Overview
Explore unsupervised learning and advanced topics in machine learning applied to petroleum engineering, energy transition, geology, and petrophysics in this fourth lecture of PioPetro's 2024 Summer Training series. Delve into the fundamentals of unsupervised learning, discover essential tools for implementation, and learn about model employment and monitoring. Examine ethical considerations in machine learning applications within the energy sector, and gain practical insights through a real-world example. Conclude with key takeaways to enhance your understanding of advanced machine learning techniques in the context of energy and geological sciences.
Syllabus
Introduction
Unsupervised learning
Tools for unsupervised learning
Model employment and monitoring
Ethical considerations
Example
Takeaways
Taught by
PioPetro