Join us for a discussion focused on how value is identified, communicated, and realized through data, analytics, and AI in energy organizations. The conversation will explore transparency, governance, adoption, and leadership responsibility, with audience participation encouraged throughout. 

Moderator: Shayne Chidlaw, Event Co Chair

Guest: Melanie Popp, Director - Operations Consulting at PwC.

Melanie Popp is an experienced professional with over 20 years of experience in the energy, utilities, and other asset-intensive industries. As a Director in PwC Canada's Digital Operations team, Melanie specializes in operational excellence, focusing on improving daily work from the office to the field. She has a proven track record of leading engagements that emphasize upskilling, business process improvement, and strategy realization.

At PwC, Melanie has been instrumental in leading AI-driven initiatives, helping clients harness the power of AI to enhance productivity and drive innovation. Her work includes developing strategies for AI adoption, facilitating workshops, and providing insights on the latest AI trends and technologies.

Session Chairs: Estelle Ducatel, ARC Resources; Danial Kaviani, Independent; Jessie Wang, ConocoPhillips Canada

The application of physics-informed, computationally efficient, and interpretable machine learning techniques in oil and gas operations and subsurface modeling has grown significantly in recent years. This session presents four use cases demonstrating how these methods are applied to diverse data sources to predict and optimize operations across the entire value chain, from subsurface characterization to surface facilities and plant operations.

Presentations:

Plunger/GAPL Well Production Optimization Using Machine Learning
Yousef Hamedi Shokrlu and Robb Oliver, Ovintiv

Scientific Machine Learning for Modeling Industrial Scale Primary Separation Vessel
Bart Maciszewski, Imperial

Optimizing Stimulation Treatments Using Post-Fracture Pressure Decay Analysis Combined with Machine Learning
Wannees Alkhayyali, University of Calgary

Interplay of Well Spacing and Economics
Ryan Hassen, whitson

 

This session focuses on choosing the right analytical approach for the problem at hand. Through real-world examples like ShadowOPs, we’ll show how fit-for-purpose analytics can unlock insights that improve efficiency and decision-making in complex energy operations. Learn why selecting the right tools matters for driving practical, measurable results.

Session Chairs: Session Chairs: Shayne Chidlaw, Independent; Danial Kaviani, Independent

Presentations:

Gas Plant Comparative Recovery Model
Michael Morgan, Turing Analytics

ShadowOps: Modular Design, Simple Logic, Real Operational Value
Monica Brookwell, Birchcliff Energy

Compliance Application Development at Heritage
Megan Hyland,  Heritage Royalty

Session Chairs: Monica Brookwell, Birchcliff Energy; Hayden Fiege, Databricks; Thomas Zhao, EVA by Turing Analytics

This session brings together data and technology leaders from a range of operating companies to share how they are shaping and evolving their data and AI strategies. Panelists will discuss how their organizations are moving beyond experimentation to scale data and AI capabilities in a way that delivers measurable business value. The conversation will focus on practical approaches, lessons learned, and key enablers such as governance, culture, and operating models that help turn data and AI investments into real impact.

Moderator:
Brian Emmerson, Director, AI & Data, Industrials & Energy, EY

Panelists:

Brad Affleck, Manager, Measurement, Analytics & Technology, Strathcona Resources

Wendy Cook, Manager, Enterprise Data and Analytics, Canadian Natural

Mark Derry, Manager, Data and Analytics, ARC Resource

Mike Michonski, Manager, Upstream Digital, Imperial