Machine Learning Applications in Subsurface Energy Resource Management (ePub)
State of the Art and Future Prognosis
(Sprache: Englisch)
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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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).
Autoren-Porträt
Dr. Srikanta Mishra is Senior Research Leader and Technical Director for Geo-energy Resource Modeling and Analytics at Battelle Memorial Institute, the world's largest independent contract R&D organization. He is nationally and internationally recognized for his expertise in developing and communicating physics-based and data-driven predictive models for subsurface resource management. Dr. Mishra currently serves as the Technical Lead of the SMART (Science Informed Machine Learning for Accelerating Real-time Decisions for Subsurface applications) initiative, organized by the US Department of Energy and involving multiple national laboratories and universities. He was a recipient of the Society of Petroleum Engineers (SPE) Distinguished Member Award in 2021, and also served as a Global Distinguished Lecturer on Big Data Analytics for SPE during 2018-19 and received the 2022 SPE Data Science and Engineering Analytics Award.
Bibliographische Angaben
- 2022, 1. Auflage, 378 Seiten, Englisch
- Herausgegeben: Srikanta Mishra
- Verlag: Taylor & Francis
- ISBN-10: 100082389X
- ISBN-13: 9781000823899
- Erscheinungsdatum: 27.12.2022
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eBook Informationen
- Dateiformat: ePub
- Grösse: 10 MB
- Ohne Kopierschutz
- Vorlesefunktion
Sprache:
Englisch
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