DocumentCode :
960866
Title :
Electromagnetic conductivity imaging with an iterative Born inversion
Author :
Alumbaugh, David L. ; Morrison, H. Frank
Author_Institution :
Lawrence Berkeley Lab., California Univ., CA, USA
Volume :
31
Issue :
4
fYear :
1993
fDate :
7/1/1993 12:00:00 AM
Firstpage :
758
Lastpage :
763
Abstract :
A technique which uses low frequency electromagnetic fields to image the Earth´s conductivity structure between two boreholes is developed. The scheme employs the Born approximation to linearize the integral equation formulation, and a regularized least squares method to invert the data for an initial estimate of the conductivity. A second Born approximation is then applied in a iterative manner to achieve better estimates of the structure. Numerical experiments show that this iterative method improves resolution when compared to normal Born inversion due to the fact that coupling between scattering currents is accounted for. The image quality is shown to be dependent on the operating frequency with the optimal frequency corresponding to the peak of a sensitivity function the authors have termed the Born kernel, which is the product of the primary electric field and the Green´s function
Keywords :
geophysical prospecting; geophysical techniques; terrestrial electricity; Born approximation; Born kernel; EM method; boreholes; cross borehole method; electrical conductivity imaging; geoelectric; image; integral equation; iterative; iterative Born inversion; low frequency electromagnetic fields; measurement; optimal frequency; prospecting; regularized least squares method; sensitivity function; structure; technique; terrestrial electricity; Approximation methods; Conductivity; Earth; Electromagnetic fields; Electromagnetic scattering; Frequency; Image quality; Integral equations; Iterative methods; Least squares methods;
fLanguage :
English
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on
Publisher :
ieee
ISSN :
0196-2892
Type :
jour
DOI :
10.1109/36.239897
Filename :
239897
Link To Document :
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