Python for Petroleum Data Analytics
This workshop introduces the application of Python in petroleum data analytics, focusing on practical techniques for handling, analyzing, and visualizing complex datasets common in oil and gas operations. Participants will gain hands-on experience with tools that support faster decision-making, improved forecasting, and enhanced operational efficiency.
Workshop Objectives
• Apply Python libraries for data cleaning, analysis, and visualization in petroleum contexts.
• Develop workflows for interpreting production, reservoir, and operational datasets.
• Strengthen predictive analysis and modeling skills to support technical and business decisions.
• Enhance data-driven approaches for efficiency, safety, and cost optimization.
About the Presenter
The workshop is conducted by a seasoned industry with experience in petroleum engineering, data science, and applied analytics. The presenter combines technical with practical insights, equipping professionals to integrate Python-based solutions into 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.