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.
Highlights
Induced polarization (IP) technology operated in both the time domain and the frequency domain is useful in exploration for groundwater mapping, mineral exploration, and other environmental studies (Revil et al, 2012, 2019; Høyer et al, 2018)
In the impulsive noise experiment, we found that the enhanced correlation identification (ECI) algorithm still has good noise reduction when the discrete point is more than 60 %, which compensates for the disadvantage of the traditional denoising algorithm
We propose the ECI algorithm that effectively attenuates the background noise in spread spectrum induced polarization (SSIP) data and improves the complex resistivity spectrum
Summary
Induced polarization (IP) technology operated in both the time domain and the frequency domain is useful in exploration for groundwater mapping, mineral exploration, and other environmental studies (Revil et al, 2012, 2019; Høyer et al, 2018). According to the intrinsic broadband characteristics of the source itself, the spectral response of an observation system can be simultaneously calculated at multiple frequencies in electrical exploration (Liu et al, 2019) This SSIP technology has been gaining attention and application in electrical prospecting (Xi et al, 2014; Lu et al, 2019; Wang and He, 2020). The new algorithm based on a circular crosscorrelation method, time-domain spectral induced polarization based on pseudorandom sequence (TSIP) algorithm, has been used to suppress the SSIP noise (Li et al 2013; Zhang et al, 2020). The TSIP algorithm is restricted because the excitation signal is sensitive to the random noise For this problem, we propose an enhanced correlation identification (ECI) algorithm for reducing the noise in SSIP data. Experimental results show that the ECI algorithm can effectively control the root mean square of noise (NRMS) increase, enhance its denoising performance in background noise and improve the valid signal preservation to display the actual location and shape of highresistivity anomalies with higher resolution
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