Lessons Learned from Spent Acid Rail Car Incident
Learning From Incidents
This session will share an incident from the summer of 2022 where an RV lifted on a spent acid rail car. Key topics will include the conditions that led to the relief, the response to mitigate the release, and the causal understanding of why the relief occurred. Finally, the discussion will focus on considerations for preventing future similar releases.
Facilitator: Ray Chafin, Pemex Deer Park
Speakers:
Hi Chen, Pemex Deer Park
Ahram Yoon, Pemex Deer Park
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
-