Global Optimization Methods in Geophysical Inversion [Hardcover]

An up-to-date overview of global optimization methods used to formulate and interpret geophysical observations, for researchers, graduate students and professionals.This up-to-date new edition provides an overview of global optimization methods, and includes succinct descriptions of background theory, advanced concepts and examples of geophysical inversion, enabling readers to formulate their own applications. A valuable resource for researchers, graduate students and professionals in geophysics, inverse theory, exploration geoscience and engineering.This up-to-date new edition provides an overview of global optimization methods, and includes succinct descriptions of background theory, advanced concepts and examples of geophysical inversion, enabling readers to formulate their own applications. A valuable resource for researchers, graduate students and professionals in geophysics, inverse theory, exploration geoscience and engineering.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.Preface; 1l_