Subsurface Machine Learning
Explore fundamental probability and statistics; inference and prediction; and model training, testing, tuning, and validation. Examine workflows for integrating many features; workflows for anomaly detection, spatiotemporal prediction, and uncertainty integration. Communicate results within a project team to impact subsurface decision making. Petroleum and Geosystems Engineering 379 (Topic: Subsurface Machine Learning) and 379 (Topic 9) may not both be counted. Three lecture hours a week for one semester.
Prerequisites & course information
Explore fundamental probability and statistics; inference and prediction; and model training, testing, tuning, and validation. Examine workflows for integrating many features; workflows for anomaly detection, spatiotemporal prediction, and uncertainty integration. Communicate results within a project team to impact subsurface decision making. Petroleum and Geosystems Engineering 379 (Topic: Subsurface Machine Learning) and 379 (Topic 9) may not both be counted. Three lecture hours a week for one semester.
Sources
- Course catalogue ↗2026-2027