De-Noising of Short-Period Seismograms by Wavelet Packet Transform

Abstract

The wavelet packet transform gives information in both the time and frequency domains, and it is very useful for describing nonstationary signals like seismograms. Moreover, this structure is dependent on the signal under study; hence we can choose the time-frequency decomposition more appropriate for every signal. In this article, we propose a new method for filtering based on the wavelet packet transform. This approach uses different parameters for filtering, depending on the band of frequencies that we are analyzing. This filtering is employed in order to achieve a high signal-to-noise ratio (SNR) and low distortion. We first apply the method to synthetic signals that we have contaminated with noise. In this way, the shape of the whole output signal and the onset time of the first pulse can be compared to the ideal signal. Finally, we apply it to short-period seismograms recorded at the local seismic network of the University of Alicante in southeastern Spain. The method proposed is compared with conventional passband filters and other methods based on wavelets. The comparison demonstrates that our method achieves a higher SNR without introducing noticeable distortion.

Assessment of CO2 dynamics in subsurface atmospheres using the wavelet approach: from cavity–atmosphere exchange to anthropogenic impacts in Rull cave (Vall d′Ebo, Spain)

“…Its soft signal variations and shape allow for an easy fit to our type of data. Daubechies wavelets have been employed to analyse seismic signals (e.g., Galiana-Merino et al 2003, drilling-ability data (Frantziskonis and Denis 2003) 8 and precipitation series (Luan et al 2011). Morlet wavelets are used to find temporal periodicities.…”

Method for Identifying Micro-seismic P-Arrival by Time-frequency Analysis Using Intrinsic Time-Scale Decomposition

“…It is necessary to reduce the interference noise of the microseismic signals as much as possible. As any slight noise, distortion, or phase shift on the first arrival can result in an incorrect time picking (Galiana-Merino et al 2003), a denoising method based on ITD (Zhang et al 2012) is more suitable for detecting the seismic signal because the abrupt change of the amplitude at the beginning of the first pulse is preserved. We therefore apply the ITD method to the microseismic signals.…”

EnvironmentalWaveletTool: Continuous and discrete wavelet analysis and filtering for environmental time series

“…3b, we show the theoretical period ranges associated to the wavelet packet coefficients obtained for 2 levels of decomposition (scale 2). More details about the DWPT can also be found in Galiana-Merino et al [26].…”