Deep Learning for Seismic Analysis
This webinar explores how deep learning techniques are revolutionizing seismic data interpretation in oil and gas. Participants will learn how advanced neural networks improve accuracy in fault detection, reservoir characterization, and subsurface imaging, enabling faster and more reliable decision-making.
Webinar Objectives
• Introduce the fundamentals of deep learning in seismic workflows.
• Demonstrate applications in fault detection, facies classification, and imaging.
• Highlight advantages over traditional seismic interpretation methods.
• Discuss challenges, data requirements, and integration into existing geophysical processes.
About the Presenter
The session is led by a domain expert with extensive experience in geophysics and machine learning. The presenter combines practical seismic knowledge with advanced data science expertise to help participants understand both the technical and applied aspects of deep learning in seismic analysis.
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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.