Applied Machine Learning for Reservoir & Production Engineering
This workshop introduces machine learning techniques applied specifically to reservoir and production engineering challenges. Attendees will learn how to build predictive models, analyze complex datasets, and optimize reservoir performance using data-driven algorithms. The course combines theoretical concepts with practical exercises to demonstrate ML applications in well performance forecasting and reservoir characterization.
Workshop Objectives
To enable participants to apply machine learning methods for improved reservoir management and production forecasting, enhancing their ability to extract actionable insights from engineering data and optimize field development strategies.
About the Presenter
Nashat Jumaah Omar - 12+Years of Experience In Oil & Gas Industry
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.