Vacuum gas oil (VGO) is the most important feedstock for hydrocracking processes in refineries

but its molecular composition cannot be fully acquired by current analysis techniques owing to its complexity. In order to build an accurate and reliable molecular-level kinetic model for reactor design and process optimization

the molecular composition of VGO has to be reconstructed based on limited measurements. In this study

a modified stochastic reconstruction-entropy maximization (SR-REM) algorithm was applied to reconstruct VGOs

with generation of a general molecule library once and for all

via

the SR method at the first step and adjustment of the molecular abundance of various VGOs

via

the REM method at the second step. The universality of the molecule library and the effectiveness of the modified SR-REM method were validated by fifteen VGOs (three from the literature) from different geographic regions of the world and with different properties. The simulated properties (density

elemental composition

paraffin-naphthene-aromatics distribution

boiling point distribution

detailed composition of naphthenes and aromatics in terms of ring number as well as composition of S-heterocycles) are in good agreement with the measured counterparts

showing average absolute relative errors of below 10% for each property.