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Data analytics for drilling engineer...
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Data analytics for drilling engineeringtheory, algorithms, experiments, software /
Record Type:
Electronic resources : Monograph/item
Title/Author:
Data analytics for drilling engineeringby Qilong Xue.
Reminder of title:
theory, algorithms, experiments, software /
Author:
Xue, Qilong.
Published:
Cham :Springer international Publishing :2020.
Description:
xiii, 312 p. :ill., digital ;24 cm.
Contained By:
Springer eBooks
Subject:
Oil well drillingData processing.
Online resource:
https://doi.org/10.1007/978-3-030-34035-3
ISBN:
9783030340353$q(electronic bk.)
Data analytics for drilling engineeringtheory, algorithms, experiments, software /
Xue, Qilong.
Data analytics for drilling engineering
theory, algorithms, experiments, software /[electronic resource] :by Qilong Xue. - Cham :Springer international Publishing :2020. - xiii, 312 p. :ill., digital ;24 cm. - information fusion and data science,2510-1528. - information fusion and data science..
introduction to the Application of Drilling Data Processing -- Signal Processing of Downhole information Transmission -- Dynamic Measurement of Spatial Attitude at the Bottom Rotating DrillString -- Measurement and Analysis of Drillstring Dynamics -- Signal processing in logging while drilling -- Data Mining in Seismic While Drilling -- Applications of Big Data in Drilling Engineering -- Summary and Outlook.
This book presents the signal processing and data mining challenges encountered in drilling engineering, and describes the methods used to overcome them. in drilling engineering, many signal processing technologies are required to solve practical problems, such as downhole information transmission, spatial attitude of drillstring, drillstring dynamics, seismic activity while drilling, among others. This title attempts to bridge the gap between the signal processing and data mining and oil and gas drilling engineering communities. There is an urgent need to summarize signal processing and data mining issues in drilling engineering so that practitioners in these fields can understand each other in order to enhance oil and gas drilling functions. in summary, this book shows the importance of signal processing and data mining to researchers and professional drilling engineers and open up a new area of application for signal processing and data mining scientists.
ISBN: 9783030340353$q(electronic bk.)
Standard No.: 10.1007/978-3-030-34035-3doiSubjects--Topical Terms:
863782
Oil well drilling
--Data processing.
LC Class. No.: TN871 / .X847 2020
Dewey Class. No.: 622.33810285
Data analytics for drilling engineeringtheory, algorithms, experiments, software /
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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.
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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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Engineering (Springer-11647)
based on 0 review(s)
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電子館藏
Items
1 records • Pages 1 •
1
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電子館藏
1圖書
電子書
EB TN871 .X8 2020 2020
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1 records • Pages 1 •
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https://doi.org/10.1007/978-3-030-34035-3
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