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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.

The commercial data acquisition systems used for seismic exploration are usually expensive equipment. In this work, a low cost data acquisition system (Geophonino) has been developed for recording seismic signals from a vertical geophone. The signal goes first through an instrumentation amplifier, INA155, which is suitable for low amplitude signals like the seismic noise, and an anti-aliasing filter based on the MAX7404 switched-capacitor filter. After that, the amplified and filtered signal is digitized and processed by Arduino Due and registered in an SD memory card. Geophonino is configured for continuous registering, where the sampling frequency, the amplitude gain and the registering time are user-defined. The complete prototype is an open source and open hardware system. It has been tested by comparing the registered signals with the ones obtained through different commercial data recording systems and different kind of geophones. The obtained results show good correlation between the tested measurements, presenting Geophonino as a low-cost alternative system for seismic data recording.

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Highlights  Low cost data acquisition system for recording three-component seismic noise.  Suitability of the equipment for the application of the H/V method.  The developed system has been successfully compared with commercial systems.  It is an open source and open hardware system.  The low cost is essential for small research groups with reduced economic support.

One of the most important tasks in seismology and applied geophysics is the identification of the different kinds of waves that form a seismic record by means of polarization analysis. In particular, this involves the extraction of body waves (linear polarization) or surface waves (mostly elliptical polarization) from a set of seismic data and which forms a key point in several studies.In this work, a new method of time-frequency polarization analysis based on the stationary wavelet packet transform is developed. The proposed approach identifies and extracts automatically the different waves included in the signal, dependent upon the reciprocal ellipticity. Moreover, the algorithm provides enough information to the user to allow them to also manually select the reciprocal ellipticity intervals, and then extract the corresponding waves of interest contained in the signals.The proposed polarization estimation method and the automatic features extraction algorithm have been evaluated first using synthetic signals, and then applied to real seismic records. Based on the results obtained from both synthetic and real signals, we can conclude that the proposed method correctly identifies and extracts automatically the linearly and ellipticaly polarized waves from the signal, discerning clearly both types of polarization. Moreover, the proposed method is able to identify and extract signals with different kinds of elliptical polarization, allowing us to understand better the characteristics of Rayleigh waves.Index Terms -Polarization analysis, wave identification, seismic signal processing, stationary wavelet packet transform (SWPT).3

The P seismic phase first arrival identification is a fundamental problem in seismology. The accurate identification of the P-wave first arrival is not a trivial process, especially when the seismograms present a very low signal-to noise ratio (SNR) or are contaminated with artificial transients that could produce false alarms. In this paper, a new approach based on higher-order statistics and the stationary wavelet transform is presented. The P onset is obtained under a statistical criterion applied in the time-frequency domain. The results have been compared to those estimated by other P phase picking algorithm and P onsets picked by expert analysts. The comparison shows that our proposed method efficiently provides a good estimate of the P onset picks that are consistent with analyst picks, especially in the cases of very low SNR.Index Terms -Kurtosis, P phase identification, seismic signal processing, stationary wavelet transform (SWT).3

A B S T R A C TMicrozonation studies using ambient noise measurements constitute a promising way for seismic hazard evaluation in urban areas. Among the existing techniques, seismic noise array measurements have become a valuable tool for estimating Vs profiles and thus, the characteristics of a soil structure. Although methods based on analysis of seismic noise are simpler, cheaper and faster than borehole drilling and down-hole or cross-hole logs to derive shear-wave velocity profiles, array deployment requires the use of several stations (broadband or short-period sensors) that are not always available. In this paper, we have compared the results obtained by 10 Hzvertical-geophone arrays with the results provided by 1 Hz-sensor arrays. Two sites in the Bajo Segura Basin (SE Spain), with different soil characteristics, were chosen for array deployment. The comparison is carried out in terms of dispersion curves by using frequency-wavenumber (f-k) and extended spatial autocorrelation (ESAC) techniques. Both analyses show a good agreement using either 1 Hz sensors or 10 Hz geophones; moreover, they demonstrate that it is possible to extend the analysis in a frequency range much below the natural frequency of the geophones. The results of our study confirm the suitability of standard seismic refraction/reflection equipment also for ambient noise array measurements, which constitutes a cheaper and faster way for investigating soil characteristics.