(520f) Decoding Hydrocracking Selectivity: A Molecular-Level Approach to Polycyclic Transformations in Vgo Conversion at Industrial Scale

Vacuum gas oil (VGO) hydroconversion is a critical upgrading process in modern refineries, aiming to transform low-value heavy fractions into lighter, more valuable products suitable for fuel production or petrochemical feedstocks. With increasing interest in maximizing yields for steam cracking applications and in adapting refinery operations to co-process alternative feedstocks, the ability to understand and predict VGO hydrocracking behavior at a molecular level has become essential for improving operational flexibility and catalyst design.

To reproduce the observed industrial process behavior, several methodological enhancements to a previously developed kinetic framework were required. Central to the success of the modeling was the extension of the lumping scheme to account for the complexity of the VGO feed. This included an extension of the considered structural classes to explicitly represent multi-ring naphthenic species undergoing ring-splitting reactions (see figure). To account for ring-splitting reactions, structural classes comprising two (poly)-rings connected either by a sigma bond or through a linear or paraffinic bridge are introduced.

The model was validated against industrial performance data, and it allowed the simulation of detailed product distributions by carbon number and by chemical family (paraffins, iso paraffins, naphthenes, and aromatics). Across all catalyst life stages, the model demonstrated strong agreement with experimental observations, both in terms of conversion and selectivity. It accurately captured the shifting boiling range of the products and the redistribution of molecular structures among product families.

This work contributes a mechanistically grounded and statistically validated tool for the simulation and analysis of VGO hydrocracking. It establishes a direct connection between catalyst properties, molecular feedstock composition, and observed product distributions under industrially relevant conditions. This extended SEMK framework provides a pathway toward the rational design of catalyst formulations and operating strategies, particularly useful under constraints of feed variability.