Mrinal K. Sen

Global Optimization Methods in Geophysical Inversion (eBook, PDF)

• Format: PDF

Produktbeschreibung

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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Produktdetails

• Verlag: Cambridge University Press
• Erscheinungstermin: 21. Februar 2013
• Englisch
• ISBN-13: 9781139603348
• Artikelnr.: 38276183

Autorenporträt

Mrinal K. Sen is a professor of geophysics in the Dept. of Geological Sciences and a research professor at the Inst. for Geophysics of the John A. and Katherine G. Jackson School of Geosciences at the U. of Texas at Austin. He worked in the oil industry from 1979 to 1982 and has been employed at the U. of Texas since 1989. Sen's research interests include seismic wave propagation, inverse theory, and computational geophysics. He holds BS and MS degrees in applied geophysics from the Indian School of Mines and a PhD degree in geophysics from the U. of Hawaii at Manoa. He is a member of SEG, AGU, EAGE, SIAM, and the European Academy of Sciences.

Inhaltsangabe

Preface
1. Preliminary statistics
2. Direct, linear, and iterative-linear inverse methods
3. Monte Carlo methods
4. Simulated annealing methods
5. Genetic algorithms
6. Other global optimization methods
7. Geophysical applications of SA and GA
8. Uncertainty estimation
References
Index.