A noise reduction method based on EWT-ICA for spectrum induced polarisation data
Zhihua Li, Wenqi Zhou, Yanjun Chang, Wei Liu, Jixuan Zhu · Exploration Geophysics · 2020
Spectrum induced polarisation (SIP) is a frequency-domain method commonly used in electrical geophysical exploration. However, SIP is very sensitive to the signal-to-noise ratio of the signal, so noise reduction is very important. Independent component analysis can be used to reduce the noise of geophysical exploration data, but it cannot be used when the observed signal has only one dimension. In this paper, an empirical wavelet transform-independent component analysis method is proposed, which can be used for noise reduction in spectrum induced polarisation data. Firstly, the original measurement data are adaptively decomposed into a finite number of intrinsic modal functions by empirical wavelet transform, and then the intrinsic modal functions are selected to construct a virtual noise channel according to their correlation with the induced polarisation signal. Finally, the induced polarisation signal in the multi-dimensional mixed data is extracted by independent component analysis. Our experiment shows results show that this method can effectively remove noise signals and improve the signal-to-noise ratio of induced polarisation data.