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Data Analytics for Drilling Engineering - Theory, Algorithms, Experiments, Software (Hardcover, 1st ed. 2020): Qilong Xue Data Analytics for Drilling Engineering - Theory, Algorithms, Experiments, Software (Hardcover, 1st ed. 2020)
Qilong Xue
R4,988 Discovery Miles 49 880 Ships in 10 - 15 working days

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.

Data Analytics for Drilling Engineering - Theory, Algorithms, Experiments, Software (Paperback, 1st ed. 2020): Qilong Xue Data Analytics for Drilling Engineering - Theory, Algorithms, Experiments, Software (Paperback, 1st ed. 2020)
Qilong Xue
R4,958 Discovery Miles 49 580 Ships in 10 - 15 working days

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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