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Uncertainty analysis in regularized multidimensional electromagnetic imaging: A nonlinear most-squares approach
- Publisher: European Association of Geoscientists & Engineers
- Source: Conference Proceedings, 10th International Congress of the Brazilian Geophysical Society, Nov 2007, cp-172-00031
Abstract
Formally, model uncertainty and non-uniqueness can be reduced by combining measurements of fundamentally different physical attributes of a subsurface target under investigation or by using available a priori information about the target. Geophysical measurements are typically band-limited in nature and contain noise. The nonlinear most-squares formalism allows for combining observations and their associated errors in an objective manner to determine the model bounds. A regularized most-squares appraisal method is described in detail and illustrated with a field example.