02700cam a2200265 i 4500 121116s2013 enk b 001 0 eng 9781107011908 SDU QE43 S474 G 2013 Sen, Mrinal K. 210850 Global optimization methods in geophysical inversion / Mrinal K. Sen, University of Texas, Austin, USA and Paul L. Stoffa, The University of Texas, Austin, USA. 2nd ed New York : Cambridge University Press, 2013 289 p. HKBU Library "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. "-- Geological modeling. 210851 Geophysics Mathematical models. 210852 Inverse problems (Differential equations) 205854 Mathematical optimization. SCIENCE / Geophysics. 210853 Stoffa, Paul L., 1948- 210854 = C.1 SDU GBE lcc 109368 109368 0 0 lcc 0 QE0043 S474 G2013 0 CGB 283816 SDU SDU GEN3 2025-10-03 2 0 QE43 S474 G 2013 1000377562 2025-10-03 00:00:00 C.1 2025-10-03 GBE