Driving Digitalization with Energy Forecasting: A Case Study from Hawiyah Gas Plant

In a sector where energy efficiency directly impacts cost and sustainability, traditional forecasting methods are no longer enough. At our upcoming conference, Khalid S. Babtain, Operations Unit Head at Aramco, will present a transformative case study from the Hawiyah Gas Plant, showcasing how machine learning is reshaping energy forecasting in oil and gas facilities. 

Khalid brings over six years of hands-on expertise in gas operations, including dehydration, compression, and hydrocarbon stabilization. A Certified Energy Manager (CEM) and ISO-certified lead assessor, Khalid has earned international recognition, including the Young Energy Professional of the Year Award by AEE for the Middle East Region. 

His session will explore the shift from outdated Excel-based linear regression models to advanced machine learning-powered Energy Demand Forecasting Solutions. These digital tools are engineered to navigate the complex, ever-changing environment of oil and gas processing. The results? Reduced energy consumption, enhanced cost-efficiency, and better environmental outcomes. 

Through a detailed case study of the Hawiyah Gas Plant, Khalid will walk attendees through the implementation process, showcasing how this solution bridges the gap between conceptual engineering and practical, digital innovation.