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portada Machine Learning for Subsurface Characterization
Type
Physical Book
Publisher
Author
Year
2019
Language
English
Pages
440
Format
Paperback
ISBN13
9780128177365
Edition No.
1
Categories

Machine Learning for Subsurface Characterization

Siddharth Misra; Hao Li; Jiabo He (Author) · Gulf Professional Publishing · Paperback

Machine Learning for Subsurface Characterization - Siddharth Misra; Hao Li; Jiabo He

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Synopsis "Machine Learning for Subsurface Characterization "

Machine Learning for Subsurface Characterization focuses on the development and application of neural networks, deep learning, unsupervised learning, reinforcement learning, and clustering methods for subsurface characterization under constraints due to financial, operational, regulatory, risk, technological and environmental challenges. The book introduces readers to methods of generating subsurface signals and analyzing the complex relationships within various subsurface signals using machine learning. Algorithmic procedures in MATLAB, R, PYTHON, and TENSORFLOW are displayed in text and through online instructional videos to assist training and learning. Field cases are also presented to demonstrate real-world applications, with a particular focus on examples involving shale reservoirs. Explaining the concept of machine learning, advantages to the industry, and applications applied to complex subsurface rocks, this book delivers a missing piece for the reservoir engineer’s toolbox.Focuses on applying predictive modeling and machine learning from real case studies and Q&A sessions at the end of each chapter Teaches users how to develop codes, such as MATLAB, PYTHON, R and TENSORFLOW with step-by-step guides includedHelps readers visually learn code development with video demonstrations

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