Molecular reconstruction model based on structure oriented lumping and group contribution methods

Molecular management is a promising technology to face challenges in the refining industry, such as more stringent requirements for product oil and heavier crude oil, and to maximize the value of every molecule in petroleum fractions. To achieve molecular management in refining processes, a novel model that is based on structure oriented lumping(SOL) and group contribution(GC) methods was proposed in this study. SOL method was applied to describe a petroleum fraction with structural increments, and GC method aimed to estimate molecular properties. The latter was achieved by associating rules between SOL structural increments and GC structures. A three-step reconstruction algorithm was developed to build a representative set of molecules from partial analytical data. First, structural distribution parameters were optimized with several properties. Then, a molecular library was created by using the optimized parameters. In the final step, maximum information entropy(MIE) method was applied to obtain a molecular fraction. Two industrial samples were used to validate the method, and the simulation results of the feedstock properties agreed well with the experimental data.

Molecular reconstruction of vacuum gas oils using a general molecule library through entropy maximization

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.

Molecule-based kinetic modeling by Monte Carlo methods for heavy petroleum conversion

A methodology for kinetic modeling of conversion processes is presented.The proposed approach allows to overcome the lack of molecular detail of the petroleum fractions and to simulate the reactions of the process by means of a two-step procedure.In the first step,a synthetic mixture of molecules representing the feedstock is generated via a molecular reconstruction method,termed SR-REM molecular reconstruction.In the second step,a kinetic Monte Carlo method,termed stochastic simulation algorithm(SSA),is used to simulate the effect of the conversion reactions on the mixture of molecules.The resulting methodology is applied to the Athabasca vacuum residue hydrocracking.An adequate molecular representation of the vacuum residue is obtained using the SR-REM algorithm.The reaction simulations present a good agreement with the laboratory data for Athabasca vacuum residue conversion.In addition,the proposed methodology provides the molecular detail of the vacuum residue conversion throughout the reactions simulations.