Overview
- Provides a new perspective on challenges in data processing in drilling engineering
- Contains numerous mathematical models of data processing
- Facilitates communication and understanding among drilling practitioners
Part of the book series: Information Fusion and Data Science (IFDS)
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Table of contents (8 chapters)
Keywords
About this book
Authors and Affiliations
Bibliographic Information
Book Title: Data Analytics for Drilling Engineering
Book Subtitle: Theory, Algorithms, Experiments, Software
Authors: Qilong Xue
Series Title: Information Fusion and Data Science
DOI: https://doi.org/10.1007/978-3-030-34035-3
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer Nature Switzerland AG 2020
Hardcover ISBN: 978-3-030-34034-6Published: 31 December 2019
Softcover ISBN: 978-3-030-34037-7Published: 31 December 2020
eBook ISBN: 978-3-030-34035-3Published: 30 December 2019
Series ISSN: 2510-1528
Series E-ISSN: 2510-1536
Edition Number: 1
Number of Pages: XIII, 312
Number of Illustrations: 48 b/w illustrations, 101 illustrations in colour
Topics: Geoengineering, Foundations, Hydraulics, Geotechnical Engineering & Applied Earth Sciences, Data-driven Science, Modeling and Theory Building, Signal, Image and Speech Processing, Vibration, Dynamical Systems, Control