Overview
- Presents the most recent advances, trending topics, and novel methods of integrated interpretation of multiphysics data
- Is the first book to consider the complex challenges of joint inversion of different geophysical data
- Helps lead to discovery and successful development of mineral deposits
Part of the book series: Advances in Geological Science (AGS)
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Table of contents (18 chapters)
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Mathematical Background
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Foundations of Inverse Theory
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Joint Inversion of Multiphysics Data
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AI-Aided Inversion
Keywords
About this book
Generally established joint inversion methods, however, are inadequate for incorporating typical physical or geological complexity. For example, analytic, empirical, or statistical correlations between different physical properties may exist for only part of the model, and their specific form may be unknown. Features or structures that are present in the data of one physical method may not be present in the data generated by another physical method or may not be equally resolvable.
This book presents and illustrates several advanced, new approaches to joint inversion and data fusion, which do not require a priori knowledge of specific empirical or statistical relationships between the different model parameters or their attributes. These approaches include the following novel methods, among others: 1) the Gramian method, which enforces the correlation between different parameters; 2) joint total variation functional or joint focusing stabilizers, e.g., minimum support and minimum gradient support constraints; 3) data fusion employing a joint minimum entropy stabilizer, which yields the simplest multiphysics solution that fits the multi-modal data. In addition, the book describes the principles of using artificial intelligence (AI) in solving multiphysics inverse problems. The book also presents in detail both the mathematical principles of these advanced approaches to joint inversion of multiphysics data and successful case histories of regional-scale and deposit-scale geophysical studies to illustrate their indicated advantages.
Authors and Affiliations
About the author
Bibliographic Information
Book Title: Advanced Methods of Joint Inversion and Fusion of Multiphysics Data
Authors: Michael S. Zhdanov
Series Title: Advances in Geological Science
DOI: https://doi.org/10.1007/978-981-99-6722-3
Publisher: Springer Singapore
eBook Packages: Earth and Environmental Science, Earth and Environmental Science (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023
Hardcover ISBN: 978-981-99-6721-6Published: 29 December 2023
Softcover ISBN: 978-981-99-6724-7Due: 29 January 2024
eBook ISBN: 978-981-99-6722-3Published: 28 December 2023
Series ISSN: 2524-3829
Series E-ISSN: 2524-3837
Edition Number: 1
Number of Pages: XVI, 369
Number of Illustrations: 15 b/w illustrations, 37 illustrations in colour
Topics: Geophysics/Geodesy, Geology, Geotechnical Engineering & Applied Earth Sciences, Natural Resource and Energy Economics