Machine learning is foundational to the digital transformation of the oil & gas industry and will have a dramatic impact on the exploration and production of hydrocarbons. Dr. Tom Smith, the founder and CEO of Geophysical Insights, conducts a comprehensive survey of machine learning technology and its applications in this 24-part series. The course will benefit geoscientists, engineers, and data analysts at all experience levels, from data analysts who want to better understand applications of machine learning to geoscience, to senior geophysicists with deep experience in the field.
Aspects of supervised learning, unsupervised learning, classification and reclassification are introduced to illustrate how they work on seismic data. Machine learning is presented, not as an end-all-be-all, but as a new set of tools which enables interpretation on seismic data on a new, higher level that of abstraction that promises to reduce risks and identify features that which might otherwise be missed.
The following major topics are covered:
- Operation – supervised and unsupervised learning; buzzwords; examples
- Foundation – seismic processing for ML; attribute selection list objectives; principal component analysis
- Practice – geobodies; below-tuning; fluid contacts; making predictions
- Prediction – the best well; the best seismic processing; over-fitting; cross-validation; who makes the best predictions?
This course can be taken for certification, or for informational purposes only (without certification).
Enroll today for this valuable e-course from Geophysical Insights!
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