Téléchargez le livre : A Primer on Machine Learning in Subsurface Geosciences

A Primer on Machine Learning in Subsurface Geosciences

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Éditeur :

Springer


Collection :

SpringerBriefs in Petroleum Geoscience & Engineering

Paru le : 2021-05-03

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Description

This book provides readers with a timely review and discussion of the success, promise, and perils of machine learning in geosciences. It explores the fundamentals of data science and machine learning, and how their advances have disrupted the traditional workflows used in the industry and academia, including geology, geophysics, petrophysics, geomechanics, and geochemistry. It then presents the real-world applications and explains that, while this disruption has affected the top-level executives, geoscientists as well as field operators in the industry and academia, machine learning will ultimately benefit these users. The book is written by a practitioner of machine learning and statistics, keeping geoscientists in mind. It highlights the need to go beyond concepts covered in STAT 101 courses and embrace new computational tools to solve complex problems in geosciences. It also offers practitioners, researchers, and academics insights into how to identify, develop, deploy, and recommend fit-for-purpose machine learning models to solve real-world problems in subsurface geosciences. 
Pages
172 pages
Collection
SpringerBriefs in Petroleum Geoscience & Engineering
Parution
2021-05-03
Marque
Springer
EAN papier
9783030717674
EAN PDF
9783030717681
Informations sur l'ebook
Nombre pages copiables
1
Nombre pages imprimables
17
Taille du fichier
12329 Ko
Prix
68,56 €
EAN EPUB
9783030717681
Informations sur l'ebook
Nombre pages copiables
1
Nombre pages imprimables
17
Taille du fichier
62956 Ko
Prix
68,56 €

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