IMPROVING HYDROCARBON RESIDUE FEED DEFINITION THROUGH VALIDATED SIMULATION MODELS

The conventional development of deasphalting processes relies on costly and time-consuming lab experiments. This study introduces a more efficient approach using simulation to tackle these challenges. The method identifies the composition of synthetic crude oil (SCO) feedstock, dividing it into four key molecular groups: Saturates, Aromatics, Resins, and Asphaltenes (SARA). These groups are pseudo-components in the simulation, characterized by parameters like boiling points and molecular weights. The simulated boiling points are then compared with actual crude oil to ensure accuracy. The framework is applied to model hydrocarbon residue in Lube Oil production, testing adaptability across various feedstocks. The strategy to improve the simulation's accuracy was adjusting molecular interactions for asphaltene separation and refining pseudo-components. This resulted in a boiling point curve with an RMSD of 2.689, closely matching the actual residue curve. This approach improves the precision of deasphalting while reducing dependence on resource-heavy lab work.