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Data Analytics for Drilling Engineering : Theory, Algorithms, Experiments, Software / by Qilong Xue.

By: Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: Information Fusion and Data Science | Springer eBook CollectionPublisher: Cham : Springer International Publishing, 2020Publisher: Cham : Imprint: Springer, 2020Edition: 1st ed. 2020Description: 1 Online-Ressource(XIII, 312 p. 149 illus., 101 illus. in color.)ISBN:
  • 9783030340353
Subject(s): Additional physical formats: 9783030340346 | 9783030340360 | 9783030340377 | Erscheint auch als: 9783030340346 Druck-Ausgabe | Erscheint auch als: 9783030340360 Druck-Ausgabe | Erscheint auch als: 9783030340377 Druck-AusgabeDOI: DOI: 10.1007/978-3-030-34035-3Online resources: Summary: Introduction to the Application of Drilling Data Processing -- Signal Processing of Downhole Information Transmission -- Dynamic Measurement of Spatial Attitude at the Bottom Rotating DrillString -- Measurement and Analysis of Drillstring Dynamics -- Signal processing in logging while drilling -- Data Mining in Seismic While Drilling -- Applications of Big Data in Drilling Engineering -- Summary and Outlook.Summary: 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.PPN: PPN: 1686643268Package identifier: Produktsigel: ZDB-2-ENG | ZDB-2-SEB | ZDB-2-SXE
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