Refinery System Process Analysis and Testing

Course details

The oil refining process is one of the most complex processes in today's industry, as it incorporates catalyst systems, complex reactor designs, sophisticated computer control hardware and software, and advanced safety and environmental controls.

A typical medium-size refinery has hundreds of pumps, heat exchangers and drums; dozens of furnaces, compressors, and high temperature/high pressure reactors; and thousands of control loops and associated computer control technologies. In order to optimize these complex systems and their interactions approach to single point or single system optimizing cannot work as effectively as we hope, as the refinery has to be considered as a system, rather than connection of its parts. Here is where the multi-method simulation comes to play an important part, as we can use Discrete Event, Agent Based and System Dynamics simulation to incorporate all the refinery systems into one and be able to have the outputs from the system, as well as its components, rather than just having an output from one of the ;  

This training course will feature:

• Explanation of refinery process
• Basis of Discrete Event, Agent Based and System Dynamics simulation
• Establishing relationships between measurements and reservoir properties
• How to minimize overall operating costs while achieving the maximum possible "upgrade" for each hydrocarbon molecule (called "molecule management")
• Hands-on practice in AnyLogic software for all three methods of simulation
• Advanced concepts: AnyLogic fluid library, incorporating operator performance

 
What are the Goals?

By the end of this training course, participants will be able to:

• Learn the concepts and methods of selecting feedstocks and product slates
• Understand the capabilities of AnyLogic as multi-method simulation tool
• Acquire the knowledge to consider the refinery as a system, not a sum off its parts
• Incorporate optimizing models into a simulation package
• Create and run simulations of complex systems
• Harness the possibilities of testing change options in virtual environment

Updated on 01 October, 2018