Title :
Piecewise smooth models for electromagnetic inverse problems
Author :
Hidalgo, Hugo ; Marroquin, José Luìs ; Gomez-Trevino, E.
Author_Institution :
CICESE, Mexico
fDate :
3/1/1998 12:00:00 AM
Abstract :
This paper presents a new method for constructing one-dimensional (1D) electrical conductivity models of the Earth from surface electromagnetic measurements. The construction of these models is a nonlinear inverse problem that can be approached by linearization techniques combined with iterative methods and Tikhonov´s regularization. The standard application of these techniques usually leads to smooth models that represent a continuous variation of conductivity with depth. In this work, the authors describe how these methods can be modified to incorporate what is known in computer vision as the line process (LP) decoupling technique, which has the ability to include discontinuities in the models. This results in piecewise smooth models that are often more adequate for representing stratified media. They have implemented a relaxation technique to construct these types of models and present numerical experiments as well as an application to field data. These examples illustrate the performance of the combined LP and Tikhonov´s regularization method
Keywords :
electromagnetic induction; geophysical prospecting; geophysical techniques; inverse problems; terrestrial electricity; EM induction; Tikhonov´s regularization; electrical conductivity model; electromagnetic inverse problem; exploration; geoelectric method; geophysical measurement technique; iterative methods; line process decoupling; linearization technique; nonlinear inverse problem; one-dimensional model; piecewise smooth model; prospecting; regularization method; surface electromagnetic measurements; terrestrial electricity; Application software; Computer vision; Conductivity; Earth; Electromagnetic measurements; Electromagnetic modeling; Inverse problems; Iterative methods; Linearization techniques; Nonhomogeneous media;
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on