Global Optimization Methods in Geophysical Inversion

Nonfiction, Science & Nature, Science, Earth Sciences, Geophysics
Cover of the book Global Optimization Methods in Geophysical Inversion by Mrinal K. Sen, Paul L. Stoffa, Cambridge University Press
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Author: Mrinal K. Sen, Paul L. Stoffa ISBN: 9781139610216
Publisher: Cambridge University Press Publication: February 21, 2013
Imprint: Cambridge University Press Language: English
Author: Mrinal K. Sen, Paul L. Stoffa
ISBN: 9781139610216
Publisher: Cambridge University Press
Publication: February 21, 2013
Imprint: Cambridge University Press
Language: English

Providing an up-to-date overview of the most popular global optimization methods used in interpreting geophysical observations, this new edition includes a detailed description of the theoretical development underlying each method and a thorough explanation of the design, implementation and limitations of algorithms. New and expanded chapters provide details of recently developed methods, such as the neighborhood algorithm, particle swarm optimization, hybrid Monte Carlo and multi-chain MCMC methods. Other chapters include new examples of applications, from uncertainty in climate modeling to whole Earth studies. Several different examples of geophysical inversion, including joint inversion of disparate geophysical datasets, are provided to help readers design algorithms for their own applications. This is an authoritative and valuable text for researchers and graduate students in geophysics, inverse theory and exploration geoscience, and an important resource for professionals working in engineering and petroleum exploration.

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Providing an up-to-date overview of the most popular global optimization methods used in interpreting geophysical observations, this new edition includes a detailed description of the theoretical development underlying each method and a thorough explanation of the design, implementation and limitations of algorithms. New and expanded chapters provide details of recently developed methods, such as the neighborhood algorithm, particle swarm optimization, hybrid Monte Carlo and multi-chain MCMC methods. Other chapters include new examples of applications, from uncertainty in climate modeling to whole Earth studies. Several different examples of geophysical inversion, including joint inversion of disparate geophysical datasets, are provided to help readers design algorithms for their own applications. This is an authoritative and valuable text for researchers and graduate students in geophysics, inverse theory and exploration geoscience, and an important resource for professionals working in engineering and petroleum exploration.

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