Data Science for Petroleum Geoscientists
This session introduces the application of data science in petroleum geoscience, highlighting how advanced analytics and machine learning support exploration and reservoir evaluation. Participants will gain insights into integrating geoscience data with modern computational tools to improve interpretation, reduce uncertainty, and accelerate decision-making.
Webinar Objectives
• Understand the role of data science in exploration and reservoir characterization.
• Review key techniques such as machine learning, pattern recognition, and predictive analytics.
• Examine workflows for integrating geological, geophysical, and petrophysical data.
• Explore practical examples of data-driven approaches in petroleum geoscience.
About the Presenter
The presenter is a skilled professional in geoscience and applied data analytics. Their experience spans both subsurface evaluation and digital technologies, providing a balanced perspective on combining domain knowledge with advanced computational methods for improved outcomes.
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Time : 9 PM Indian Time | Duration : 90 Minutes
Python for PTA: Type curves creation
This webinar equips petroleum engineers with practical Python skills to generate Gringarten type curves for Pressure Transient Analysis (PTA), transforming theoretical reservoir concepts into actionable code. Participants will review the diffusivity equation, explore its analytical solutions, master dimensionless parameters, and implement Python scripts for log-log type curve plotting—essential for estimating permeability, skin factor, and reservoir boundaries from well test data.Ideal for reservoir and production engineers seeking data-driven PTA workflows, the session leverages NumPy, Matplotlib, and hydraulic modeling principles to analyze performance data efficiently. Attendees leave with reusable code templates and real-world applications from field operations.