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A Primer on Machine Learning in Subsurface Geosciences

Af: Shuvajit Bhattacharya Engelsk Paperback

A Primer on Machine Learning in Subsurface Geosciences

Af: Shuvajit Bhattacharya Engelsk Paperback
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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. 

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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. 

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Produktdetaljer
Sprog: Engelsk
Sider: 172
ISBN-13: 9783030717674
Indbinding: Paperback
Udgave:
ISBN-10: 3030717674
Kategori: Geologi, geomorfologi og lithosfæren
Udg. Dato: 4 maj 2021
Længde: 0mm
Bredde: 155mm
Højde: 235mm
Forlag: Springer Nature Switzerland AG
Oplagsdato: 4 maj 2021
Forfatter(e): Shuvajit Bhattacharya
Forfatter(e) Shuvajit Bhattacharya

Kategori Geologi, geomorfologi og lithosfæren

ISBN-13 9783030717674

Sprog Engelsk

Indbinding Paperback

Sider 172

Udgave

Længde 0mm

Bredde 155mm

Højde 235mm

Udg. Dato 4 maj 2021

Oplagsdato 4 maj 2021

Forlag Springer Nature Switzerland AG