Publications

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Since May 2010, we have been recording continuous seismic data at Sandia's FACT site. The collected signals provide us with a realistic archive for testing algorithms under development for local monitoring of explosive testing. Numerous small explosive tests are routinely conducted around Kirtland AFB by different organizations. Our goal is to identify effective methods for distinguishing these events from normal daily activity on and near the base, such as vehicles, aircraft, and storms. In this report, we describe the recording system, and present some observations of the varying ambient noise conditions at FACT. We present examples of various common, non-explosive, sources. Next we show signals from several small explosions, and discuss their characteristic features.

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The relationship between explosive yield and seismic magnitude has been extensively studied for underground nuclear tests larger than about 1 kt. For monitoring smaller tests over local ranges (within 200 km), we need to know whether the available formulas can be extrapolated to much lower yields. Here, we review published information on amplitude decay with distance, and on the seismic magnitudes of industrial blasts and refraction explosions in the western U. S. Next we measure the magnitudes of some similar shots in the northeast. We find that local magnitudes ML of small, contained explosions are reasonably consistent with the magnitude-yield formulas developed for nuclear tests. These results are useful for estimating the detection performance of proposed local seismic networks.

We have used Matlab and Google Earth to construct a prototype application for modeling the performance of local seismic networks for monitoring small, contained explosions. Published equations based on refraction experiments provide estimates of peak ground velocities as a function of event distance and charge weight. Matlab routines implement these relations to calculate the amplitudes across a network of stations from sources distributed over a geographic grid. The amplitudes are then compared to ambient noise levels at the stations, and scaled to determine the smallest yield that could be detected at each source location by a specified minimum number of stations. We use Google Earth as the primary user interface, both for positioning the stations of a hypothetical local network, and for displaying the resulting detection threshold contours.

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To make use of some portions of the National Nuclear Security Administration (NNSA) Knowledge Base (KB) for which no current operational monitoring applications were available, Sandia National Laboratories have developed a set of prototype regional analysis tools (MatSeis, EventID Tool, CodaMag Tool, PhaseMatch Tool, Dendro Tool, Infra Tool, etc.), and we continue to maintain and improve these. Individually, these tools have proven effective in addressing specific monitoring tasks, but collectively their number and variety tend to overwhelm KB users, so we developed another application - the KB Navigator - to launch the tools and facilitate their use for real monitoring tasks. The KB Navigator is a flexible, extensible java application that includes a browser for KB data content, as well as support to launch any of the regional analysis tools. In this paper, we will discuss the latest versions of KB Navigator and the regional analysis tools, with special emphasis on the new overarching inter-tool communication methodology that we have developed to make the KB Navigator and the tools function together seamlessly. We use a peer-to-peer communication model, which allows any tool to communicate with any other. The messages themselves are passed as serialized XML, and the conversion from Java to XML (and vice versa) is done using Java Architecture for XML Binding (JAXB).

To improve the nuclear event monitoring capability of the U.S., the NNSA Ground-based Nuclear Explosion Monitoring Research & Engineering (GNEM R&E) program has been developing a collection of products known as the Knowledge Base (KB). Though much of the focus for the KB has been on the development of calibration data, we have also developed numerous software tools for various purposes. The Matlab-based MatSeis package and the associated suite of regional seismic analysis tools were developed to aid in the testing and evaluation of some Knowledge Base products for which existing applications were either not available or ill-suited. This presentation will provide brief overviews of MatSeis and each of the tools, emphasizing features added in the last year. MatSeis was begun in 1996 and is now a fairly mature product. It is a highly flexible seismic analysis package that provides interfaces to read data from either flatfiles or an Oracle database. All of the standard seismic analysis tasks are supported (e.g. filtering, 3 component rotation, phase picking, event location, magnitude calculation), as well as a variety of array processing algorithms (beaming, FK, coherency analysis, vespagrams). The simplicity of Matlab coding and the tremendous number of available functions make MatSeis/Matlab an ideal environment for developing new monitoring research tools (see the regional seismic analysis tools below). New MatSeis features include: addition of evid information to events in MatSeis, options to screen picks by author, input and output of origerr information, improved performance in reading flatfiles, improved speed in FK calculations, and significant improvements to Measure Tool (filtering, multiple phase display), Free Plot (filtering, phase display and alignment), Mag Tool (maximum likelihood options), and Infra Tool (improved calculation speed, display of an F statistic stream). Work on the regional seismic analysis tools (CodaMag, EventID, PhaseMatch, and Dendro) began in 1999 and the tools vary in their level of maturity. All rely on MatSeis to provide necessary data (waveforms, arrivals, origins, and travel time curves). CodaMag Tool implements magnitude calculation by scaling to fit the envelope shape of the coda for a selected phase type (Mayeda, 1993; Mayeda and Walter, 1996). New tool features include: calculation of a yield estimate based on the source spectrum, display of a filtered version of the seismogram based on the selected band, and the output of codamag data records for processed events. EventID Tool implements event discrimination using phase ratios of regional arrivals (Hartse et al., 1997; Walter et al., 1999). New features include: bandpass filtering of displayed waveforms, screening of reference events based on SNR, multivariate discriminants, use of libcgi to access correction surfaces, and the output of discrim{_}data records for processed events. PhaseMatch Tool implements match filtering to isolate surface waves (Herrin and Goforth, 1977). New features include: display of the signal's observed dispersion and an option to use a station-based dispersion surface. Dendro Tool implements agglomerative hierarchical clustering using dendrograms to identify similar events based on waveform correlation (Everitt, 1993). New features include: modifications to include arrival information within the tool, and the capability to automatically add/re-pick arrivals based on the picked arrivals for similar events.

The International Monitoring System (IMS) proposed for verifying compliance with the Comprehensive Nuclear-Test-Ban Treaty will include an infrasound network for detecting and identifying explosions in the atmosphere. As is the case with seismic monitoring, data collected from historic events of interest are vital for improving infrasonic monitoring capabilities. Unfortunately, however, infrasonic recordings of such events are rare and thus any additional data sets that might be available should be pursued. Towards that end, we will digitize, as a result of the ROA01-38 award, paper records and extract from 9-track tapes several unique data sets from Sandia National Laboratories and Los Alamos National Laboratory that have not been available to the monitoring community. These data sets include recordings of surface and atmospheric explosions representing different yields, altitudes and weather conditions, as well as bolides and other natural phenomena that may be detected by the international infrasound monitoring network. Once the data are all in digital form, we will convert them to the standard CSS format, including event and station information. The complete set of database tables and binary waveform files will be the ultimate product of our work.

In order to exploit the information on surface wave propagation that is stored in large seismic event datasets, Sandia and Lawrence Livermore National Laboratories have developed a MatSeis interface for performing phase-matched filtering of Rayleigh arrivals. MatSeis is a Matlab-based seismic processing toolkit which provides graphical tools for analyzing seismic data from a network of stations. Tools are available for spectral and polarization measurements, as well as beam forming and f-k analysis with array data, to name just a few. Additionally, one has full access to the Matlab environment and any functions available there. Previously the authors reported the development of new MatSeis tools for calculating regional discrimination measurements. The first of these performs Lg coda analysis as developed by Mayeda and coworkers at Lawrence Livermore National Laboratory. A second tool measures regional phase amplitude ratios for an event and compares the results to ratios from known earthquakes and explosions. Release 1.5 of MatSeis includes the new interface for the analysis of surface wave arrivals. This effort involves the use of regionalized dispersion models from a repository of surface wave data and the construction of phase-matched filters to improve surface wave identification, detection, and magnitude calculation. The tool works as follows. First, a ray is traced from source to receiver through a user-defined grid containing different group velocity versus period values to determine the composite group velocity curve for the path. This curve is shown along with the upper and lower group velocity bounds for reference. Next, the curve is used to create a phase-matched filter, apply the filter, and show the resultant waveform. The application of the filter allows obscured Rayleigh arrivals to be more easily identified. Finally, after screening information outside the range of the phase-matched filter, an inverse version of the filter is applied to obtain a cleaned raw waveform which can be used for amplitude measurements. Because all the MatSeis tools have been written as Matlab functions, they can be easily modified to experiment with different processing details. The performance of the propagation models can be evaluated using any event available in the repository of surface wave events.