Read Machine Learning Applications in Subsurface Energy Resource Management: State of the Art and Future Prognosis

Machine Learning Applications in Subsurface Energy Resource Management: State of the Art and Future Prognosis

Srikanta Mishra

4.9/5 (23913 ratings)

Description:The utilization of machine learning (ML) techniques to understand hidden patterns and build data-driven predictive models from complex multivariate datasets is rapidly increasing in many applied science and engineering disciplines, including geo-energy. Motivated by these developments, Machine Learning Applications in Subsurface Energy Resource Management presents a current snapshot of the state of the art and future outlook for ML applications to manage subsurface energy resources (e.g., oil and gas, geologic carbon sequestration, and geothermal energy).Covers ML applications across multiple application domains (reservoir characterization, drilling, production, reservoir modeling, and predictive maintenance)Offers a variety of perspectives from authors representing operating companies, universities, and research organizationsProvides an array of case studies illustrating the latest applications of several ML techniquesIncludes a literature review and future outlook for each application domainThis book is targeted at practicing petroleum engineers or geoscientists interested in developing a broad understanding of ML applications across several subsurface domains. It is also aimed as a supplementary reading for graduate-level courses and will also appeal to professionals and researchers working with hydrogeology and nuclear waste disposal.We have made it easy for you to find a PDF Ebooks without any digging. And by having access to our ebooks online or by storing it on your computer, you have convenient answers with Machine Learning Applications in Subsurface Energy Resource Management: State of the Art and Future Prognosis. To get started finding Machine Learning Applications in Subsurface Energy Resource Management: State of the Art and Future Prognosis, you are right to find our website which has a comprehensive collection of manuals listed.
Our library is the biggest of these that have literally hundreds of thousands of different products represented.

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ISBN: 1000823873

Description: The utilization of machine learning (ML) techniques to understand hidden patterns and build data-driven predictive models from complex multivariate datasets is rapidly increasing in many applied science and engineering disciplines, including geo-energy. Motivated by these developments, Machine Learning Applications in Subsurface Energy Resource Management presents a current snapshot of the state of the art and future outlook for ML applications to manage subsurface energy resources (e.g., oil and gas, geologic carbon sequestration, and geothermal energy).Covers ML applications across multiple application domains (reservoir characterization, drilling, production, reservoir modeling, and predictive maintenance)Offers a variety of perspectives from authors representing operating companies, universities, and research organizationsProvides an array of case studies illustrating the latest applications of several ML techniquesIncludes a literature review and future outlook for each application domainThis book is targeted at practicing petroleum engineers or geoscientists interested in developing a broad understanding of ML applications across several subsurface domains. It is also aimed as a supplementary reading for graduate-level courses and will also appeal to professionals and researchers working with hydrogeology and nuclear waste disposal.We have made it easy for you to find a PDF Ebooks without any digging. And by having access to our ebooks online or by storing it on your computer, you have convenient answers with Machine Learning Applications in Subsurface Energy Resource Management: State of the Art and Future Prognosis. To get started finding Machine Learning Applications in Subsurface Energy Resource Management: State of the Art and Future Prognosis, you are right to find our website which has a comprehensive collection of manuals listed.
Our library is the biggest of these that have literally hundreds of thousands of different products represented.

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Machine Learning Applications in Subsurface Energy Resource Management: State of the Art and Future Prognosis

Machine Learning Applications in Subsurface Energy Resource Management: State of the Art and Future Prognosis

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