publication . Article . 2012

Transdimensional tomography

Malcolm Sambridge; Nicholas Rawlinson; Pierre Arroucau; Thomas Bodin;
Open Access
  • Published: 04 Apr 2012 Journal: Geophysical Journal International, volume 189, pages 1,536-1,556 (issn: 0956-540X, Copyright policy)
  • Publisher: Oxford University Press (OUP)
SUMMARY A meaningful interpretation of seismic measurements requires a rigorous quantification of the uncertainty. In an inverse problem, the data noise determines how accurately observations should be fit, and ultimately the level of detail contained in the recovered model. A common problem in seismic tomography is the difficulty in quantifying data uncertainties, and thus the required level of data fit. Traditionally, the complexity of the solution model (defined by both the number of basis functions and the regularization) is defined arbitrarily by the user prior to inversion with only limited use of data errors. In the context of multiscale problems, dealing...
free text keywords: Geochemistry and Petrology, Geophysics, Inverse problem, Data type, Regularization (mathematics), Level of detail, Basis function, Data set, Data mining, computer.software_genre, computer, Probability distribution, Ambient noise level, Mathematics
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