UID:
almahu_9949300065602882
Umfang:
1 online resource (378 pages)
ISBN:
0-12-822308-1
Inhalt:
Advances in Subsurface Data Analytics: Traditional and Physics-Based Approaches brings together the fundamentals of popular and emerging machine learning (ML) algorithms with their applications in subsurface analysis, including geology, geophysics, petrophysics, and reservoir engineering. The book is divided into four parts: traditional ML, deep learning, physics-based ML, and new directions, with an increasing level of diversity and complexity of topics. Each chapter focuses on one ML algorithm with a detailed workflow for a specific application in geosciences. Some chapters also compare the results from an algorithm with others to better equip the readers with different strategies to implement automated workflows for subsurface analysis.
Anmerkung:
Includes index.
Weitere Ausg.:
Print version: Bhattacharya, Shuvajit Advances in Subsurface Data Analytics San Diego : Elsevier,c2022 ISBN 9780128222959
Weitere Ausg.:
ISBN 9780128222959
Weitere Ausg.:
Print version: ISBN 0128222956
Weitere Ausg.:
ISBN 9780128222959
Weitere Ausg.:
Print version: Advances in subsurface data analytics ISBN 9780128222959
Sprache:
Englisch
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