State estimation for heavy oil hydroprocessing reactors using extended Kalman filters

Abstract

A state estimator for a class of slurry-phase reactors for heavy oil hydroprocessing is presented. The algorithm is based on the extended Kalman filter formulation for non-linear systems under plant-model mismatch. Although state and parameter estimation have been widely used in the literature for different reacting systems, so far it has not been applied in multiphase slurry reactors for heavy oil hydroprocessing since modeling and simulation of this type of systems is still an emerging area. The reactor and kinetic models used to formulate the filter algorithm were taken from the literature for hydrocracking and hydrotreating reactions of an atmospheric residue (312 °C+) for different slurry-phase reactor configurations. In order to simulate a real plant operation were measurements for heavy oil composition are difficult to obtain online, the present study assumed that the system states were estimated using only temperature measurements and the proposed slurry-phase reactor models. Simulation results have shown that the extended Kalman filter provides acceptable estimations of the systems states and that they can be used for online control and process optimization. However, these results need to be validated once experimental data for this system becomes available.