Multicatalyst System Testing Methodology for Upgrading Residual Oils

Abstract

Atmospheric residue desulfurization (ARDS) is one of the major processes installed in refineries worldwide for upgrading petroleum residues to more-valuable clean products. Because of the importance of the process, research and development related to the process and its associated catalysts has gained increasing attention internationally. Hence, it is necessary to develop a reliable testing methodology for evaluating ARDS catalysts in a relatively short time. From our experience, it has been determined that, within 2-3 months, an ARDS catalyst system consisting of 3-5 catalysts can be evaluated and their performance in an industrial unit can be predicted. This requires generating quality data related to the initial activities, kinetic parameters of individual catalysts, the deactivation behavior, and maximum metal capacity in the catalyst system. Using the proposed catalyst evaluation methodology, values of the apparent reaction kinetics and catalyst life can be determined. These data are fed into an in-house developed mathematical model, which enables the prediction of the performance of the same catalyst system in an industrial scale. Very satisfactory results, from both pilotplant test and commercial plant prediction, are realized from the developed methodology. When conducting long-life tests using the same feedstock and catalyst system, but under different operation modes, such as the constant-sulfur mode or the constant-temperature mode, the catalyst deactivation behaviors between the two life tests are significantly different, However, their respective values of the maximum metal-on-catalyst (MMOC) of the total catalyst system are very similar.

Predicted Effects of Heavy Feeds on the Deactivation of a Commercial Atmospheric Residue Desulfurization Catalyst System

“…Albazzaz et al 9 proposed a robust parameter estimation procedure for the ARDS model based on a more generalized procedure. 16 For the robust procedure, kinetic test data provided reaction related information, such as rate constant, reaction order, and activation energy. The accelerated test gave MMOC, fresh Thiele modulus (Φ ij ), and spent Thiele modulus (Φ z,ij ) values of the catalysts, while the early life test data were needed for the contact efficiency (η ij ).…”

“…The experimental data obtained from the kinetic, accelerated, and life tests were used to estimate the parameters of the ARDS model. Albazzaz et al proposed a robust parameter estimation procedure for the ARDS model based on a more generalized procedure . For the robust procedure, kinetic test data provided reaction related information, such as rate constant, reaction order, and activation energy.…”

“…The life test data were then used for comparing simulated vs experimental data, and the mean square error (MSE) was utilized as an assessment method for evaluating the goodness of fit between simulated and experimental data. Parameter estimation was conducted using the first 1000 h of life test data based on previous recommendations, , to estimate individual catalyst parameters. Supporting Information Tables 1–9 list the estimated values of contacting efficiency and Thiele modulus for fresh and spent catalysts for each of the feeds.…”

Gap Analysis and Optimization of Hydroprocessing Prediction Model

“…The same algorithm for obtaining the optimal set of kinetic parameters is employed with similar success in [11]. In [21] a hydroprocessing model taking into account more reactor configuration properties is investigated and the reported predictions' accuracy falls into a ±10% interval. Good modelling results are also achieved in [8, 22 and 23].…”

Robust Predictions of Catalyst Deactivation of Atmospheric Residual Desulfurization

“…Marafi et al summarized a three-step experimental and parameter estimation procedure for the ARDS model proposed by Kam et al…”