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Machine Learning Applications in Subsurface Energy Resource Management
- Binding:
- Hardback
- Pages:
- 360
- Published:
- December 27, 2022
- Dimensions:
- 158x25x235 mm.
- Weight:
- 642 g.
Delivery:
2-3 weeks
Expected delivery: July 14, 2024
Description of Machine Learning Applications in Subsurface Energy Resource Management
Machine Learning Applications in Subsurface Energy Resource Management presents a current snapshot of the state of the art and future outlook for machine learning applications in subsurface energy resource management (e.g., oil and gas, geologic carbon sequestration, geothermal energy).
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