(77b) Heavy Oil Hydroconversion: Modeling Composition and Chemistry | AIChE

(77b) Heavy Oil Hydroconversion: Modeling Composition and Chemistry

Authors 

Raman, S. - Presenter, Exxonmobil Research & Engineering Comp
Pyl, S., Exxonmobil Research & Engineering Comp
Harper, M. R., ExxonMobil
Quann, R. J., ExxonMobil Research & Engineering
Crude oil refining heavily relies on process models for a wide variety of applications, including refinery operations planning and scheduling, real-time optimization, opportunity studies and process design. Only process models that incorporate a fundamental understanding of crude oil composition, kinetics and thermodynamics possess the necessary flexibility and rigor required by present-day refineries.

Modeling the composition and chemistry of the heaviest crude oil fractions and thermally processed heavy ends has long remained a challenge. At the same time, unlocking their true value by better understanding their behavior has become increasingly important as refiners attempt to upgrade these low-cost oil fractions into the highest-value products. Thanks to recent advances in analytical chemistry it is now possible to characterize these fractions with an unprecedented level of detail. Advanced analytical techniques such as FT-ICR MS and FD-MS enabled to gain fundamental insights into their composition. Moreover, through analyses of feed and product pairs allows for better understanding of conversion chemistry and kinetics.

Using these insights and building on the principles of structure-oriented lumping (SOL), novel methods have been developed to describe the composition, phase behavior and hydroconversion chemistry of heavy ends. Lumping of structural isomers into homologous series of components is a powerful strategy to organize molecules into a tractable set of components. However, the vast chemical diversity observed in heavy oils calls for alternative strategies to keep the number of components (and therefore the number of differential equations in a process model) manageable. The developed modeling approach uses clusters of chemistry-related components to arrive at a concise description of composition, generate large reaction networks, and define kinetic rate expressions. The approach ensures that the resulting model of composition (i) remains detailed enough so it can capture key compositional differences between heavy oils; (ii) enables adequate description of phase behavior and conversion chemistry.