Compositional Modeling of VGO Fractions via Analytical Characterization, Structural Assignment, Property Modeling, and Molecular Component Parsing

Abstract

The detailed molecular characterization of the vacuum gas oil (VGO) fractions is the key to understanding petroleum structure−property relationships and optimizing petroleum refinery operations. In our study, a rapid VGO database-based molecular component parsing method was proposed that could directly calculate detailed molecular composition information using conventional bulk properties as inputs. The molecular database of VGO included four aspects: analytical characterization, molecular structural assignment, single molecular property estimation, and bulk property prediction. According to our established molecular database of typical VGO samples, two main parts in the rapid parsing algorithm of the molecular components were present. The method screened the VGO samples with the most similar bulk properties. The molecular component contents of the most similar sample were subsequently optimized by a simulated annealing algorithm, thereby finally obtaining the practical molecular composition of VGO. Our proposed method overcomes the drawbacks of the virtual molecular information acquired by the traditional compositional reconstruction algorithm. Our results were more accurate, obtained faster, and could facilitate a solid foundation for refineries to achieve the optimization of the entire molecular process simulation.