Machine Learning Applications in Subsurface Energy Resource Management
Machine Learning Applications in Subsurface Energy Resource Management
Hardback
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Sign in or Sign up!- Release Date: 27/12/2022
- Barcode: 9781032074528
- Genre: Computing & Internet
- Label: CRC Press
- Publisher: Taylor & Francis Ltd
- Subgenre: Science Nature & Math

Machine Learning Applications in Subsurface Energy Resource Management
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DESCRIPTION
State of the Art and Future Prognosis. Machine Learning Applications in Subsurface Energy Resource Management presents a current snapshot of the state of the art and future outlook for machine learning applications in subsurface energy resource management (e.g., oil and gas, geologic carbon sequestration, geothermal energy). 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). This 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.
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