Moderator: Shanahan Mondal, Cheniere Energy Speakers:
Andrew Laszewsk, Cenovus Energy - Superior Refinery
Layne Boudreaux, Gabe LaLande, Todd Conner & Lowell Nance, Cheniere Energy - Sabine Pass Liquefaction
David Ybarra, Sascha Schieke & Bart Aupperle, Flint Hills Resources - Corpus Christi Complex
Moderator: Larry Webb, Flint Hills Resources, LLC Speakers:
Nick Martin & Barret Von Behren, Marathon Petroleum Company - Robinson Refinery
Ben Way & Kacey Lopez, Phillips 66 - Sweeny Refinery
Moderator: Shanahan Mondal, Cheniere Energy Speakers:
Andrew Laszewsk, Cenovus Energy - Superior Refinery
Layne Boudreaux, Gabe LaLande, Todd Conner & Lowell Nance, Cheniere Energy - Sabine Pass Liquefaction
David Ybarra, Sascha Schieke & Bart Aupperle, Flint Hills Resources - Corpus Christi Complex
Moderator: Tommy Sessum, Chevron U.S.A. Inc. Speakers:
Justin Newton & Audra Higgins, Phillips 66 - Sweeny Refinery
David Coleman & Jerry Rodriguez, Valero Energy Corporation - McKee Refinery
Woodrow Henderson, Valero Energy Corporation - Three Rivers Refinery
Moderator: Tommy Sessum, Chevron U.S.A. Inc. Speakers:
Justin Newton & Audra Higgins, Phillips 66 - Sweeny Refinery
David Coleman & Jerry Rodriguez, Valero Energy Corporation - McKee Refinery
Woodrow Henderson, Valero Energy Corporation - Three Rivers Refinery
Speakers:
Chris Harrison, Marathon Petroleum Corporation
This session will discuss the project development and workflow, implementation, and application maintenance of an Imubit DLPC that was used to reduce giveaway on drum cycles on a delayed coker unit. The DLPC was successful in reducing the number of cycles in which the target level was not achieved in the fixed cycle time period. This resulted in an overall reduction in the number of barrels given away in each cycle. The application has achieved great acceptance by Operations.
Participants will:
Gain an understanding of the Imubit DLPC application to reduce giveway on Coker Drum cycles
Gain an understanding of the workflow for an Imubit DLPC project
Gain an understanding of unique challenges and lessons learned from the project
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
Discussion of the basics of good data collection, appropriate methods for filtering data, database requirements and the supporting infrastructure for possible Machine Learning applications.
Speakers:
Chris Harrison, Marathon Petroleum Corporation
This session will discuss the project development and workflow, implementation, and application maintenance of an Imubit DLPC that was used to reduce giveaway on drum cycles on a delayed coker unit. The DLPC was successful in reducing the number of cycles in which the target level was not achieved in the fixed cycle time period. This resulted in an overall reduction in the number of barrels given away in each cycle. The application has achieved great acceptance by Operations.
Participants will:
Gain an understanding of the Imubit DLPC application to reduce giveway on Coker Drum cycles
Gain an understanding of the workflow for an Imubit DLPC project
Gain an understanding of unique challenges and lessons learned from the project