(193ae) Characterization of Multicomponent Mixtures Based On Real Surrogate Components | AIChE

(193ae) Characterization of Multicomponent Mixtures Based On Real Surrogate Components


Mair-Zelenka, P. - Presenter, Graz University of Technology
Wallek, T. - Presenter, Graz University of Technology, NAWI Graz
Reiter, A. - Presenter, Graz University of Technology
Siebenhofer, M. - Presenter, Graz University of Technology

The characterization of multicomponent mixtures – especially in the field of petroleum engineering – has been a challenging task ever since. In recent years efforts have been made to describe multicomponent mixtures like crude oil in terms of real components to achieve a better understanding for downstream processes based on detailed molecular information.

This approach for the characterization of crude oil is based on key components in terms of surrogate components to properly model fuels leaving the simulated crude oil distillation unit (CDU). An optimization algorithm yields a substitute mixture defined in terms of selected key components and their corresponding amount. Thermodynamic validation of the algorithm is based on equation of state binary interaction parameters (EOS BIPs) and a characteristic distillation curve.

Validation of the simulation results is carried out with operation data of a crude oil distillation unit. It has been demonstrated that multicomponent mixtures can be characterized by using key components instead of the state-of-the-art pseudocomponent approach.

The specification of multicomponent mixtures within this work – three different types of crude oil have been subject of investigation – is accessible via experimental determination of the true boiling point curve (TBP) and the corresponding fragment densities. Crucial factor within this approach is the use of fragment densities instead of density curves.

Representative components for each fragment density are selected with respect to their individual density and the boiling temperature range of the respective fragment density.

An extended optimization-approach based on minimization of differences between experimentally obtained and predicted values provides the basis for calculating the fraction of each real component in the simulated mixture.

The quality of simulation results based on key components is then evaluated with operation data via comparison of the fragment densities, distillation curves as well as other important parameters such as the cloud point.

The algorithm provides a first step in an expandable characterization based on real components with real physical properties instead of pseudocomponents.