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Proceedings Paper

Full-waveform associated identification method of ATEM 3D anomalies based on multiple linear regression analysis
Author(s): Yanju Ji; Wanyu Huang; Mingmei Yu; Shanshan Guan; Yuan Wang; Yu Zhu
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Paper Abstract

This article studies full-waveform associated identification method of airborne time-domain electromagnetic method (ATEM) 3-d anomalies based on multiple linear regression analysis method. By using convolution algorithm, full-waveform theoretical responses are computed to derive sample library including switch-off-time period responses and off-time period responses. Extract full-waveform attributes from theoretical responses to derive linear regression equations which are used to identify the geological parameters. In order to improve the precision ulteriorly, we optimize the identification method by separating the sample library into different groups and identify the parameter respectively. Performance of full-waveform associated identification method with field data of wire-loop test experiments with ATEM system in Daedao of Changchun proves that the full-waveform associated identification method is feasible practically.

Paper Details

Date Published: 23 January 2017
PDF: 8 pages
Proc. SPIE 10322, Seventh International Conference on Electronics and Information Engineering, 1032225 (23 January 2017); doi: 10.1117/12.2265560
Show Author Affiliations
Yanju Ji, Jilin Univ. (China)
Wanyu Huang, Jilin Univ. (China)
Mingmei Yu, Jilin Univ. (China)
Shanshan Guan, Jilin Univ. (China)
Yuan Wang, Jilin Univ. (China)
Yu Zhu, Jilin Univ. (China)

Published in SPIE Proceedings Vol. 10322:
Seventh International Conference on Electronics and Information Engineering
Xiyuan Chen, Editor(s)

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