An enhanced correlation identification algorithm and its application on spread spectrum induced polarization data
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Published:2021-05-19
Issue:2
Volume:28
Page:247-256
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ISSN:1607-7946
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Container-title:Nonlinear Processes in Geophysics
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language:en
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Short-container-title:Nonlin. Processes Geophys.
Author:
He Siming,Guan Jian,Ji Xiu,Xu Hang,Wang Yi
Abstract
Abstract. In spread spectrum induced polarization (SSIP) data
processing, attenuation of background noise from the observed data is the
essential step that improves the signal-to-noise ratio (SNR) of SSIP data.
The time-domain spectral induced polarization based on pseudorandom
sequence (TSIP) algorithm has been proposed to improve the SNR of these
data. However, signal processing in background noise is still a challenging
problem. We propose an enhanced correlation identification (ECI) algorithm
to attenuate the background noise. In this algorithm, the cross-correlation
matching method is helpful for the extraction of useful components of the
raw SSIP data and suppression of background noise. Then the frequency-domain
IP (FDIP) method is used for extracting the frequency response of the
observation system. Experiments on both synthetic and real SSIP data show
that the ECI algorithm will not only suppress the background noise but also
better preserve the valid information of the raw SSIP data to display the
actual location and shape of adjacent high-resistivity anomalies, which can
improve subsequent steps in SSIP data processing and imaging.
Funder
Jilin Scientific and Technological Development Program Education Department of Jilin Province Changzhou Institute of Technology
Publisher
Copernicus GmbH
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