Machine learning guide for oil and gas using Python : a step-by-step breakdown with data, algorithms, codes, and applications

Machine Learning Guide for Oil and Gas Using Python: A Step-by-Step Breakdown with Data, Algorithms, Codes, and Applications delivers a critical training and resource tool to help engineers understand machine learning theory and practice, specifically referencing use cases in oil and gas. The refere...

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Bibliographic Details
Main Authors: Belyadi, Hoss, (Author), Haghighat, Alireza, (Author)
Format: eBook
Language: English
Published: Cambridge, MA : Gulf Professional Publishing, 2021.
Subjects:
Petroleum engineering > Data processing.
Natural gas > Data processing.
Machine learning.
elektronické knihy
electronic books
ISBN: 9780128219300
0128219300
9780128219294
0128219297
Physical Description: 1 online resource

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Table of contents

LEADER 02976cam a2200397 i 4500
001 kn-on1246283594
003 OCoLC
005 20240717213016.0
006 m o d
007 cr cn|||||||||
008 210416s2021 mau ob 001 0 eng d
040 |a YDX  |b eng  |e rda  |e pn  |c YDX  |d OPELS  |d OCLCO  |d OCLCF  |d GZM  |d UAB  |d OPELS  |d N$T  |d UND  |d OCLCQ  |d OCLCO  |d ORMDA  |d K6U  |d OCLCQ  |d OCLCO  |d OCLCL  |d SXB 
020 |a 9780128219300  |q (electronic bk.) 
020 |a 0128219300  |q (electronic bk.) 
020 |a 9780128219294  |q (electronic bk.) 
020 |a 0128219297  |q (electronic bk.) 
035 |a (OCoLC)1246283594  |z (OCoLC)1246142343  |z (OCoLC)1249100538 
100 1 |a Belyadi, Hoss,  |e author. 
245 1 0 |a Machine learning guide for oil and gas using Python :  |b a step-by-step breakdown with data, algorithms, codes, and applications /  |c Hoss Belyadi, Alireza Haghighat. 
264 1 |a Cambridge, MA :  |b Gulf Professional Publishing,  |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 
504 |a Includes bibliographical references and index. 
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 Guide for Oil and Gas Using Python: A Step-by-Step Breakdown with Data, Algorithms, Codes, and Applications delivers a critical training and resource tool to help engineers understand machine learning theory and practice, specifically referencing use cases in oil and gas. The reference moves from explaining how Python works to step-by-step examples of utilization in various oil and gas scenarios, such as well testing, shale reservoirs and production optimization. Petroleum engineers are quickly applying machine learning techniques to their data challenges, but there is a lack of references beyond the math or heavy theory of machine learning. Machine Learning Guide for Oil and Gas Using Python details the open-source tool Python by explaining how it works at an introductory level then bridging into how to apply the algorithms into different oil and gas scenarios. While similar resources are often too mathematical, this book balances theory with applications, including use cases that help solve different oil and gas data challenges. 
590 |a Knovel  |b Knovel (All titles) 
650 0 |a Petroleum engineering  |x Data processing. 
650 0 |a Natural gas  |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 Haghighat, Alireza,  |e author. 
776 0 8 |i Print version:  |a Belyadi, Hoss.  |t Machine learning guide for oil and gas using Python  |z 0128219297  |z 9780128219294  |w (OCoLC)1195448296 
856 4 0 |u https://proxy.k.utb.cz/login?url=https://app.knovel.com/hotlink/toc/id:kpMLGOGUP4/machine-learning-guide?kpromoter=marc  |y Full text 

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