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Institute
Volcanic tremor extraction and earthquake detection using music information retrieval algorithms
(2021)
Volcanic tremor signals are usually observed before or during volcanic eruptions and must be monitored to evaluate the volcanic activity. A challenge in studying seismic signals of volcanic origin is the coexistence of transient signal swarms and long-lasting volcanic tremor signals. Separating transient events from volcanic tremors can, therefore, contrib-ute to improving upon our understanding of the underlying physical processes. Exploiting the idea of harmonic-percussive separation in musical signal processing, we develop a method to extract the harmonic volcanic tremor signals and to detect tran-sient events from seismic recordings. Based on the similarity properties of spectrogram frames in the time-frequency domain, we decompose the signal into two separate spec-trograms representing repeating (harmonic) and nonrepeating (transient) patterns, which correspond to volcanic tremor signals and earthquake signals, respectively. We reconstruct the harmonic tremor signal in the time domain from the complex spectrogram of the repeating pattern by only considering the phase components for the frequency range in which the tremor amplitude spectrum is significantly contribut-ing to the energy of the signal. The reconstructed signal is, therefore, clean tremor signal without transient events. Furthermore, we derive a characteristic function suitable for the detection of tran-sient events (e.g., earthquakes) by integrating amplitudes of the nonrepeating spectro-gram over frequency at each time frame. Considering transient events like earthquakes, 78% of the events are detected for signal-to-noise ratio = 0.1 in our semisynthetic tests. In addition, we compared the number of detected earthquakes using our method for one month of continuous data recorded during the Holuhraun 2014-2015 eruption in Iceland with the bulletin presented in Agustsdottir et al. (2019). Our single station event detection algorithm identified 84% of the bulletin events. Moreover, we detected a total of 12,619 events, which is more than twice the number of the bulletin events.
This study presents an unsupervised feature selection and learning approach for the discovery and intuitive imaging of significant temporal patterns in seismic single-station or network recordings. For this purpose, the data are parametrized by real-valued feature vectors for short time windows using standard analysis tools for seismic data, such as frequency-wavenumber, polarization, and spectral analysis. We use Self-Organizing Maps (SOMs) for a data-driven feature selection, visualization and clustering procedure, which is in particular suitable for high-dimensional data sets. Our feature selection method is based on significance testing using the Wald-Wolfowitz runs test for-individual features and on correlation hunting with SOMs in feature subsets. Using synthetics composed of Rayleigh and Love waves and real-world data, we show the robustness and the improved discriminative power of that approach compared to feature subsets manually selected from individual wavefield parametrization methods. Furthermore, the capability of the clustering and visualization techniques to investigate the discrimination of wave phases is shown by means of synthetic waveforms and regional earthquake recordings.
Traveltime residuals for worldwide seismic stations are calculated. We use P and S waves from earthquakes in SE-Asia at teleseismic and regional distances. The obtained station residuals help to enhance earthquake localisation. Furthermore we calculated regional source dependent station residuals. They show a systematic dependence of the locality of the source. These source dependent residuals reflect heterogenities along the path and can be used for a refinement of earthquake localisation.
On 26 December 2004, a moment magnitude M-w = 9.3 earthquake occurred along Northern Sumatra, the Nicobar and Andaman islands, resulting in a devastating tsunami in the Indian Ocean region(1). The rapid and accurate estimation of the rupture length and direction of such tsunami-generating earthquakes is crucial for constraining both tsunami wave- height models as well as the seismic moment of the events. Compressional seismic waves generated at the hypocentre of the Sumatra earthquake arrived after about 12 min at the broadband seismic stations of the German Regional Seismic Network (GRSN)(2,3), located approximately 9,000 km from the event. Here we present a modification of a standard array- seismological approach and show that it is possible to track the propagating rupture front of the Sumatra earthquake over a total rupture length of 1,150 km. We estimate the average rupture speed to be 2.3-2.7 km s(-1) and the total duration of rupture to be at least 430 s, and probably between 480 and 500 s.
We examine the use of ambient noise cross-correlation tomography for shallow site characterization using a modified two-step approach. Initially, we extract Rayleigh wave traveltimes from correlation traces of vertical component seismic recordings from a local network installed in Mygdonia basin, northern Greece. The obtained Rayleigh wave traveltimes show significant spatial variability, as well as distance and frequency dependence due to the 3-D structure of the area, dispersion, and anelastic attenuation effects. The traveltime data sets are inverted through a surface wave tomography approach to determine group velocity maps for each frequency. The proposed tomographic inversion involves the use of approximate Fresnel volumes and interfrequency smoothing constraints to stabilize the results. In the last step, we determine a final 3-D velocity model using a node-based Monte Carlo 1-D dispersion curve inversion. The reliability of the final 3-D velocity model is examined by spatial and depth resolution analysis, as well as by inversion for different model parameterizations. The obtained results are in very good agreement with previous findings from seismic and other geophysical methods. The new 3-D VS model provides additional structural constraints for the shallow sediments and bedrock structure of the northern Mygdonia basin up to the depth of similar to 200-250 m. Present work results suggest that the migration of ambient tomography techniques from large scales (tens or hundreds of km) to local scales (few hundred meters) is possible but cannot be used as a black box technique for 3-D modeling and detailed geotechnical site characterization.
Permafrost inundated since the last glacial maximum is degrading, potentially releasing trapped or stabilized greenhouse gases, but few observations of the depth of ice-bonded permafrost (IBP) below the seafloor exist for most of the arctic continental shelf. We use spectral ratios of the ambient vibration seismic wavefield, together with estimated shear wave velocity from the dispersion curves of surface waves, for estimating the thickness of the sediment overlying the IBP. Peaks in spectral ratios modeled for three-layered 1-D systems correspond with varying thickness of the unfrozen sediment. Seismic receivers were deployed on the seabed around Muostakh Island in the central Laptev Sea, Siberia. We derive depths of the IBP between 3.7 and 20.7m15%, increasing with distance from the shoreline. Correspondence between expected permafrost distribution, modeled response, and observational data suggests that the method is promising for the determination of the thickness of unfrozen sediment.
We test the capability of broadband arrays at teleseismic distances to image the spatio-temporal characteristics of the seismic energy release during the Dec 26, 2004 Sumatra earthquake at early observation times. Using a non-plane-wave array location technique previously reported values for rupture length (about 1150 km), duration (about 480 s), and average rupture velocity (2.4-2.7 km/s) are confirmed. Three dominant energy releases are identified: one near the hypocenter, a second at 6 degrees N94 degrees E about 130 s later and a third one after 300 s at 9 degrees N92-93 degrees E. The spatio-temporal distribution of the radiated seismic energy in the source region is calculated from the stacked broadband recordings of two arrays in Germany and Japan and results in rough estimates of the total seismic energy of 0.55.10(18) Nm (GRSN) and 1.53.10(18) Nm (FNET) respectively. Changes in the relative ratio of energy as function of spatio-temporal location indicate a rotation of the focal mechanism during the rupture process
The most recent intense earthquake swarm in the Vogtland lasted from 6 October 2008 until January 2009. Greatest magnitudes exceeded M3.5 several times in October making it the greatest swarm since 1985/86. In contrast to the swarms in 1985 and 2000, seismic moment release was concentrated near swarm onset. Focal area and temporal evolution are similar to the swarm in 2000. Work hypothysis: uprising upper-mantle fluids trigger swarm earthquakes at low stress level. To monitor the seismicity, the University of Potsdam operated a small aperture seismic array at 10 km epicentral distance between 18 October 2008 and 18 March 2009. Consisting of 12 seismic stations and 3 additional microphones, the array is capable of detecting earthquakes from larger to very low magnitudes (M<-1) as well as associated air waves. We use array techniques to determine properties of the incoming wavefield: noise, direct P and S waves, and converted phases.
In the present study, we investigated the dispersion characteristics of medium-to-long period Rayleigh waves (2 s < T < 20 s) using both single-station techniques (multiple-filter analysis, and phase-match filter) and multichannel techniques (horizontal slowness [p] and angular frequency [omega] stack, and cross-correlation) to determine the velocity structure for the Mt. Etna volcano. We applied these techniques to a dataset of teleseisms, as regional and local earthquakes recorded by two broad-band seismic arrays installed at Mt. Etna in 2002 and 2005, during two seismic surveys organized by the Istituto Nazionale di Geofisica e Vulcanologia (INGV), sezione di Napoli. The dispersion curves obtained showed phase velocities ranging from 1.5 km/s to 4.0 km/s in the frequency band 0.05 Hz to 0.45 Hz. We inverted the average phase velocity dispersion curves using a non-linear approach, to obtain a set of shear-wave velocity models with maximum resolution depths of 25 km to 30 km. Moreover, the presence of lateral velocity contrasts was checked by dividing the whole array into seven triangular sub-arrays and inverting the dispersion curves relative to each triangle.
We present an integrated approach for deriving the 1D shear wave velocity (Vs) information at few tens to hundreds of meters down to the first strong impedance contrast in typical sedimentary environments. We use multiple small aperture seismic arrays in 1D and 2D configuration to record active and passive seismic surface wave data at two selected geotechnical sites in Germany (Horstwalde & Lobnitz). Standard methods for data processing include the Multichannel Analysis of Surface Waves (MASW) method that exploits the high frequency content in the active data and the sliding window frequency-wavenumber (f-k) as well as the spatial autocorrelation (SPAC) methods that exploit the low frequency content in passive seismic data. Applied individually, each of the passive methods might be influenced by any source directivity in the noise wavefield. The advantages of active shot data (known source location) and passive microtremor (low frequency content) recording may be combined using a correlation based approach applied to the passive data in the so called Interferometric Multichannel Analysis of Surface Waves (IMASW). In this study, we apply those methods to jointly determine and interpret the dispersion characteristics of surface waves recorded at Horstwalde and Lobnitz. The reliability of the dispersion curves is controlled by applying strict limits on the interpretable range of wavelengths in the analysis and further avoiding potentially biased phase velocity estimates from the passive f-k method by comparing to those derived from the SPatial AutoCorrelation method (SPAC). From our investigation at these two sites, the joint analysis as proposed allows mode extraction in a wide frequency range (similar to 0.6-35 Hz at Horstwalde and similar to 1.5-25 Hz at Lobnitz) and consequently improves the Vs profile inversion. To obtain the shear wave velocity profiles, we make use of a global inversion approach based on the neighborhood algorithm to invert the interpreted branches of the dispersion curves. Within the uncertainty given by the apparent spread of forward models we find that besides a well defined sediment velocity range also a reasonable minimum estimate of bedrock depth and bedrock velocity can be achieved. The Vs estimate for the best model in Horstwalde ranges from similar to 190 m/s at the surface up to similar to 390 m/s in the bottom of the soft sediment column. The bedrock starts earliest around 200 m depth and bedrock velocities are higher than 1000 m/s. In Lobnitz, we observe slightly lower velocities for the sediments (similar to 165-375 m/s for the best model) and a minimum thickness of 75 m. (C) 2016 Elsevier B.V. All rights reserved.