Electronic Resource

A Primer on Machine Learning in Subsurface Geosciences

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Penilaian

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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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Availability

Inventory Code	Barcode	Call Number	Location	Status
2108000007	EB0005258	561	Central Library (OPAC)	Available

Detail Information

Series Title

-

Call Number

561

Publisher

Switzerland : Springer Cham., 2021

Collation

xvii, 172p.:ill

Language

English

ISBN/ISSN

978-3-030-71768-1

Classification

561

Content Type

Ebook

Media Type

-

Carrier Type

online resource

Edition

1

Subject(s)

Fossil

Specific Detail Info

-

Statement of Responsibility

BRF

Other version/related

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