IFP Energies nouvelles International Conference: MAPI 2012: Multiscale Approaches for Process Innovation
Open Access
Numéro
Oil Gas Sci. Technol. – Rev. IFP Energies nouvelles
Volume 68, Numéro 6, November-December 2013
IFP Energies nouvelles International Conference: MAPI 2012: Multiscale Approaches for Process Innovation
Page(s) 1027 - 1038
DOI https://doi.org/10.2516/ogst/2013135
Publié en ligne 13 novembre 2013
  • Boduszynski M.M. (1987) Composition of heavy petroleums. 1. Molecular weight, hydrogen deficiency, and heteroatom concentration as a function of atmospheric equivalent boiling point up to 1400.degree.F (760.degree. C), Energy Fuels 1, 2-11. [CrossRef] [Google Scholar]
  • Neurock M., Libanati C., Nigam A., Klein M.T. (1990) Monte Carlo simulation of complex reaction systems: molecular structure and reactivity in modelling heavy oils, Chem. Eng. Sci. 45, 2083-2088. [CrossRef] [Google Scholar]
  • Quann R.J., Jaffe S.B. (1992) Structure-oriented lumping: describing the chemistry of complex hydrocarbon mixtures, Ind. Eng. Chem. Res. 31, 2483-2497. [CrossRef] [Google Scholar]
  • Jaffe S.B., Freund H., Olmstead W.N. (2005) Extension of Structure-Oriented Lumping to Vacuum Residua, Ind. Eng. Chem. Res. 44, 9840-9852. [CrossRef] [Google Scholar]
  • Liguras D.K., Allen D.T. (1989) Structural models for catalytic cracking. 1. Model compound reactions, Ind. Eng. Chem. Res. 28, 665-673. [CrossRef] [Google Scholar]
  • Martens G.G., Marin G.B. (2001) Kinetics for hydrocracking based on structural classes: Model development and application, AIChE J. 47, 1607-1622. [CrossRef] [Google Scholar]
  • Lopez-Garcia C., Hudebine D., Schweitzer J.-M., Verstraete J.J., Ferré D. (2010) In-depth modeling of gas oil hydrotreating: From feedstock reconstruction to reactor stability analysis, Catal. Today 150, 279-299. [CrossRef] [Google Scholar]
  • Charon-Revellin N., Dulot H., Lopez-Garcia C., Jose J. (2011) Kinetic Modeling of Vacuum Gas Oil Hydrotreatment using a Molecular Reconstruction Approach, Oil Gas Sci. Technol. — Revue d’IFP Energies nouvelles 66, 479-490. [CrossRef] [EDP Sciences] [Google Scholar]
  • Martens G.G., Marin G.B., Martens J.A., Jacobs P.A., Baron G.V. (2000) A Fundamental Kinetic Model for Hydrocracking of C$ to C12 Alkanes on Pt/US—Y Zeolites, J. Catal. 195, 253-267. [CrossRef] [Google Scholar]
  • Valéry E., Guillaume D., Surla K., Galtier P., Verstraete J. J., Schweich D. (2007) Kinetic Modeling of Acid Catalyzed Hydrocracking of Heavy Molecules: Application to Squalane, Ind. Eng. Chem. Res. 46, 4755-4763. [CrossRef] [Google Scholar]
  • Guillaume D., Valéry E., Verstraete J.J., Surla K., Galtier P., Schweich D. (2011) Single Event Kinetic Modelling without Explicit Generation of Large Networks: Application to Hydrocracking of Long Paraffins, Oil Gas Sci. Technol. — Revue d’IFP Energies nouvelles. 66, 399-422. [CrossRef] [EDP Sciences] [Google Scholar]
  • Mitsios M., Guillaume D., Galtier P., Schweich D. (2009) Single-Event Microkinetic Model for Long-Chain Paraffin Hydrocracking and Hydroisomerization on an Amorphous Pt/SiO2 Al2O3 Catalyst, Ind. Eng. Chem. Res. 48, 3284-3292. [CrossRef] [Google Scholar]
  • Shahrouzi J.R., Guillaume D., Rouchon P., Da Costa P. (2008) Stochastic Simulation and Single Events Kinetic Modeling: Application to Olefin Oligomerization, Ind. Eng. Chem. Res. 47, 4308-4316. [CrossRef] [Google Scholar]
  • Lozano-Blanco G., Thybaut J.W., Surla K., Galtier P., Marin G.B. (2008) Single-Event Microkinetic Model for Fischer—Tropsch Synthesis on Iron-Based Catalysts, Ind. Eng. Chem. Res. 47, 5879-5891. [CrossRef] [Google Scholar]
  • Lozano-Blanco G., Surla K., Thybaut J.W., Marin G.B. (2011) Extension of the Single-Event Methodology to Metal Catalysis: Application to Fischer-Tropsch Synthesis, Oil Gas Sci. Technol. — Revue d’IFP Energies nouvelles. 66, 423-435. [CrossRef] [EDP Sciences] [Google Scholar]
  • Cochegrue H., Gauthier P., Verstraete J.J., Surla K., Guillaume D., Galtier P., et al. (2011) Reduction of Single Event Kinetic Models by Rigorous Relumping: Application to Catalytic Reforming, Oil Gas Sci. Technol. — Revue d’IFP Energies nouvelles. 66, 367-397. [CrossRef] [EDP Sciences] [Google Scholar]
  • Broadbelt L.J., Stark S.M., Klein M.T. (1994) Computer Generated Pyrolysis Modeling: On-the-Fly Generation of Species, Reactions, and Rates, Ind Eng. Chem. Res. 33, 790-799. [CrossRef] [Google Scholar]
  • De Witt M.J., Dooling D.J., Broadbelt L.J. (2000) Computer Generation of Reaction Mechanisms Using Quantitative Rate Information: Application to Long-Chain Hydrocarbon Pyrolysis, Ind. Eng. Chem. Res. 39, 2228-2237. [CrossRef] [Google Scholar]
  • Liguras D.K., Neurock M., Klein M.T., Stark S.M., Libanati C., Nigam A., et al. (1992) Monte Carlo simulation of complex reactive mixture: An FCC case study, AIChE Symposium Series 88, 68-75. [Google Scholar]
  • Merdrignac I., Espinat D. (2007) Physicochemical Characterization of Petroleum Fractions: the State of the Art, Oil Gas Sci. Technol. — Revue d’IFP Energies nouvelles. 62, 7-32. [CrossRef] [EDP Sciences] [Google Scholar]
  • Hudebine D., Verstraete J.J. (2004) Molecular reconstruction of LCO gasoils from overall petroleum analyses, Chem. Eng. Sci. 59, 4755-4763. [CrossRef] [Google Scholar]
  • Verstraete J.J., Revellin N., Dulot H. (2004) Molecular reconstruction of vacuum gasoils, Preprints of Papers — Am. Chem. Soc. Division Fuel Chem. 49, 20-21. [Google Scholar]
  • Verstraete J.J., Schnongs P., Dulot H., Hudebine D. (2010) Molecular reconstruction of heavy petroleum residue fractions, Chem. Eng. Sci. 65, 304-312. [CrossRef] [Google Scholar]
  • de Oliveira L.P., Trujillo Vazquez A., Verstraete J.J., Kolb M. (2013) Molecular reconstruction of petroleum fractions: Application to various vacuum residues, Energy Fuels 27, 3622-3641. [CrossRef] [Google Scholar]
  • Hudebine D., Verstraete J.J., Chapus T. (2011) Statistical Reconstruction of Gas Oil Cuts, Oil Gas Sci. Technol. —. Revue d’IFP Energies nouvelles 66, 461-477. [CrossRef] [EDP Sciences] [Google Scholar]
  • Neurock M., Nigam A., Trauth D.M., Klein M.T. (1994) Molecular representation of complex hydrocarbon feedstocks through efficient characterization and stochastic algorithms, Chem. Eng. Sci. 49, 4153-4177. [CrossRef] [Google Scholar]
  • Trauth D.M., Stark S.M., Petti T.F., Neurock M., Klein M.T. (1994) Representation of the Molecular Structure of Petroleum Resid through Characterization and Monte Carlo Modeling, Energy Fuels 8, 576-580. [CrossRef] [Google Scholar]
  • Hudebine D., Verstraete J.J. (2011) Reconstruction of Petroleum Feedstocks by Entropy Maximization. Application to FCC Gasolines, Oil Gas Sci. Technol. — Revue d’IFP Energies nouvelles 66, 437-460. [CrossRef] [EDP Sciences] [Google Scholar]
  • Van Geem K.M., Hudebine D., Reyniers M.-F., Wahl F., Verstraete J.J., Marin G.B. (2007) Molecular reconstruction of naphtha steam cracking feedstocks based on commercial indices, Comput. Chem. Eng. 31, 1020-1034. [CrossRef] [Google Scholar]
  • Van Geem K.M., Reyniers M.-F., Marin G.B. (2008) Challenges of Modeling Steam Cracking of Heavy Feedstocks, Oil Gas Sci. Technol. — Revue d’IFP Energies nouvelles 63, 79-94. [CrossRef] [EDP Sciences] [Google Scholar]
  • Shannon C.E. (1948) A mathematical theory of communication, Bell Syst. Tech. J. 27, 379-423, 623-656. [CrossRef] [MathSciNet] [Google Scholar]
  • Boduszynski M.M. (1988) Composition of heavy petroleums. 2, Molecular characterization, Energy Fuels 2, 597-613. [CrossRef] [Google Scholar]
  • McKenna A.M., Blakney G.T., Xian F., Glaser P.B., Rodgers R.P., Marshall A.G. (2010) Heavy Petroleum Composition. 2. Progression of the Boduszynski Model to the Limit of Distillation by Ultrahigh-Resolution FTICR Mass Spectrometry, Energy Fuels 24, 2939-2946. [CrossRef] [Google Scholar]
  • Sheu E.Y. (2002) Petroleum AsphalteneProperties, Characterization, and Issues, Energy Fuels 16, 74-82. [CrossRef] [Google Scholar]
  • Wiehe I.A. (1994) The Pendant-Core Building Block Model of Petroleum Residua, Energy Fuels 8, 536-544. [CrossRef] [Google Scholar]
  • API 2B2.I (1987) API procedure 2B2.1 for estimating the molecular weight of a petroleum fraction, API Technical Handbook. [Google Scholar]
  • Gillespie D.T. (1976) A general method for numerically simulating the stochastic time evolution of coupled chemical reactions, J. Comput. Phys. 22, 403-434. [NASA ADS] [CrossRef] [MathSciNet] [Google Scholar]
  • Gillespie D.T. (2007) Stochastic simulation of chemical kinetics, Annu. Rev. Phys. Chem. 58, 35-55. [NASA ADS] [CrossRef] [PubMed] [Google Scholar]
  • Gillespie D.T. (1992) A rigorous derivation of the chemical master equation, Physica A: Statistical Mechanics and Its Applications 188, 404-425. [NASA ADS] [CrossRef] [Google Scholar]
  • Schweitzer J.-M., Kressmann S. (2004) Ebullated bed reactor modeling for residue conversion, Chem. Eng. Sci. 59, 5637-5645. [CrossRef] [Google Scholar]
  • Pereira de Oliveira L., Verstraete J.J., Kolb M. (2012) A Monte Carlo modeling methodology for the simulation of hydrotreating processes, Chem. Eng. J. 207-208, 94-102. [CrossRef] [Google Scholar]
  • de Oliveira L.P., Verstraete J.J., Kolb M. (2013) Molecule- based kinetic modeling by Monte Carlo methods for heavy petroleum conversion, Science China Chemistry, DOI: 10.1007/s11426-013-4989-3 (in press). [Google Scholar]
  • de Oliveira L.P., Verstraete J.J., Kolb M. (2013) Simulating vacuum residue hydroconversion by means of Monte- Carlo techniques, Catalysis Today, DOI: 10.1016/j.cattod. 2013.08.011 (in press). [Google Scholar]

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