Wireline and LWD Log Quality Control and its Impact on Interpretation
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This workshop provides an in-depth understanding of wireline and LWD log quality control and its critical role in accurate formation evaluation. Participants will learn how to identify, assess, and correct data quality issues that directly influence interpretation reliability and reservoir characterization.
Workshop Objectives
• Understand key principles of wireline and LWD log quality control.
• Identify common sources of logging errors and their impact on data interpretation.
• Learn practical methods for validating and correcting log data.
• Evaluate how quality control affects formation evaluation and reservoir assessment.
About the Presenter
The workshop is conducted by a professional with experience in well logging, petrophysical interpretation, and reservoir evaluation. The presenter has a proven background in applying quality control practices to ensure accurate and reliable subsurface data analysis across various operational environments.
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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.