Data processing method for magnetotelluric sounding based on cepstral analysis

Magnetotelluric (MT) signals exhibit the characteristics of being weak and having a wide frequency band. The acquired field data are susceptible to various types of noise, which poses challenges in accurate identification and processing. Currently, there exist numerous MT data processing methods; ho...

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Main Authors: Qining Zhan, Cai Liu, Yang Liu, Pengfei Zhao
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-10-01
Series:Frontiers in Earth Science
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/feart.2023.1183188/full
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author Qining Zhan
Cai Liu
Yang Liu
Pengfei Zhao
author_facet Qining Zhan
Cai Liu
Yang Liu
Pengfei Zhao
author_sort Qining Zhan
collection DOAJ
description Magnetotelluric (MT) signals exhibit the characteristics of being weak and having a wide frequency band. The acquired field data are susceptible to various types of noise, which poses challenges in accurate identification and processing. Currently, there exist numerous MT data processing methods; however, they lack efficiency and physical meaning. To address this issue and improve the signal-to-noise ratio of the acquired data, this study proposes a MT data processing method based on cepstral analysis. By employing cepstral analysis on the MT data, the cepstrum is obtained, and an appropriate truncation position is selected for processing. The experimental results demonstrate that this method obtains smoother and more continuous apparent resistivity curves with fewer errors. Compared with other methods, the cepstral analysis method can effectively suppress different types of MT noise, and the method is simple and efficient with clear physical significance.
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spelling doaj.art-44e247d1ea7f4fb580e06b1eed5f218e2023-10-18T08:09:39ZengFrontiers Media S.A.Frontiers in Earth Science2296-64632023-10-011110.3389/feart.2023.11831881183188Data processing method for magnetotelluric sounding based on cepstral analysisQining ZhanCai LiuYang LiuPengfei ZhaoMagnetotelluric (MT) signals exhibit the characteristics of being weak and having a wide frequency band. The acquired field data are susceptible to various types of noise, which poses challenges in accurate identification and processing. Currently, there exist numerous MT data processing methods; however, they lack efficiency and physical meaning. To address this issue and improve the signal-to-noise ratio of the acquired data, this study proposes a MT data processing method based on cepstral analysis. By employing cepstral analysis on the MT data, the cepstrum is obtained, and an appropriate truncation position is selected for processing. The experimental results demonstrate that this method obtains smoother and more continuous apparent resistivity curves with fewer errors. Compared with other methods, the cepstral analysis method can effectively suppress different types of MT noise, and the method is simple and efficient with clear physical significance.https://www.frontiersin.org/articles/10.3389/feart.2023.1183188/fullmagnetotelluriccepstral analysisdata processingspectral smoothingsignal denoising
spellingShingle Qining Zhan
Cai Liu
Yang Liu
Pengfei Zhao
Data processing method for magnetotelluric sounding based on cepstral analysis
Frontiers in Earth Science
magnetotelluric
cepstral analysis
data processing
spectral smoothing
signal denoising
title Data processing method for magnetotelluric sounding based on cepstral analysis
title_full Data processing method for magnetotelluric sounding based on cepstral analysis
title_fullStr Data processing method for magnetotelluric sounding based on cepstral analysis
title_full_unstemmed Data processing method for magnetotelluric sounding based on cepstral analysis
title_short Data processing method for magnetotelluric sounding based on cepstral analysis
title_sort data processing method for magnetotelluric sounding based on cepstral analysis
topic magnetotelluric
cepstral analysis
data processing
spectral smoothing
signal denoising
url https://www.frontiersin.org/articles/10.3389/feart.2023.1183188/full
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AT yangliu dataprocessingmethodformagnetotelluricsoundingbasedoncepstralanalysis
AT pengfeizhao dataprocessingmethodformagnetotelluricsoundingbasedoncepstralanalysis