Optimized filtering of regional and teleseismic seismograms: results of maximizing SNR measurements from the wavelet transform and filter banks

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Development of a worldwide network to monitor seismic activity requires deployment of seismic sensors in areas which have not been well studied or may have from available recordings. Development and testing of detection and discrimination algorithms requires a robust representative set of calibrated seismic events for a given region. Utilizing events with poor signal-to-noise (SNR) can add significant numbers to usable data sets, but these events must first be adequately filtered. Source and path effects can make this a difficult task as filtering demands are highly varied as a function of distance, event magnitude, bearing, depth etc. For a given ... continued below

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13 p.

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Leach, R.R.; Schultz, C. & Dowla, F. July 15, 1997.

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Development of a worldwide network to monitor seismic activity requires deployment of seismic sensors in areas which have not been well studied or may have from available recordings. Development and testing of detection and discrimination algorithms requires a robust representative set of calibrated seismic events for a given region. Utilizing events with poor signal-to-noise (SNR) can add significant numbers to usable data sets, but these events must first be adequately filtered. Source and path effects can make this a difficult task as filtering demands are highly varied as a function of distance, event magnitude, bearing, depth etc. For a given region, conventional methods of filter selection can be quite subjective and may require intensive analysis of many events. In addition, filter parameters are often overly generalized or contain complicated switching. We have developed a method to provide an optimized filter for any regional or teleseismically recorded event. Recorded seismic signals contain arrival energy which is localized in frequency and time. Localized temporal signals whose frequency content is different from the frequency content of the pre-arrival record are identified using rms power measurements. The method is based on the decomposition of a time series into a set of time series signals or scales. Each scale represents a time-frequency band with a constant Q. SNR is calculated for a pre-event noise window and for a window estimated to contain the arrival. Scales with high SNR are used to indicate the band pass limits for the optimized filter.The results offer a significant improvement in SNR particularly for low SNR events. Our method provides a straightforward, optimized filter which can be immediately applied to unknown regions as knowledge of the geophysical characteristics is not required. The filtered signals can be used to map the seismic frequency response of a region and may provide improvements in travel-time picking, bearing estimation regional characterization, and event detection. Results are shown for a set of low SNR events as well as 92 regional and teleseismic events in the Middle East.

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13 p.

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OSTI as DE98051134

Other: FDE: PDF; PL:

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  • Research symposium on monitoring a comprehensive test ban treaty, Orlando, FL (United States), 23-25 Sep 1997

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  • Other: DE98051134
  • Report No.: UCRL-JC--127900
  • Report No.: CONF-970967--
  • Grant Number: W-7405-ENG-48
  • Office of Scientific & Technical Information Report Number: 610743
  • Archival Resource Key: ark:/67531/metadc693730

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  • July 15, 1997

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  • Aug. 14, 2015, 8:43 a.m.

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  • April 10, 2017, 1:29 p.m.

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Leach, R.R.; Schultz, C. & Dowla, F. Optimized filtering of regional and teleseismic seismograms: results of maximizing SNR measurements from the wavelet transform and filter banks, article, July 15, 1997; California. (digital.library.unt.edu/ark:/67531/metadc693730/: accessed August 20, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.