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Volcanic eruptions are often preceded by seismic activity that can be used to quantify the volcanic activity. In order to allow consistent inference of the volcanic activity state from the observed seismicity patterns, objective and time-invariant classification results achievable by automatic systems should be preferred. Most automatic classification approaches need a large preclassified data set for training the system. However, in case of a volcanic crisis, we are often confronted with a lack of training data due to insufficient prior observations. In the worst case (e. g., volcanic crisis related reconfiguration of stations), there are even no prior observations available. Finally, due to the imminent crisis there might be no time for the time-consuming process of preparing a training data set. For this reason, we have developed a novel seismic-event spotting technique in order to be less dependent on previously acquired data bases and classification schemes. We are using a learning-while-recording approach based on a minimum number of reference waveforms, thus allowing for the build-up of a classification scheme as early as interesting events have been identified. First, short-term wave-field parameters (here, polarization and spectral attributes) are extracted from a continuous seismic data stream. The sequence of multidimensional feature vectors is then used to identify a fixed number of clusters in the feature space. Based on this general description of the overall wave field by a mixture of multivariate Gaussians, we are able to learn particular event classifiers (here, hidden Markov models) from a single waveform example. To show the capabilities of this new approach we apply the algorithm to a data set recorded at Soufriere Hills volcano, Montserrat. Supported by very high classification rates, we conclude that the suggested approach provides a valuable tool for volcano monitoring systems.
Constructing a hidden Markov Model based earthquake detector: application to induced seismicity
(2012)
The triggering or detection of seismic events out of a continuous seismic data stream is one of the key issues of an automatic or semi-automatic seismic monitoring system. In the case of dense networks, either local or global, most of the implemented trigger algorithms are based on a large number of active stations. However, in the case of only few available stations or small events, for example, like in monitoring volcanoes or hydrothermal power plants, common triggers often show high false alarms. In such cases detection algorithms are of interest, which show reasonable performance when operating even on a single station. In this context, we apply Hidden Markov Models (HMM) which are algorithms borrowed from speech recognition. However, many pitfalls need to be avoided to apply speech recognition technology directly to earthquake detection. We show the fit of the model parameters in an innovative way. State clustering is introduced to refine the intrinsically assumed time dependency of the HMMs and we explain the effect coda has on the recognition results. The methodology is then used for the detection of anthropogenicly induced earthquakes for which we demonstrate for a period of 3.9 months of continuous data that the single station HMM earthquake detector can achieve similar detection rates as a common trigger in combination with coincidence sums over two stations. To show the general applicability of state clustering we apply the proposed method also to earthquake classification at Mt. Merapi volcano, Indonesia.
Forecasting seismo-volcanic activity by using the dynamical behavior of volcanic earthquake rates
(2012)
We present a novel approach for short-term forecasting of volcano seismic activity. Volcanic earthquakes can be seen as a response mechanism of the earth crust to stresses induced by magma injection. From this point of view the temporal evolution of seismicity can be represented as a diffusion process which compensates pressure differences. By means of this dynamical approach we are able to estimate the system behavior in the near future which in turn allows us to forecast the evolution of the earthquake rate for the next time span from actual and past observations. For this purpose we model the earthquake rate as a random walk process embedded in a moving and deforming potential function. The center of the potential function is given by a moving average of the random walk's trace. We successfully apply this procedure to estimate the next day seismicity at Soufriere Hills volcano, Montserrat, over a time period of six years. When comparing the dynamical approach to the well known method of material failure forecast we find much better predictions of the critical stages of volcanic activity using the new approach.
The inversion of surface-wave dispersion curve to derive shear-wave velocity profile is a very delicate process dealing with a nonunique problem, which is strongly dependent on the model space parameterization. When independent and reliable information is not available, the selection of most representative models within the ensemble produced. by the inversion is often difficult. We implemented a strategy in the inversion of dispersion curves able to investigate the influence of the parameterization of the model space and to select a "best" class of models. We analyzed surface-wave dispersion curves measured at 14 European strong..-motion sites within the NERIES EC-Project. We focused on the inversion task exploring the model space by means of four distinct pararneterization classes composed of layers progressively added over a half-space. The classes differ in the definition of the shear-wave velocity profile; we considered models with uniform velocity as well as models with increasing velocity with depth. At each site and for each model parameterization, we performed an extensive surface-wave inversion (200,100 models for five seeds) using the conditional neighborhood algorithm. We addressed the model evaluation following the corrected Akaike's information criterion (AlCc) that combines the concept of misfit to the number of degrees of freedom of the system. The misfit was computed as least-squares estimation between theoretical and observed dispersion curve. The model complexity was accounted in a penalty term by AlCc. By applying such inversion strategy on 14 strong-motion sites, we found that the best parameterization of the model space is mostly three to four layers over a half-space: where the shear-wave velocity of the uppermost layers can follow uniform or power-law dependence with depth. The shear-wave velocity profiles derived by inversion agree with shear-wave velocity profiles provided by borehole surveys at approximately 80% of the sites.
Tsunami early warning (TEW) is a challenging task as a decision has to be made within few minutes on the basis of incomplete and error-prone data. Deterministic warning systems have difficulties in integrating and quantifying the intrinsic uncertainties. In contrast, probabilistic approaches provide a framework that handles uncertainties in a natural way. Recently, we have proposed a method using Bayesian networks (BNs) that takes into account the uncertainties of seismic source parameter estimates in TEW. In this follow-up study, the method is applied to 10 recent large earthquakes offshore Sumatra and tested for its performance. We have evaluated both the general model performance given the best knowledge we have today about the source parameters of the 10 events and the corresponding response on seismic source information evaluated in real-time. We find that the resulting site-specific warning level probabilities represent well the available tsunami wave measurements and observations. Difficulties occur in the real-time tsunami assessment if the moment magnitude estimate is severely over- or underestimated. In general, the probabilistic analysis reveals a considerably large range of uncertainties in the near-field TEW. By quantifying the uncertainties the BN analysis provides important additional information to a decision maker in a warning centre to deal with the complexity in TEW and to reason under uncertainty.
Salt diapirs are common features of sedimentary basins. If close to the surface, they can bear a significant hazard due to possible dissolution sinkholes, karst formation and collapse dolines or their influence on ground water chemistry. We investigate the potential of ambient vibration techniques to map the 3-D roof morphology of shallow salt diapirs. Horizontal-to-vertical (H/V) spectral peaks are derived at more than 900 positions above a shallow diapir beneath the city area of Hamburg, Germany, and are used to infer the depth of the first strong impedance contrast. In addition, 15 small-scale array measurements are conducted at different positions in order to compute frequency-dependent phase velocities of Rayleigh waves between 0.5 and 25 Hz. The dispersion curves are inverted together with the H/V peak frequency to obtain shear-wave velocity profiles. Additionally, we compare the morphology derived from H/V and array measurements to borehole lithology and a gravity-based 3-D model of the salt diapir. Both methods give consistent results in agreement with major features indicated by the independent data. An important result is that H/V and array measurements are better suited to identify weathered gypsum caprocks or gypsum floaters, while gravity-derived models better sample the interface between sediments and homogeneous salt. We further investigate qualitatively the influence of the 3-D subsurface topography of the salt diapir on the validity of local 1-D inversion results from ambient vibration dispersion curve inversion.
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.
Ambient vibration measurements with small, temporary arrays that produce estimates of surface wave dispersion have become increasingly popular as a low-cost, non-invasive tool for site characterisation. An important requirement for these measurements to be meaningful, however, is the temporal consistency and repeatability of the resulting dispersion and spatial autocorrelation curve estimates. Data acquired within several European research projects (NERIES task JRA4, SESAME, and other multinational experiments) offer the chance to investigate the variability of the derived data products. The dataset analysed here consists of repeated array measurements, with several years of time elapsed between them. The measurements were conducted by different groups in different seasons, using different instrumentations and array layouts, at six sites in Greece and Italy. Ambient vibration amplitude spectra and locations of dominant sources vary between the two measurements at each location. Still, analysis indicates that this does not influence the derived dispersion information, which is stable in time and neither influenced by the instrumentation nor the analyst. The frequency range over which the dispersion curves and spatial autocorrelation curves can be reliably estimated depends on the array dimensions (minimum and maximum aperture) used in the specific deployment, though, and may accordingly vary between the repeated experiments. The relative contribution of Rayleigh and Love waves to the wavefield can likewise change between repeated measurements. The observed relative contribution of Rayleigh waves is generally at or below 50%, with especially low values for the rural sites. Besides, the visibility of higher modes depends on the noise wavefield conditions. The similarity of the dispersion and autocorrelation curves measured at each site indicates that the curves are stable, mainly determined by the sub-surface structure, and can thus be used to derive velocity information with depth. Differences between velocity models for the same site derived from independently determined dispersion and autocorrelation curves-as observed in other studies-are consequently not adequately explained by uncertainties in the measurement part.
Earthquake rupture length and width estimates are in demand in many seismological applications. Earthquake magnitude estimates are often available, whereas the geometrical extensions of the rupture fault mostly are lacking. Therefore, scaling relations are needed to derive length and width from magnitude. Most frequently used are the relationships of Wells and Coppersmith (1994) derived on the basis of a large dataset including all slip types with the exception of thrust faulting events in subduction environments. However, there are many applications dealing with earthquakes in subduction zones because of their high seismic and tsunamigenic potential. There are no well-established scaling relations for moment magnitude and length/width for subduction events. Within this study, we compiled a large database of source parameter estimates of 283 earthquakes. All focal mechanisms are represented, but special focus is set on (large) subduction zone events, in particular. Scaling relations were fitted with linear least-square as well as orthogonal regression and analyzed regarding the difference between continental and subduction zone/oceanic relationships. Additionally, the effect of technical progress in earthquake parameter estimation on scaling relations was tested as well as the influence of different fault mechanisms. For a given moment magnitude we found shorter but wider rupture areas of thrust events compared to Wells and Coppersmith (1994). The thrust event relationships for pure continental and pure subduction zone rupture areas were found to be almost identical. The scaling relations differ significantly for slip types. The exclusion of events prior to 1964 when the worldwide standard seismic network was established resulted in a remarkable effect on strike-slip scaling relations: the data do not show any saturation of rupture width of strike- slip earthquakes. Generally, rupture area seems to scale with mean slip independent of magnitude. The aspect ratio L/W, however, depends on moment and differs for each slip type.
Shallowly situated evaporites in built-up areas are of relevance for urban and cultural development and hydrological regulation. The hazard of sinkholes, subrosion depressions and gypsum karst is often difficult to evaluate and may quickly change with anthropogenic influence. The geophysical exploration of evaporites in metropolitan areas is often not feasible with active industrial techniques. We collect and combine different passive geophysical data as microgravity, ambient vibrations, deformation and hydrological information to study the roof morphology of shallow evaporites beneath Hamburg, Northern Germany. The application of a novel gravity inversion technique leads to a 3-D depth model of the salt diapir under study. We compare the gravity-based depth model to pseudo-depths from H/V measurements and depth estimates from small-scale seismological array data. While the general range and trend of the diapir roof is consistent, a few anomalous regions are identified where H/V pseudo-depths indicate shallower structures not observed in gravity or array data. These are interpreted by shallow residual caprock floaters and zones of increased porosity. The shallow salt structure clearly correlates with a relative subsidence in the order of 2 mm yr(-1). The combined interpretation of roof morphology, yearly subsidence rates, chemical analyses of groundwater and of hydraulic head in aquifers indicates that the salt diapir beneath Hamburg is subject to significant ongoing dissolution that may possibly affect subrosion depressions, sinkhole distribution and land usage. The combined analysis of passive geophysical data may be exemplary for the study of shallow evaporites beneath other urban areas.
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.
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.
Rapid and robust characterization of large earthquakes in terms of their spatial extent and temporal duration is of high importance for disaster mitigation and early warning applications. Backtracking of seismic P-waves was successfully used by several authors to image the rupture process of the great Sumatra earthquake (26.12.2004) using short period and broadband arrays. We follow here an approach of Walker et al. to backtrack and stack broadband waveforms from global network stations using traveltimes for a global Earth model to obtain the overall spatio-temporal development of the energy radiation of large earthquakes in a quick and robust way. We present results for selected events with well studied source processes (Kokoxili 14.11.2001, Tokachi-Oki 25.09.2003, Nias 28.03.2005). Further, we apply the technique in a semi-real time fashion to broadband data of earthquakes with a broadband magnitude >= 7 (roughly corresponding to Mw 6.5). Processing is based on first automatic detection messages from the GEOFON extended virtual network (GEVN).
An der Universität Potsdam wird seit 2008 ein automatisiertes Verfahren angewandt, um Bruchparamter großer Erdbeben in quasi-Echtzeit, d.h. wenige Minuten nachdem sich das Beben ereignet hat, zu bestimmen und der Öffentlichkeit via Internet zur Verfügung zu stellen. Es ist vorgesehen, das System in das Deutsch-Indonesische Tsunamifrühwarnsystem (GITEWS) zu integrieren, für das es speziell konfiguriert ist. Wir bestimmen insbesondere die Dauer und die Ausdehnung des Erdbebens, sowie dessen Bruchgeschwindigkeit und -richtung. Dabei benutzen wir die Seismogramme der zuerst eintreffenden P Wellen vom Breitbandstationen in teleseimischer Entfernung vom Beben sowie herkömmliche Arrayverfahren in teilweise modifizierter Form. Die Semblance wir als Ähnlichkeitsmaß verwendet, um Seismogramme eines Stationsnetzes zu vergleichen. Im Falle eines Erdbebens ist die Semblance unter Berücksichtigung des Hypozentrums zur Herdzeit und während des Bruchvorgangs deutlich zeitlich und räumlich erhöht und konzentriert. Indem wir die Ergebnisse verschiedener Stationsnetzwerke kombinieren, erreichen wir Unabhängigkeit von der Herdcharakteristik und eine raum-zeitliche Auflösung, die es erlaubt die o.g. Parameter abzuleiten. In unserem Beitrag skizzieren wir die Methode. Anhand der beiden M8.0 Benkulu Erdbeben (Sumatra, Indonesien) vom 12.09.2007 und dem M8.0 Sichuan Ereignis (China) vom 12.05.2008 demonstrieren wir Auflösungsmöglichkeiten und vergleichen die Ergebnisse der automatisierten Echtzeitanwendung mit nachträglichen Berechnungen. Weiterhin stellen wir eine Internetseite zur Verfügung, die die Ergebnisse präsentiert und animiert. Diese kann z.B. in geowissenschaftlichen Einrichtungen an Computerterminals gezeigt werden. Die Internetauftritte haben die folgenden Adressen: http://www.geo.uni-potsdam.de/arbeitsgruppen/Geophysik_Seismologie/forschung/ruptrack/openday http://www.geo.uni-potsdam.de/arbeitsgruppen/Geophysik_Seismologie/forschung/ruptrack
We use seismic array methods (semblance analysis) to image areas of seismic energy release in the Sunda Arc region and world-wide. Broadband seismograms at teleseismic distances (30° ≤ Δ ≤ 100°) are compared at several subarrays. Semblance maps of different subarrays are multiplied. High semblance tracked over long time (10s of second to minutes) and long distances indicate locations of earthquakes. The method allows resolution of rupture characteristics important for tsunami early warning: start and duration, velocity and direction, length and area. The method has been successfully applied to recent and historic events (M>6.5) and is now operational in real time. Results are obtained shortly after source time, see http://www.geo.uni-potsdam.de/Forschung/Geophysik/GITEWS/tsunami.htm). Comparison of manual and automatic processing are in good agreement. Computational effort is small. Automatic results may be obtained within 15 - 20 minutes after event occurrence.
We study the rupture propagation of the 2008/05/12 Ms8.0 Wenchuan Earthquake. We apply array techniques such as semblance vespagram analysis to P waves recorded at seismic broadband station within 30-100° epicentral distance. By combination of multiple large aperture station groups spatial and temporal resolution is enhanced and problems due source directivity and source mechanism are avoided. We find that seismic energy was released for at least 110 s. Propagating unilaterally at sub-shear rupture velocity of about 2.5 km/s in NE direction, the earthquake reaches a lateral extent of more than 300 km. Whereas high semblance during within 70 s from rupture start indicates simple propagation more complex source processes are indicated thereafter by decreases coherency in seismograms. At this stage of the event coherency is low but significantly above noise level. We emphasize that first result of our computations where obtain within 30 minutes after source time by using an atomized algorithm. This procedure has been routinely and globally applied to major earthquakes. Results are made public through internet.
The spatio-temporal evolution of the three recent tsunamogenic earthquakes (TsE) off-coast N-Sumatra (Mw9.3), 28/03/2005 (Mw8.5) off-coast Nias, on 17/07/2006 (Mw7.7) off-coast Java. Start time, duration, and propagation of the rupture are retrieved. All parameters can be obtained rapidly after recording of the first-arrival phases in near-real time processing. We exploit semblance analysis, backpropagation and broad-band seismograms within 30°-95° distance. Image enhancement is reached by stacking the semblance of arrays within different directions. For the three events, the rupture extends over about 1150, 150, and 200km, respectively. The events in 2004, 2005, and 2006 had source durations of at least 480s, 120s, and 180s, respectively. We observe unilateral rupture propagation for all events except for the rupture onset and the Nias event, where there is evidence for a bilateral start of the rupture. Whereas average rupture speed of the events in 2004 and 2005 is in the order of the S-wave speed (≈2.5-3km/s), unusually slow rupturing (≈1.5 km/s) is indicated for the July 2006 event. For the July 2006 event we find rupturing of a 200 x 100 km wide area in at least 2 phases with propagation from NW to SE. The event has some characteristics of a circular rupture followed by unilateral faulting with change in slip rate. Fault area and aftershock distribution coincide. Spatial and temporal resolution are frequency dependent. Studies of a Mw6.0 earthquake on 2006/09/21 and one synthetic source show a ≈1° limit in resolution. Retrieved source area, source duration as well as peak values for semblance and beam power generally increase with the size of the earthquake making possible an automatic detection and classification of large and small earthquakes.
The Mw=7.7 tsunamogenic earthquake (TsE) on 17 July 2006, 08:19:28 shock the Indian Ocean at about 15 km depth off-coast Java, Indonesia. It caused a local tsunami with wave heights exceeding 2 m. The death toll reached several hundred. Thousands of people were displaced. By means of standard array methods, we have investigated the propagation and the extent of the rupture front of the causative earthquake. Waveform similarity is expressed by means of the semblance. We back-propagate the semblance for first-arrival phases recorded at broad-band stations within teleseismic distances (30°-95°). Image enhancement is realised by stacking the semblance of 8 arrays within different epicentral and azimuthal directions. From teleseismic observations we find rupturing of a 200 x 100 km wide area in at least 2 phases with propagation from NW to SE and source duration >125 s. The event has some characteristics of a circular rupture followed by unilateral faulting with change in slip rate. Unusually slow rupturing (≈1.5 km/s) is indicated. Fault area and aftershock distribution coincide. Spatial and temporal resolution are frequency dependent. Studies of a Mw6.0 earthquake on 2006/09/21 and one synthetic source show a ≈1° limit in resolution. Retrieved source area, source duration as well as peak values for semblance and beam power increase with the size of the earthquake making possible an automatic detection and classification of large and small earthquakes.
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.
Interdisziplinäres Zentrum für Musterdynamik und Angewandte Fernerkundung Workshop vom 9. - 10. Februar 2006