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Conductivity-depth Imaging Algorithm for Central-loop Helicopter TEM

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Abstract & Overview

A Conductivity-Depth Imaging(CDI) algorithm is presented for a central-loop helicopter airborne system as an example in this paper,to transform the transient induced electromotive force response data into a conductivity-depth section very quickly.The method aimed at the non-uniqueness problem of the apparent conductivity and the difficulties to obtain the imaging depth in the imaging method,and is successfully developed according to the following steps:firstly,a transformation formula of the data function ?(?)about the conductivity of homogeneous half-space model ? is presented,and then a table of the data function relationship with the conductivity is built to search the apparent conductivity value.This method can overcome the problem of the non-unique value of the apparent conductivity.Secondly,the apparent depth is approximated using the depth of the maximum induced electric field in the homogeneous half-space earth,and a data table about apparent conductivity and apparent depth is established to accelerate computing.Finally,the imaging depth is determined based on the depth change of the maximum electric field at the two adjacent delay time and then the CDI result is obtained consequently.The advantage of the method is that its high-efficiency of the table lookup technique can make the real-time CDI possible.Using a table lookup with a large conductivity range from 10-4 S/m to 102 S/m,tests on synthetic data demonstrate that the algorithm does a good job of solving conductive or resistive thin layers and 2D object.

Cite this record

Lifeng Mao (2013). Conductivity-depth Imaging Algorithm for Central-loop Helicopter TEM. Computerized Tomography Theory and Applications. https://library.shubhaarti.in/content/adebe4e2-6f2b-4c98-9bd5-65710e0213f1

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Mao, L. (2013). Conductivity-depth Imaging Algorithm for Central-loop Helicopter TEM. Computerized Tomography Theory and Applications. https://library.shubhaarti.in/content/adebe4e2-6f2b-4c98-9bd5-65710e0213f1
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