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Study of a quantitative screening method of magnetotelluric sounding curves

  • Zhang GangEmail author
  • Wang Xuben
  • Li Dewei
  • Luo Wei
Original Study
  • 15 Downloads

Abstract

An accurate tensor estimation function is a guarantee for acquiring a reliable underground electrical structure model. The past studies regarding transmission functions aim at obtaining smooth and continuous sounding curves through the time domain by data screening means such as least square, robust and remote reference processing methods as well as digital filtering techniques such as wavelet denoising, empirical mode decomposition and Hilbert–Huang transform denoising. As SNRs in different field measurement sites are different, if different data processing algorithms like single-site processing, remote reference processing, magnetic field correlation-based remote reference processing and magnetic channel sharing are used for data processing at the same measuring site, 3N-2 groups of sounding curves with different qualities will be obtained. Manual screening method has been mainly used in the past for screening of the abovementioned 3N-2 groups of sounding curves. If the quantity of sounding site is large, this manual screening method is of low efficiency without quantitative screening indexes. In this paper, discrete Fréchet distance is mainly utilized to carry out quantitative screening of 3N-2 groups of sounding curves processed through the abovementioned four processing methods in order to obtain smooth, continuous and reliable sounding curves, thus avoiding subjectivity and low efficiency problems in the past manual screening. A quantitative sorting of all kinds of data processing results can be conducted, and the optimal sounding curve is finally picked out for data inversion. The above sounding curve selection result has improved processing accuracy of magnetotelluric data.

Keywords

Magnetotelluric sounding Fréchet distance Tensor impedance estimation 

Notes

Acknowledgements

This study was supported by the Chinese National Natural Science Foundation (Grant 41704105, 41674078), China Postdoctoral Science Foundation (Grant 2017M610611).

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Copyright information

© Akadémiai Kiadó 2019

Authors and Affiliations

  1. 1.School of Environment and ResourceSouthwest University of Science and TechnologyMianyangChina
  2. 2.Institute of GeophysicsChengdu University of TechnologyChengduChina
  3. 3.Sichuan Shutong Geotechnical Engineering CompanyChengduChina

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