TY  - BOOK
AU  - Belyadi,Hoss
AU  - Haghighat,Alireza
ED  - Ohio Library and Information Network
TI  - Machine learning guide for oil and gas using Python: a step-by-step breakdown with data, algorithms, codes, and applications 
SN  - 9780128219300
AV  - TN871 BEL 
U1  - 622.3380285631 23
PY  - 2021///
CY  - Cambridge, MA
PB  - Gulf Professional Publishing
KW  - Petroleum engineering
KW  - Data processing
KW  - Natural gas
KW  - Machine learning
KW  - Electronic books
N1  - Includes bibliographical references and index; Available to OhioLINK libraries
N2  - 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
UR  - https://learning.oreilly.com/library/view/~/9780128219300/?ar
ER  -