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 tra...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2013-11-01
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| Series: | Oil & Gas Science and Technology |
| Online Access: | http://dx.doi.org/10.2516/ogst/2013135 |
| _version_ | 1818365308758392832 |
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| author | Pereira de Oliveira L. Verstraete J. J. KoIb M. |
| author_facet | Pereira de Oliveira L. Verstraete J. J. KoIb M. |
| author_sort | Pereira de Oliveira L. |
| collection | DOAJ |
| description | 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 the conversion reactions with the same accuracy
as the deterministic approach. The full-scale stochastic simulation approach using
molecular-level reaction pathways provides high amounts of detail on the effluent
composition and is briefly illustrated for Athabasca VR hydrocracking. |
| first_indexed | 2024-12-13T22:18:12Z |
| format | Article |
| id | doaj.art-619a5df26ca846af9626e2f321cef79c |
| institution | Directory Open Access Journal |
| issn | 1294-4475 1953-8189 |
| language | English |
| last_indexed | 2024-12-13T22:18:12Z |
| publishDate | 2013-11-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | Oil & Gas Science and Technology |
| spelling | doaj.art-619a5df26ca846af9626e2f321cef79c2022-12-21T23:29:27ZengEDP SciencesOil & Gas Science and Technology1294-44751953-81892013-11-016861027103810.2516/ogst/2013135ogst120170Development of a General Modelling Methodology for Vacuum Residue HydroconversionPereira de Oliveira L.Verstraete J. J.0KoIb M.1IFP Energies nouvellesLaboratoire de Chimie, École Normale SupérieureThis 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 the conversion reactions with the same accuracy as the deterministic approach. The full-scale stochastic simulation approach using molecular-level reaction pathways provides high amounts of detail on the effluent composition and is briefly illustrated for Athabasca VR hydrocracking.http://dx.doi.org/10.2516/ogst/2013135 |
| spellingShingle | Pereira de Oliveira L. Verstraete J. J. KoIb M. Development of a General Modelling Methodology for Vacuum Residue Hydroconversion Oil & Gas Science and Technology |
| title | Development of a General Modelling Methodology for Vacuum
Residue Hydroconversion |
| title_full | Development of a General Modelling Methodology for Vacuum
Residue Hydroconversion |
| title_fullStr | Development of a General Modelling Methodology for Vacuum
Residue Hydroconversion |
| title_full_unstemmed | Development of a General Modelling Methodology for Vacuum
Residue Hydroconversion |
| title_short | Development of a General Modelling Methodology for Vacuum
Residue Hydroconversion |
| title_sort | development of a general modelling methodology for vacuum residue hydroconversion |
| url | http://dx.doi.org/10.2516/ogst/2013135 |
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