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3-D inversion of magnetic data
TLDR
We present a method for inverting surface magnetic data to recover 3-D susceptibility models by minimizing a global objective function composed of the model objective function and data misfit. Expand
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Estimating depth of investigation in DC resistivity and IP surveys
In this paper, the term “depth of investigation” refers generically to the depth below which surface data are insensitive to the value of the physical property of the earth. Estimates of this depthExpand
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3-D inversion of gravity data
We present two methods for inverting surface gravity data to recover a 3-D distribution of density contrast. In the first method, we transform the gravity data into pseudomagnetic data via Poisson'sExpand
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3-D inversion of gravity data
We present two methods for inverting surface gravity data to recover a 3-D distribution of density contrast. In the first method, we transform the gravity data into pseudomagnetic data via Poisson'sExpand
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The inversion and interpretation of gravity anomalies
A rearrangement of the formula used for the rapid calculation of the gravitational anomaly caused by a two‐dimensional uneven layer of material (Parker, 1972) leads to an iterative procedure forExpand
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NON-LINEAR INVERSION USING GENERAL MEASURES OF DATA MISFIT AND MODEL STRUCTURE
We investigate the use of general, non-l2 measures of data misfit and model structure in the solution of the non-linear inverse problem. Of particular interest are robust measures of data misfit, andExpand
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3-D Inversion of Magnetic Data
We present a method for inverting surface magnetic data to recover 3-D susceptibility models. To allow the maximum flexibility for the model to represent geologically realistic structures, weExpand
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A Discrimination Algorithm for UXO Using Time Domain Electromagnetics
An assumption is made that the Time Domain Electromagnetic (TEM) response of a buried axisymmetric metallic object can be modelled as the sum of two dipoles centered at the midpoint of the body. TheExpand
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A comparison of automatic techniques for estimating the regularization parameter in non-linear inverse problems
SUMMARY Two automatic ways of estimating the regularization parameter in underdetermined, minimumstructure-type solutions to non-linear inverse problems are compared: the generalized crossvalidationExpand
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METHODS FOR CALCULATING FRÉCHET DERIVATIVES AND SENSITIVITIES FOR THE NON‐LINEAR INVERSE PROBLEM: A COMPARATIVE STUDY1
A fundamental step in the solution of most non-linear inverse problems is to establish a relationship between changes in a proposed model and resulting changes in the forward modelled data. Once thisExpand
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