(406e) Simulation As a Tool for Learning from Historical FCC Regenerator Operations | AIChE

(406e) Simulation As a Tool for Learning from Historical FCC Regenerator Operations


Simulation As A Tool For Learning From Historical FCC Regenerator Operations

John Pendergrass, Peter Blaser, Sam Clark


10899 Montgomery Blvd. NE, Suite A, Albuquerque, NM USA

E-mail: john.pendergrass@cpfd-software.com


Simulation of FCCUs is frequently used when anticipating changes to design or process conditions, and is often performed prior to a turnaround. Simulation has been shown to identify root causes of underperformance, test the effects of potential changes prior to implementation, and minimize the risk of unforeseen negative consequences of changes.

Successful utilization of simulation by refiners requires both technology and people. While multiphase gas-particle simulation technology has significantly matured in recent years, other industry trends have been observed which affect the average experience level of personnel working on FCCUs. In many cases retirement has reduced the in-house expertise pool in this area, particularly those with 30+ years of specialty experience with FCC technology. Simultaneously, highly skilled newer staff are rapidly rotated through multiple areas of refinery operations, with seemingly increasing frequency. As a result, the pool of those with deep experience with FCCUs, especially spanning multiple units or multiple turnaround cycles, is declining.

This presentation and discussion is focused on how simulation is used to capture lessons learned from current and historical FCCU operations and convert this knowledge to prediction of future proposed changes. Multiple case studies are presented from both North American and international refiners, where simulations were used to understand and mitigate issues such as erosion, emissions, afterburn, and catalyst losses. The simulation results and historical operational data are analyzed to capture lessons learned, both positive and negative. Finally, examples of simulation to predict the effects of proposed changes are presented.


This paper has an Extended Abstract file available; you must purchase the conference proceedings to access it.


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