Data Analytics for Drilling Engineering
Theory, Algorithms, Experiments, Software
Authors: Xue, Qilong
- 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
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- About this book
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This book presents the signal processing and data mining challenges encountered in drilling engineering, and describes the methods used to overcome them. In drilling engineering, many signal processing technologies are required to solve practical problems, such as downhole information transmission, spatial attitude of drillstring, drillstring dynamics, seismic activity while drilling, among others. This title attempts to bridge the gap between the signal processing and data mining and oil and gas drilling engineering communities. There is an urgent need to summarize signal processing and data mining issues in drilling engineering so that practitioners in these fields can understand each other in order to enhance oil and gas drilling functions. In summary, this book shows the importance of signal processing and data mining to researchers and professional drilling engineers and open up a new area of application for signal processing and data mining scientists.
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Bibliographic Information
- Bibliographic Information
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- Book Title
- Data Analytics for Drilling Engineering
- Book Subtitle
- Theory, Algorithms, Experiments, Software
- Authors
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- Qilong Xue
- Series Title
- Information Fusion and Data Science
- Copyright
- 2020
- Publisher
- Springer International Publishing
- Copyright Holder
- Springer Nature Switzerland AG
- eBook ISBN
- 978-3-030-34035-3
- DOI
- 10.1007/978-3-030-34035-3
- Hardcover ISBN
- 978-3-030-34034-6
- Series ISSN
- 2510-1528
- Edition Number
- 1
- Number of Pages
- XIII, 312
- Number of Illustrations
- 48 b/w illustrations, 101 illustrations in colour
- Topics
