Tuesday, March 25, 2025

15:55 - 17:35

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Details

Forecasting well production and other key variables in reservoir engineering is a cornerstone of field development and optimization, applicable in Oil & Gas as well as in emerging subsurface industries like Geothermal. Over recent decades, the demand for increased efficiency in this process, coupled with the rise of digital twins for high-frequency operation monitoring, has spurred the adoption of data-driven and statistical methods alongside traditional physics-based simulators. In this context, a range of Machine Learning techniques has shown great promise in providing computationally effective yet precise predictions of near-future production values. This session will convene international experts from academia, startups, and energy companies to discuss new advancements and practical case studies in this rapidly evolving field. Topics of discussion may include the benefits of emerging neural architectures, the integration of physical and statistical methods in hybrid models, and common challenges such as data integration, model validation, and the implementation of recent technologies in history matching and operational workflows. Join us for insightful discussions at the intersection of engineering, physics, subsurface modeling, and data science!