Simulating vacuum residue hydroconversion by means of Monte-Carlo techniques

• We model both feedstock composition and process reactions at a molecular level.
• The feedstock is represented by mixtures of molecules exhibiting key feedstock properties.
• The reactions are simulated by a kinetic Monte Carlo method on the set of molecules.
• The methodology was applied to the hydroconversion of an Ural vacuum residue.
• Both the feed and the effluents were favorably compared to experimental data.

The present work focuses on the development of a novel methodology for the kinetic modeling of heavy oil conversion processes. The methodology models both the feedstock composition and the process reactions at a molecular level. The composition modeling consists of generating a set of molecules whose properties are close to those of the process feedstock analyses. This synthetic mixture of molecules is generated by a two-step molecular reconstruction algorithm. In its first step, an equimolar set of molecules is built by assembling structural blocks in a stochastic manner. In the second step, the mole fractions of the molecules are adjusted by maximizing an information entropy criterion. Once the composition of the feedstock is represented, the conversion process is simulated by applying, event by event, its main reactions to the set of molecules by means of a kinetic Monte Carlo (kMC) method. The methodology has been applied to hydroconversion of Ural vacuum residue and both the feed and the predicted effluents were favorably compared to the experimental yield pattern.