Seismic Detectors: The State-of-the-Art

Berger, Jon; Sax, Robert L.

doi:10.21236/ada099446

Cited by 12 publications

(4 citation statements)

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“…It is implemented in many online-detection algorithms, and its principles are described, for example, by Allen (1978Allen ( , 1982, Berger and Sax (1980), or Ruud and Husebye (1992). Detectors based on STA/LTA are mainly sensitive to a change in amplitude (energy); and therefore discrimination between P and S phases is critical, even if applied only to horizontal components.…”

Section: Sta/lta Detectormentioning

confidence: 99%

Automatic S-Wave Picker for Local Earthquake Tomography

Diehl

Deichmann

Kissling

et al. 2009

Bulletin of the Seismological Society of America

118

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High-resolution seismic tomography at local and regional scales requires large and consistent sets of arrival-time data. Algorithms combining accurate picking with an automated quality classification can be used for repicking waveforms and compiling large arrival-time data sets suitable for tomographic inversion. S-wave velocities represent a key parameter for petrological interpretation, improved hypocenter determination, as well as for seismic hazard models. In our approach, we combine three commonly used phase detection and picking methods in a robust S-wave picking procedure. Information from the different techniques provides an in situ estimate of timing uncertainty and of the reliability of the automatic phase identification. Automatic picks are compared against manually picked reference picks of selected earthquakes in the Alpine region. The average accuracy of automatic picks and their classification is comparable with the reference picks, although a higher number of picks is downgraded to lower quality classes by the automatic picker. In the production-mode, we apply the picker to a data set of 552 earthquakes in the Alps recorded at epicentral distances ≤ 150 km. The resulting data set includes about 2500 S phases with an upper error bound of 0.27 sec.

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Section: Sta/lta Detectormentioning

confidence: 99%

Automatic S-Wave Picker for Local Earthquake Tomography

Diehl

Deichmann

Kissling

et al. 2009

Bulletin of the Seismological Society of America

118

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“…This ratio is constantly updated as new data flows in, and a detection is declared when the ratio exceeds a threshold value. When the signal and the noise are Gaussian distributed, the STA/LTA method yields an optimal detector that strikes the optimal balance between Type I and Type II errors [4,5]. As explained in [6], seismic waves are non-Gaussian, and therefore higher order statistics (such as skewness and kurtosis) can be used to detect the onset of seismic waves [7,8,9].…”

Section: Estimation Of Arrival-timesmentioning

confidence: 99%

Exploring the Manifold of Seismic Waves: Application to the Estimation of Arrival-Times

Taylor,

Procopio,

Young

et al. 2010

Preprint

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We propose a new method to analyze seismic time series and estimate the arrival-times of seismic waves. Our approach combines two ingredients: the times series are first lifted into a high-dimensional space using time-delay embedding; the resulting phase space is then parametrized using a nonlinear method based on the eigenvectors of the graph Laplacian. We validate our approach using a dataset of seismic events that occurred in Idaho, Montana, Wyoming, and Utah, between 2005 and Our approach outperforms methods based on singular-spectrum analysis, wavelet analysis, and STA/LTA.

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“…The temporal separation of these peaks is then used to narrow the time window o ver which to search for the highest energy non-dispersive v alue which i s t h e n u s e d a s the trigger. All of the previously mentioned detectors are reviewed by Berger and Sax (1980) and some are discussed by Allen (1982).…”

Section: Previous Workmentioning

confidence: 99%

An automated local and regional seismic event detection and location system using waveform correlation

Withers

Aster

Young

1999

Bulletin of the Seismological Society of America

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We report on the development of an automated Local Waveform Correlation Event Detection System (LWCEDS) and its application to the New Mexico Tech Seismic Network. LWCEDS is an adaptation of a global system, WCEDS, a matched filtering algorithm for global Comprehensive Test Ban Treaty (CTBT) monitoring applications developed at Sandia National Laboratories and New Mexico Tech. Although the current CTBT monitoring system is based on teleseismic phase detection, effort is being placed on research to highlight specific areas of the globe for which local and regional seismic networks could be employed. An automated waveform correlation regional location system could also serve as a rapid alert and automated location system by providing magnitude and hypocenter information within a few minutes of the occurrence of a hazardous earthquake. In the LWCEDS algorithm, processed waveforms are correlated with theoretical travel-time envelopes, and a grid search is performed to identify the space-time solutions that yield the highest correlations. High correlation indicates that an event has occurred and that a good approximation to the correct origin time and hypocenter has been determined; explicit phase identification is not required. To avoid the large computational expense of calculating a complete correlation for each grid point, we use a laterally homogeneous velocity model and reformulate the problem into a single matrix multiplication and matrix assessment for each time step. LWCEDS has been successfully tested on a suite of local and regional seismic events selected to span the range of expected event quality. Preliminary results from our sparse network show typical epicentral errors of less than 3 km for local events and, with notable exceptions, to within 10 to 20 km for regional events. Similar results were obtained during an on-line experiment conducted to generate daily bulletins during the time period from 3 December 1996 through 7 January 1997. Data from 156 triggers were processed, including 33 teleseisms, 102 regional events (includes explosions), and 21 local earthquakes. Results from this expanded test set are encouraging but reveal the need for a method to mask or flag various electronic and telemetry spikes.

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Seismic Detectors: The State-of-the-Art

Abstract: The complex analytic signal. A modulated carrier f(t), its quadrature function F (t), and the associated complex analytic signal are ayl shown as functions of the real variable time (after Bracewell, 1965

Cited by 12 publications

References 0 publications

Automatic S-Wave Picker for Local Earthquake Tomography

Automatic S-Wave Picker for Local Earthquake Tomography

Exploring the Manifold of Seismic Waves: Application to the Estimation of Arrival-Times

An automated local and regional seismic event detection and location system using waveform correlation

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