Using Waveform Correlation to Reduce Analyst Workload Due to Repeating Mining Blasts

Session: Leveraging Advanced Detection, Association and Source Characterization in Network Seismology [Poster]
Type: Poster
Date: 4/30/2020
Time: 08:00 AM
Room: Ballroom
Description: 

Numerous studies have shown that waveform correlation is effective in detecting similar waveforms from repeating seismic events such as aftershock sequences or mining blasts. Meanwhile, monitoring agencies have shown interest in adopting techniques to quickly and automatically characterize these types of events with the purpose of reducing the workload on analysts. In this presentation, we discuss our work on characterizing mining blasts. We present results from applying SeisCorr, a waveform correlation application developed at Sandia National Laboratories, to representative study regions and time periods for active mining as chosen by International Data Centre (IDC) staff. The regions selected for study are located in Wyoming and Northern Scandinavia; for each region, two one-week time periods were designated for processing. Our approach uses a year of waveform templates from International Monitoring System (IMS) array stations located near these regions to detect and identify blasts during the chosen time periods, where the IMS stations were chosen by IDC staff. We compare candidate events detected with our processing methods to the Reviewed Event Bulletin (REB) to develop an estimate of the potential reduction in analyst workload.

Presenting Author: Amy Sundermier

Authors