What you will learn:
- 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?
Each of these topics includes one or more examples and simple exercises to illustrate a principle where appropriate.
- Supervised and Unsupervised Learning
- MLP; CNN; FCN; k-means; SOM
- Attribute space classification
- Seismic Processing for Machine Learning
- Attribute Selection List Objectives
- Principal Component Analysis (PCA)
- Geobody Classification
- Fluid Contacts
- Geobody Seismic Facies
- Making Predictions
- The Best Well
- The Best Seismic Processing
- Who Makes the Best Predictions?
*Note: Publication image quality is available upon request, please contact [email protected] for additional information.
Click on a unit below to view lessons
- Machine Learning Operation
- Machine Learning Foundation
- Machine Learning Practice
- Machine Learning Prediction