Main Column Bottoms Operation and Optimization
101 Series, FCC
This session will review a collaboration between UOP and Marathon to optimize operation of the FCC bottoms section. After detecting fouling in the main column slurry pumparound packing, an innovative internals modification was implemented to minimize this in the future. This presentation will review the observed benefits of the new internals and provide an overview of key variables to monitor in the bottoms circuit.
Moderator:
Michael Allegro, BASF Corporation
Speakers:
Ryan Brown, Marathon Petroleum Corporation
Nick Turner, Honeywell UOP
Speakers
Session Start End
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Topic
Implementing a Refinery Diesel Pool Optimizer Using Neural Networks and Reinforcement Learning
Artificial Intelligence, Advanced Process Controls
Facilitator:
Atique Malik, AIControl LLC
Speaker:
Yangdong Pan, Delek US
Toni Adetayo, Imubit, Inc.
Multi-unit optimization has long been a complex issue in the oil and gas industry. Despite efforts using first-principle models or empirical approaches, challenges persist. However, the emergence of machine learning and AI technologies offers an alternative solution. In particular, AI-based process control technology has shown promise for multi-unit optimization. This session will delve into an example using a distillate system optimizer to understand how these AI models address large-scale optimization challenges and how parent and child models collaborate.
Participants will learn:
- The strength of the technology and its high flexibility of handling core issues
- How the technology deals with the availability of individual units, and cooperates with unit controllers from other advanced control technologies
- How to sustain the technology’s performance and benefits
- A site-wide AI adoption strategy
Speakers
Session Start End
-
Implementing a Refinery Diesel Pool Optimizer Using Neural Networks and Reinforcement Learning
Artificial Intelligence, Advanced Process Controls
Facilitator:
Atique Malik, AIControl LLC
Speaker:
Yangdong Pan, Delek US
Toni Adetayo, Imubit, Inc.
Multi-unit optimization has long been a complex issue in the oil and gas industry. Despite efforts using first-principle models or empirical approaches, challenges persist. However, the emergence of machine learning and AI technologies offers an alternative solution. In particular, AI-based process control technology has shown promise for multi-unit optimization. This session will delve into an example using a distillate system optimizer to understand how these AI models address large-scale optimization challenges and how parent and child models collaborate.
Participants will learn:
- The strength of the technology and its high flexibility of handling core issues
- How the technology deals with the availability of individual units, and cooperates with unit controllers from other advanced control technologies
- How to sustain the technology’s performance and benefits
- A site-wide AI adoption strategy
Speakers
Session Start End
-