Machine Learning for Drilling Engineering with Python
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For PEA Members Only
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.
Workshop Objectives
Load, clean, and explore drilling data in Python
Build prediction models for rate of penetration (ROP)
Detect and flag drilling problems early (stuck pipe, kicks, vibration)
Use real-time data to support drilling decisions
Read model results and know when to trust them
Take the code back to your team and put it to work
About the Presenter
The workshop is conducted by an experienced industry professional with a strong background in reservoir engineering, drilling operations, and well integrity. The presenter shares practical insights and field-based approaches to help participants apply geomechanical principles effectively.
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For PEA Members Only
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