Development of a General Modelling Methodology for Vacuum Residue Hydroconversion

Abstract

Re´sume´-De´veloppement d'une me´thodologie ge´ne´rale de mode´lisation pour l'hydroconversion de re´sidu sous vide -Ce travail porte sur le de´veloppement d'une me´thodologie de mode´lisation cine´tique de proce´de´s de raffinage, et plus particulie`rement de proce´de´s pour la conversion de re´sidus sous vide. L'approche propose´e permet de surmonter le manque de de´tail mole´culaire des fractions pe´trolie`res et de simuler la transformation des mole´cules de la charge en mole´cules de l'effluent au moyen d'une proce´dure en deux e´tapes. Dans la premie`re e´tape, un me´lange synthe´tique de mole´cules repre´sentant la charge du proce´de´est ge´ne´re´par une me´thode de reconstruction mole´culaire appele´e SR-REM. Dans la seconde e´tape, une me´thode de Monte-Carlo cine´tique est utilise´e pour simuler les re´actions de conversion sur ce me´lange de mole´cules. La reconstruction mole´culaire a e´te´applique´e a`plusieurs re´sidus pe´troliers et est illustre´e pour un re´sidu sous vide Athabasca (Canada). La me´thode de Monte-Carlo cine´tique est ensuite de´crite en de´tail. Afin de valider cette approche stochastique, un mode`le de´terministe regroupe´pour la conversion de re´sidu sous vide a e´te´simule´en utilisant l'algorithme de simulation stochastique de Gillespie. Malgre´le fait que les deux approches sont fonde´es sur des hypothe`ses tre`s diffe´rentes, l'algorithme de simulation stochastique simule les re´actions de conversion avec la meˆme pre´cision que l'approche de´terministe. En utilisant des voies re´actionnelles au niveau mole´culaire, l'approche de simulation stochastique fournit ainsi des informations de´taille´es sur la composition de l'effluent et est brie`vement illustre´e pour l'hydrocraquage du re´sidu sous vide d'Athabasca.Abstract -Development of a General Modelling Methodology for Vacuum Residue Hydroconversion -This work concerns the development of a methodology for kinetic modelling of refining processes, and more specifically for vacuum residue conversion. The proposed approach allows to overcome the lack of molecular detail of the petroleum fractions and to simulate the transformation of the feedstock molecules into effluent molecules by means of a two-step procedure. In the first step, a synthetic mixture of molecules representing the feedstock for the process is generated via a molecular reconstruction method, termed SR-REM molecular reconstruction. In the second step, a kinetic Monte-Carlo method (kMC) is used to simulate the conversion reactions on this mixture of molecules. The molecular reconstruction was applied to several petroleum residues and is illustrated for an Athabasca (Canada) vacuum residue. The kinetic Monte-Carlo method is then described in detail. In order to validate this stochastic approach, a lumped deterministic model for vacuum residue conversion was simulated using Gillespie's Stochastic Simulation Algorithm. Despite the fact that both approaches are based on very different hypotheses, the stochastic simulation algorithm simulates

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

“…The different probability density distribution functions were selected according to the structural properties of the different components. The result confirmed that the simulation error met the requirements. − Zhang et al added structural information analyzed by high-resolution mass spectrometry (HRMS) to the construction of a compositional model of residual oil containing 400,000 molecules. Their results demonstrated that their model could significantly reduce the deviation between simulated and experimental values .…”

Stochastic Modeling and Simulation Approach for Industrial Fixed-Bed Hydrocrackers

“…The slight deviations from the deterministic solution in various sections along the reactor are caused by the inherent random noise of stochastic simulation methods. Such divergences can be corrected by averaging repeated stochastic simulations, as pointed out by de Oliveira et al 50 Therefore, multiple repetitions of the hydrocracker simulations were required in order to eliminate any defects associated with the simulation method. 4.2.…”

Comprehensive Residual Oil Hydrocracking Reaction Kinetic Modeling Combined with Effective Phase Equilibrium Calculation

“…Relevant data especially for the heavy components is very scarce. Monte Carlo method has been applied by a number of authors to develop component sets having proper properties and reaction networks with usable kinetics. − Nevertheless, the positive aspect is that the data concerning real components’ properties and their reactions are not bound to a single system as is the case with lumped components, but once collected and stored to a databank, they can be utilized for handling new cases. Some models accounting for molecular structure have been published, e.g., for gasoil hydrotreating, for fluid catalytic cracker, , and for hydrotreating of light cycle oil from fluid catalytic cracking and hydrocracking of vacuum residues .…”

“…However, the architecture of the model is not dependent on the method used for generation of the feed composition and properties. An alternative approach for feed composition generation would be the Monte Carlo methods presented in the literature. ,− …”