(75d) An Equation-Oriented Model of a Trickle-Bed Reactor for Hydrodesulfurization Process Analysis and Digital Twin Applications

The Fourth Industrial Revolution is marked by the convergence of digital, physical, and biological technologies, bringing relevant tools to allow deep process analysis and optimizations, thus enabling more assertive decision-making. One such tool directly linked to rigorous modeling and simulation is the process digital twin. When a digital twin is connected to powerful data sources (i.e., rigorous thermodynamic basis, industrial data sets, and detailed phenomenological models), it can be used for process design ^[1,2]. In this sense, the industrial sector, particularly the oil and gas industry, can benefit of digital twin approaches to improve process efficiency. The Hydrodesulfurization (HDS) process is considered a well-known and established technology used in refineries to remove sulfur compounds, such as sulfides and disulfides, from petroleum fractions. HDS consists of a catalytic process capable of treating a contaminated oil charge stream through a hydrogenation reaction under controlled operating conditions that are highly dependent on the oil physicochemical characteristics ^[3]. However, the definition of such operating conditions, as well as the evaluations related to reactant characteristics and catalysts need special attention.

In this work, the improvement of a rigorous HDS process model, based on a trickle-bed reactor block ^[4] in AVEVA Process Simulation is presented. The previously validated phenomenological model ^[5,6] has been connected to the AVEVA thermodynamics database for comprehensive process analysis. The resulting simulation enables the description of the sulfur removal and the formation of H₂S process throughout the reactor, in addition to satisfactorily predicting the effects on the conversion of the organic sulfur compounds through changes in nominal trickle-bed reactor conditions. The obtained relationship employing this model between the gas/oil ratio and the partial pressure of hydrogen sulfide presented a realistic behavior, enabling improvements on sulfur removal. Operating conditions, such as temperature and pressure, present consistent performance associated with effectiveness of desulfurization. The concentrations of the compounds in liquid phase and on the catalyst surface are analyzed throughout the reactor confirming experimental and industrial results ^[5,6].

References

^[1] Macchi, M., Roda, I., Negri, E., & Fumagalli, L. (2018). Exploring the Role of Digital Twin for Asset Lifecycle Management. IFAC-PapersOnLine, 51(11), 790–795.

^[2] Rosen, R.; Von Wichert, G.; Lo, G., & Bettenhausem, K. D. (2015). About The Importance of Autonomy and Digital Twins for the Future of Manufacturing. In IFAC-PapersOnLine, 48:567–72. Elsevier Ltd.

^[3] Mendez, F.J.; Franco-Lopez, O.E.;. Bokhimi, X.; Solis-Casados, D. A.; Escobar-Alarcon, L., & Klimova, T. E. (2017). Dibenzothiophene hydrodesulfurization with NiMo and CoMo catalysts supported on niobium-modified MCM-41, Appl. Catal. B Environ. 219, pp 479–491.

^[4] Barros, A.; Bishop, B..; Tavernard, A.; Lima, F. V., & Bispo, H. (2020). Development of an Equation Oriented Model Applied to a Hydrodesulfurization (HDS) Process. AIChE Annual Meeting.

^[5] Neto, A. T. P., Fernandes, T. C. R. L., da Silva Junior, H. B., de Araújo, A. C. B., & Alves, J. J. N. (2020). Three-phase trickle-bed reactor model for industrial hydrotreating processes: CFD and experimental verification. Fuel Processing Technology, 208.

^[6] Korsten, H., & Hoffmann, U. (1996). Three phase reactor model for hydrotreating in pilot trickle bed reactor, AIChE Journal, 42, pp 1350-1360.