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Title: The Iterative Processing Framework: A New Paradigm for Automatic Event Building

Journal Article · · Bulletin of the Seismological Society of America
DOI: https://doi.org/10.1785/0120190093 · OSTI ID:1575269
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  1. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
  2. ENSCO, Inc., Springfield, VA (United States)

Abstract In a traditional data-processing pipeline, waveforms are acquired, a detector makes the signal detections (i.e., arrival times, slownesses, and azimuths) and passes them to an associator. The associator then links the detections to the fitting-event hypotheses to generate an event bulletin. Most of the time, this traditional pipeline requires substantial human-analyst involvement to improve the quality of the resulting event bulletin. For the year 2017, for instance, International Data Center (IDC) analysts rejected about 40% of the events in the automatic bulletin and manually built 30% of the legitimate events. Here, we introduce an iterative processing framework (IPF) that includes a new data-processing module that incorporates automatic analyst behaviors (auto analyst [AA]) into the event-building pipeline. In the proposed framework, through an iterative process, the AA takes over many of the tasks traditionally performed by human analysts. These tasks can be grouped into two major processes: (1) evaluating small events with a low number of location-defining arrival phases to improve their formation; and (2) scanning for and exploiting unassociated arrivals to form potential events missed by previous association runs. To test the proposed framework, we processed a two-week period (15–28 May 2010) of the signal-detections dataset from the IDC. Comparison with an expert analyst-reviewed bulletin for the same time period suggests that IPF performs better than the traditional pipelines (IDC and baseline pipelines). The majority of the additional events built by the AA are low-magnitude events that were missed by these traditional pipelines. The AA also adds additional signal detections to existing events, which saves analyst time, even if the event locations are not significantly affected.

Research Organization:
Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
Sponsoring Organization:
USDOE National Nuclear Security Administration (NNSA)
Grant/Contract Number:
AC04-94AL85000; NA0003525
OSTI ID:
1575269
Report Number(s):
SAND--2019-4285J; 674752
Journal Information:
Bulletin of the Seismological Society of America, Journal Name: Bulletin of the Seismological Society of America Journal Issue: 6 Vol. 109; ISSN 0037-1106
Publisher:
Seismological Society of AmericaCopyright Statement
Country of Publication:
United States
Language:
English