Employing Combined Subsurface and Facility Digital Twins to Optimize Production and Reduce Carbon Footprint of Oil and Gas Assets

SPEAKERS

Gerardo Munoz Product Marketing Manager, Aspen Technology, Inc

ABOUT THE SESSION

Gerardo Muñoz, Product Marketing Manager at Aspen Technology, is deeply passionate about sustainability and fostering inclusive workplaces where authenticity thrives. With extensive experience in product messaging, sales enablement, and content development for AspenTech’s sustainability solutions and Aspen Plus process simulation software, he brings a unique blend of technical and strategic expertise. Over six years, he has served as a trusted Solution Consultant for clients across Latin America and previously led global training on AspenTech’s engineering products. With a background in alternative fuels research and carbon capture design, Gerardo is set to share his insights on employing combined subsurface and facility digital twins to optimize production and reduce the carbon footprint of oil and gas assets.

He will share his views on implementing practical digital twins that span both reservoir and facility models, enabling a unified view of operations to maximize asset performance. By harnessing existing data and incorporating hybrid models, he highlights how AI can significantly boost the predictive capabilities of digital twins, supporting proactive decision-making. His approach emphasizes operational efficiency while also uncovering actionable opportunities for carbon emission reduction in active oil and gas assets. He will demonstrate how integrating AI and engineering models not only enhances productivity but also aligns with sustainability objectives. Drawing from compelling case studies, he will showcase real-world applications that prove the transformative impact of digital twins—delivering measurable gains in performance, cost-efficiency, and environmental compliance.

Key Topics-

1. Practical digital twins that span reservoir and facility models and data to maximize asset performance
 

2. Exploit existing data and employ hybrid models to integrate AI into predictive power of the digital twin
 

3. Identify opportunities for carbon emission reduction in producing assets
 

4. Case studies

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