J. Rosa-Herranz

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

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.

Seismic

The seismic P phase first arrival identification is a fundamental problem in seismology. The accurate identification of the P -wave first arrival is not a trivial process, particularly 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 another 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, particularly in cases of very low SNR.

P

Abstract With the recent development and the growth of personal computers technology, we decided to implement a new earthquake detector. This detector, WDetect, can register in continuous mode all signals received from all our stations of the Local Seismic Network in the province of Alicante in the South-East of Spain. Simultaneously, our program can detect and store seismic events using the classical algorithm based on short- and long-term averages (STA and LTA, respectively). As a new improvement in the detection process, we have added signal prefiltering using the discrete wavelet transform, which increases the detection rate and reduces the false alarm rate, in contrast to other detectors like XDetect or XRTP. All this has been achieved without losing any meaningful event. These improvements were verified by an analysis performed during March 2001 on data from the Local Seismic Network in the province of Alicante, where WDetect has been running since the end of year 2000.

Phase Picking Using a Kurtosis-Based Criterion in the Stationary Wavelet Domain

Abstract We have developed a new method for estimating azimuth in local three-component seismograms through wavelet analysis. The proposed process proceedsin three stages. First, the seismogram is filtered through a wavelet packet approach.Second, the first arrival is determined through a P picker similar to a short-term-average long-term-average scheme that is applied on the wavelet domain. Finally,an adaptive-length window around the pick is selected and used for determining theazimuth, using the property of linear polarization of the first arrival.The proposed method has been applied to three-component short-period seismo-grams for local earthquakes recorded by the seismic network of Alicante provincein southeastern Spain. The locations of these events were previously obtainedthroughthe software HYPO71PC (Lee and Valdes, 1989) and the seismograms recorded byfour analog stations of vertical component distributed within theprovinceofAlicante.The results obtained by the wavelet-based algorithm have been compared with theazimuth angles obtained through the results from the location software. The com-parison indicates that the proposed algorithm can determine the azimuth of the an-alyzed events to within a mean bias of 4.5 .Introduction

A real-time earthquake detector with prefiltering by wavelets

Abstract A MATLAB-based computer code has been developed for the simultaneous wavelet analysis and filtering of multichannel seismic data. The considered time–frequency transforms include the continuous wavelet transform, the discrete wavelet transform and the discrete wavelet packet transform. The developed approaches provide a fast and precise time–frequency examination of the seismograms at different frequency bands. Moreover, filtering methods for noise, transients or even baseline removal, are implemented. The primary motivation is to support seismologists with a user-friendly and fast program for the wavelet analysis, providing practical and understandable results. Program summary Program title: SeismicWaveTool Catalogue identifier: AENG_v1_0 Program summary URL: http://cpc.cs.qub.ac.uk/summaries/AENG_v1_0.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland Licensing provisions: Standard CPC license, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 611072 No. of bytes in distributed program, including test data, etc.: 14688355 Distribution format: tar.gz Programming language: MATLAB (MathWorks Inc.) version 7.8.0.347 (R2009a) or higher. Wavelet Toolbox is required. Computer: Developed on a MacBook Pro. Tested on Mac and PC. No computer-specific optimization was performed. Operating system: Any supporting MATLAB (MathWorks Inc.) v7.8.0.347 (R2009a) or higher. Tested on Mac OS X 10.6.8, Windows XP and Vista. Classification: 13. Nature of problem: Numerous research works have developed a great number of free or commercial wavelet based software, which provide specific solutions for the analysis of seismic data. On the other hand, standard toolboxes, packages or libraries, such as the MathWorks’ Wavelet Toolbox for MATLAB, offer command line functions and interfaces for the wavelet analysis of one-component signals. Thus, software usually is focused on very specific problems or carries out the wavelet analysis from a wide point of view. Solution method: The program implements the simultaneous wavelet analysis and filtering of multichannel seismic data. The considered time–frequency transforms include the continuous wavelet transform, the discrete wavelet transform and the discrete wavelet packet transform. The developed approaches provide a fast and precise time–frequency examination of the seismograms at different frequency bands. Moreover, several wavelet-based methods for band-pass filtering and noise, transients or even baseline removal, are implemented. Additional comments: A README file giving the names and a brief description of all the files that make up the package and clear instructions on the installation and execution of the program is included in the distribution package. Sample input files (approx. 12.2 MB) are also included.

Wavelet Transform Methods for Azimuth Estimation in Local Three-Component Seismograms

Short-period seismographs of the vertical component have a frequency response similar to a bandpass filter with a low cutoff frequency around 1 Hz. This instrument9s response distorts in some way the interesting signal that arrives at the sensor. In this case, the aim of the deconvolution is at recover the signal as it arrives at the sensor, since this signal can be very important to the study of source mechanisms, for instance. In this article we present a new method of regularized inversion based on the wavelet packet transform. This method achieves the deconvolution of the instrument response through the time-frequency information contained in the wavelet packet transform of the signals. Although the instrument response is known (Jauregui, 1997), the noise and other artifacts in the signal make deconvolution a nontrivial process. As an evaluation method, we first apply it to synthetic signals we generated. 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. The method is also applied to real signals, specifically to local short-period seismograms registered at the seismic network of the University of Alicante in southeastern Spain. In both cases, the results are compared with the water-level correction method currently used. The comparison shows how the proposed method works better, as it provides, in contrast to the current method, the shape and the onset time of the ideal signal.

SeismicWaveTool: Continuous and discrete wavelet analysis and filtering for multichannel seismic data

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. Display Omitted Development of a low-cost seismic recorder with amplifier and anti-aliasing filter.Geophonino is an open source and open hardware system.After configuration, data acquisition does not require any laptop connection.Comparisons with commercial systems confirm the right performance of Geophonino.