Sen, Mrinal K. Primary Author Stoffa, Paul L. Primary Author mixed material bibliography Cambridge Cambridge University 2013 en English

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xii, 289 p. : Illust. ; 25 cm Making inferences about systems in the Earth's subsurface from remotely-sensed, sparse measurements is a challenging task. Geophysical inversion aims to find models which explain geophysical observations - a model-based inversion method attempts to infer model parameters by iteratively fitting observations with theoretical predictions from trial models. Global optimization often enables the solution of non-linear models, employing a global search approach to find the absolute minimum of an objective function, so that predicted data best fits the observations. This new edition provides an up-to-date overview of the most popular global optimization methods, including a detailed description of the theoretical development underlying each method, and a thorough explanation of the design, implementation, and limitations of algorithms. A new chapter provides details of recently-developed methods, such as the neighborhood algorithm, and particle swarm optimization. An expanded chapter on uncertainty estimation includes a succinct description on how to use optimization methods for model space exploration to characterize uncertainty, and now discusses other new methods such as 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. Geophysics Mathematical Optimization Geological Modeling Inverse Problems (Differential Equations) Geophysics--Mathematical Models 550.113 9781107011908 e-Library Universitas Pertamina Be Global Leader 550.113 SEN g 2025/PUP/2016 Perpustakaan Universitas Pertamina 550.113 SEN g c.1 Global_Optimization_Methods_in_Geophysical_Inversion.jpg.jpg 701 2017-04-12 11:11:12 2017-04-12 11:11:42 machine generated Geophysical Engineering Geological Engineering Petroleum Engineering Computer Science