Applying Waveform Correlation to Aftershock Sequences Using a Global Sparse Network
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Agencies that monitor for underground nuclear tests are interested in techniques that automatically characterize earthquake aftershock sequences to reduce the human analyst effort required to produce high-quality event bulletins. Waveform correlation is effective in detecting similar seismic waveforms from repeating earthquakes, including aftershock sequences. We report the results of an experiment that uses waveform templates recorded by multiple stations of the Comprehensive Nuclear-Test-Ban Treaty International Monitoring System during the first twelve hours after a mainshock to detect and identify aftershocks that occur during the subsequent week. We discuss approaches for station and template selection, threshold setting, and event detection that are specialized for aftershock processing for a sparse, global network. We apply the approaches to three aftershock sequences to evaluate the potential for establishing a set of standards for aftershock waveform correlation processing that can be effective for operational monitoring systems with a sparse network. We compare candidate events detected with our processing methods to the Reviewed Event Bulletin of the International Data Center to develop an intuition about potential reduction in analyst workload.
- Research Organization:
- Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
- Sponsoring Organization:
- USDOE National Nuclear Security Administration (NNSA), Office of Defense Nuclear Nonproliferation (NA-20)
- DOE Contract Number:
- AC04-94AL85000; NA0003525
- OSTI ID:
- 1763210
- Report Number(s):
- SAND--2019-10184; 678925
- Country of Publication:
- United States
- Language:
- English
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