Data Science & Machine Learning for Petroleum Engineers and Geoscientists
This workshop equips petroleum engineers and geoscientists with practical knowledge of data science and machine learning applications in the energy sector. Through industry-relevant examples, participants will learn how advanced analytics can be applied to reservoir characterization, production optimization, and operational forecasting.
Workshop Objectives
• Understand core data science and machine learning concepts relevant to petroleum applications.
• Apply statistical and computational techniques to subsurface and production data.
• Build predictive models to support exploration, reservoir management, and operational decision-making.
• Enhance technical workflows by integrating modern data-driven approaches with traditional engineering and geoscience practices.
About the Presenter
Led by a professional in petroleum engineering, geoscience, and data analytics, the workshop bridges technical depth with practical application. The presenter draws on years of industry experience to guide participants in applying data science and machine learning tools to real-world oil and gas challenges.
Applied Machine Learning for Upstream and Subsurface Domains
This two-day hands-on workshop is designed for petroleum and subsurface professionals seeking practical skills in machine learning for upstream oil & gas operations. The program teaches participants how to apply machine learning to uncover patterns in production and reservoir data, discover equations from historical relationships, and build predictive models for vital engineering parameters. Real-world datasets from drilling and subsurface domains are used, focusing on automating reports, visualizing data, and interpreting model outputs for improved decision-making.