precipitate and grow into large aggregates. Our study on asphaltene precipitation shows that large asphaltene particles are aggregates consisting of very small (sub-micrometer) size asphaltene particles. One mechanism to control asphaltenes is to kinetically inhibit the phase separation of asphaltenes by adding a small amount of a chemical that interferes with the phase separation processes. Another mechanism to control asphaltenes is to inhibit growth by stabilizing the colloidal suspension of the sub-micrometer asphaltene particles to significantly slow the flocculation and settling processes. Asphaltene chemical additives of known molecular structures as well as proprietary chemical blends were selected for this study. None of chemicals studied inhibited phase separation; however, some of the dispersants did slow or stop flocculation and growth. Four different analytical techniques have been used to study the effect of chemical additives on asphaltene aggregation and settling and to evaluate the effectiveness of different asphaltene chemicals in keeping asphaltene particles suspended/dispersed in crude oils. From the turbidity measurement, asphaltene dispersants can be classified into three categories based on their performance. The particle size distribution measurement showed three different types of asphaltenes: stable asphaltenes, colloidal asphaltenes, and flocculated asphaltenes, on the basis of aggregate sizes. Asphaltene dispersants can stabilize colloidal asphaltenes and slow the growth and formation of flocculated asphaltenes. These results can be used to select the best chemical treatment plan for preventing/reducing asphaltene settling and deposition.

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.