Naturally Fractured Reservoirs
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This workshop provides an in-depth understanding of the characterization, evaluation, and management of naturally fractured reservoirs. Participants will explore fracture systems, their impact on reservoir behaviour, and strategies for maximizing hydrocarbon recovery in complex fractured settings.
Workshop Objectives
• Understand the nature and classification of naturally fractured reservoirs.
• Apply methods for fracture characterization and modeling.
• Assess the impact of fractures on fluid flow and reservoir performance.
• Evaluate production challenges and recovery strategies.
• Integrate geological, geophysical, and engineering data for reservoir management.
About the Presenter
The workshop is led by an experienced reservoir with a strong background in fractured reservoir analysis and field development. Combining technical with practical case knowledge, the presenter delivers actionable insights and best practices to support effective reservoir evaluation and management.
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Machine Learning for Drilling Engineering with Python
Drilling generates huge amounts of data — but most of it sits unused. This hands-on workshop shows you how to turn that data into better decisions using Python and machine learning.Over the sessions, you'll work with real drilling datasets to build models that predict problems before they happen — stuck pipe, ROP optimization, bit wear, formation changes, and more. No heavy math theory. You write code, run it on actual data, and see the results.By the end, you'll have working Python scripts you can adapt to your own field data, plus a clear understanding of where ML adds value in drilling and where it doesn't.Built for drilling engineers, not data scientists. If you can read a drilling report, you can follow this course.