A Novel Method for Obtaining Optimal Apparent Resistivity Curve of Controlled-Source Electromagnetic

The controlled-source electromagnetic (CSEM) method is an effective approach for obtaining subsurface electrical structures and exploring deep-seated mineral resources. However, the quality of CSEM data is often severely affected by noise. The traditional approach to signal-to-noise separation aims...

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Bibliographic Details
Published in:IEEE transactions on geoscience and remote sensing Vol. 62; pp. 1 - 12
Main Authors: Liu, Yecheng, Li, Diquan
Format: Journal Article
Language:English
Published: New York IEEE 2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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ISSN:0196-2892, 1558-0644
Online Access:Get full text
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Summary:The controlled-source electromagnetic (CSEM) method is an effective approach for obtaining subsurface electrical structures and exploring deep-seated mineral resources. However, the quality of CSEM data is often severely affected by noise. The traditional approach to signal-to-noise separation aims to achieve accurate separation of the effective signal and noise. Departing from this conventional idea, we propose a novel method to improve the quality of CSEM apparent resistivity curves. This article presents two main contributions. First, we introduce a quantitative parameter known as the smoothness value (SV) to evaluate the smoothness of the apparent resistivity curve. Second, based on this parameter and considering the relationship between the time-series data and the apparent resistivity curves, we propose the apparent resistivity curve screening method to screen out the optimal apparent resistivity curve in the CSEM-measured sites. To validate the proposed method, we conduct batch processing on a total of 100 CSEM-measured sites derived from two survey lines. The experimental results show that the proposed method improves the apparent resistivity curves of all the measured sites to different degrees. Compared with the original, the SV values of all curves were reduced by 5.28 on average. This reduction underscores the method's substantial potential for practical application in the field.
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ISSN:0196-2892
1558-0644
DOI:10.1109/TGRS.2024.3477509