Machine learning and data science in the oil and gas industry : best practices, tools, and case studies

Machine Learning and Data Science in the Oil and Gas Industry explains how machine learning can be specifically tailored to oil and gas use cases. Petroleum engineers will learn when to use machine learning, how it is already used in oil and gas operations, and how to manage the data stream moving f...

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Bibliographic Details
Other Authors: Bangert, Patrick.
Format: eBook
Language: English
Published: Cambridge, MA : Gulf Professional, 2021.
Subjects:
Petroleum industry and trade > Data processing.
Machine learning.
elektronické knihy
electronic books
ISBN: 9780128209141
0128209143
9780128207147
0128207140
Physical Description: 1 online resource

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Table of contents

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001 kn-on1240670836
003 OCoLC
005 20240717213016.0
006 m o d
007 cr cn|||||||||
008 210307s2021 mau o 000 0 eng d
040 |a YDX  |b eng  |e pn  |c YDX  |d OPELS  |d N$T  |d OCLCF  |d OCLCO  |d OCLCQ  |d OCLCO  |d ORMDA  |d K6U  |d OCLCQ  |d OCLCO  |d OCLCL  |d SXB 
020 |a 9780128209141  |q (electronic bk.) 
020 |a 0128209143  |q (electronic bk.) 
020 |z 9780128207147 
020 |z 0128207140 
035 |a (OCoLC)1240670836 
245 0 0 |a Machine learning and data science in the oil and gas industry :  |b best practices, tools, and case studies /  |c edited by Patrick Bangert. 
260 |a Cambridge, MA :  |b Gulf Professional,  |c 2021. 
300 |a 1 online resource 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
506 |a Plný text je dostupný pouze z IP adres počítačů Univerzity Tomáše Bati ve Zlíně nebo vzdáleným přístupem pro zaměstnance a studenty 
520 |a Machine Learning and Data Science in the Oil and Gas Industry explains how machine learning can be specifically tailored to oil and gas use cases. Petroleum engineers will learn when to use machine learning, how it is already used in oil and gas operations, and how to manage the data stream moving forward. Practical in its approach, the book explains all aspects of a data science or machine learning project, including the managerial parts of it that are so often the cause for failure. Several real-life case studies round out the book with topics such as predictive maintenance, soft sensing, and forecasting. Viewed as a guide book, this manual will lead a practitioner through the journey of a data science project in the oil and gas industry circumventing the pitfalls and articulating the business value. Chart an overview of the techniques and tools of machine learning including all the non-technological aspects necessary to be successful Gain practical understanding of machine learning used in oil and gas operations through contributed case studies Learn change management skills that will help gain confidence in pursuing the technology Understand the workflow of a full-scale project and where machine learning benefits (and where it does not). 
590 |a Knovel  |b Knovel (All titles) 
650 0 |a Petroleum industry and trade  |x Data processing. 
650 0 |a Machine learning. 
655 7 |a elektronické knihy  |7 fd186907  |2 czenas 
655 9 |a electronic books  |2 eczenas 
700 1 |a Bangert, Patrick. 
776 0 8 |i Print version:  |z 0128207140  |z 9780128207147  |w (OCoLC)1158482535 
856 4 0 |u https://proxy.k.utb.cz/login?url=https://app.knovel.com/hotlink/toc/id:kpMLDSOGI2/machine-learning-and?kpromoter=marc  |y Full text 

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