Exploring the limits of waveform correlation event detection as applied to three earthquake aftershock sequences.
Swarms of earthquakes and/or aftershock sequences can dramatically increase the level of seismicity in a region for a period of time lasting from days to months, depending on the swarm or sequence. Such occurrences can provide a large amount of useful information to seismologists. For those who monitor seismic events for possible nuclear explosions, however, these swarms/sequences are a nuisance. In an explosion monitoring system, each event must be treated as a possible nuclear test until it can be proven, to a high degree of confidence, not to be. Seismic events recorded by the same station with highly correlated waveforms almost certainly have a similar location and source type, so clusters of events within a swarm can quickly be identified as earthquakes. We have developed a number of tools that can be used to exploit the high degree of waveform similarity expected to be associated with swarms/sequences. Dendro Tool measures correlations between known events. The Waveform Correlation Detector is intended to act as a detector, finding events in raw data which correlate with known events. The Self Scanner is used to find all correlated segments within a raw data steam and does not require an event library. All three techniques together provide an opportunity to study the similarities of events in an aftershock sequence in different ways. To comprehensively characterize the benefits and limits of waveform correlation techniques, we studied 3 aftershock sequences, using our 3 tools, at multiple stations. We explored the effects of station distance and event magnitudes on correlation results. Lastly, we show the reduction in detection threshold and analyst workload offered by waveform correlation techniques compared to STA/LTA based detection. We analyzed 4 days of data from each aftershock sequence using all three methods. Most known events clustered in a similar manner across the toolsets. Up to 25% of catalogued events were found to be a member of a cluster. In addition, the Waveform Correlation Detector and Self Scanner identified significant numbers of new events that were not in either the EDR or regional catalogs, showing a lowering of the detection threshold. We extended our analysis to study the effect of distance on correlation results by applying the analysis tools to multiple stations along a transect of nearly constant azimuth when possible. We expected the number of events found via correlation would drop off as roughly 1/r2, where r is the distance from mainshock to station. However, we found that regional geological conditions influenced the performance of a given station more than distance. For example, for one sequence we clustered 25% of events at the nearest station to the mainshock (34 km), while our performance dropped to 2% at a station 550 km distant. However, we matched our best performance (25% clustering) at a station 198 km distant.
- Research Organization:
- Sandia National Laboratories (SNL), Albuquerque, NM, and Livermore, CA (United States)
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- AC04-94AL85000
- OSTI ID:
- 1013245
- Report Number(s):
- SAND2010-3107C; TRN: US201110%%562
- Resource Relation:
- Conference: Proposed for presentation at the Seismological Society of America Annual Meeting held April 20-23, 2010 in Portland, OR.
- Country of Publication:
- United States
- Language:
- English
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