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Data analytics for drilling engineer...

Xue, Qilong.

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Data analytics for drilling engineering = theory, algorithms, experiments, software /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Data analytics for drilling engineering/ by Qilong Xue.
其他題名:	theory, algorithms, experiments, software /
作者:	Xue, Qilong.
出版者:	Cham :Springer international Publishing : : 2020.,
面頁冊數:	xiii, 312 p. :ill., digital ;24 cm.
內容註:	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.
Contained By:	Springer eBooks
標題:	Oil well drilling - Data processing. -
電子資源:	https://doi.org/10.1007/978-3-030-34035-3
ISBN:	9783030340353

Data analytics for drilling engineering = theory, algorithms, experiments, software /
Xue, Qilong.

Data analytics for drilling engineeringtheory, 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

Standard No.: 10.1007/978-3-030-34035-3doiSubjects--Topical Terms:

3446302
Oil well drilling
--Data processing.

LC Class. No.: TN871 / .X847 2020

Dewey Class. No.: 622.33810285

Data analytics for drilling engineering = theory, algorithms, experiments, software /
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505 0 $a 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.
520 $a 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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