Using the DOE Knowledge Base for Special Event Analysis
The DOE Knowledge Base is a library of detailed information whose purpose is to support the United States National Data Center (USNDC) in its mission to monitor compliance with the Comprehensive Test Ban Treaty (CTBT). One of the important tasks which the USNDC must accomplish is to periodically perform detailed analysis of events of high interest, so-called "Special Events", to provide the national authority with information needed to make policy decisions. In this paper we investigate some possible uses of the Knowledge Base for Special Event Analysis (SEA), and make recommendations for improving Knowledge Base support for SEA. To analyze an event in detail, there are two basic types of data which must be used sensor-derived data (wave- forms, arrivals, events, etc.) and regiohalized contextual data (known sources, geological characteristics, etc.). Cur- rently there is no single package which can provide full access to both types of data, so for our study we use a separate package for each MatSeis, the Sandia Labs-developed MATLAB-based seismic analysis package, for wave- form data analysis, and ArcView, an ESRI product, for contextual data analysis. Both packages are well-suited to pro- totyping because they provide a rich set of currently available functionality and yet are also flexible and easily extensible, . Using these tools and Phase I Knowledge Base data sets, we show how the Knowledge Base can improve both the speed and the quality of SEA. Empirically-derived interpolated correction information can be accessed to improve both location estimates and associated error estimates. This information can in turn be used to identi~ any known nearby sources (e.g. mines, volcanos), which may then trigger specialized processing of the sensor data. Based on the location estimate, preferred magnitude formulas and discriminants can be retrieved, and any known blockages can be identified to prevent miscalculations. Relevant historic events can be identilled either by spatial proximity searches or through waveform correlation processing. The locations and waveforms of these events can then be made available for side-by-side comparison and processing. If synthetic modeling is thought to be warranted, a wide variety of rele- vant contextu~l information (e.g. crustal thickness and layering, seismic velocities, attenuation factors) can be retrieved and sent to the appropriate applications. Once formedj the synthetics can then be brought in for side-by-side comparison and fhrther processing. Based on our study, we make two general recommendations. First, proper inter-process communication between sensor data analysis software and contextual data analysis sofisvare should be developed. Second, some of the Knowl- edge Base data sets should be prioritized or winnowed to streamline comparison with observed quantities.
- Research Organization:
- Sandia National Laboratories (SNL), Albuquerque, NM, and Livermore, CA (United States)
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- AC04-94AL85000
- OSTI ID:
- 1058
- Report Number(s):
- SAND98-2349C; ON: DE00001058
- Resource Relation:
- Conference: 20th Annual Seismic Research Symposium on Monitoring a Comprehensive Test Ban Treaty (CTBT); Sante Fe, NM; 09/21-23/1998
- Country of Publication:
- United States
- Language:
- English
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