S U M M A R YIt has long been accepted that occurrences of a known signal are most effectively detected by cross-correlating the incoming data stream with a waveform template. Such matched signal detectors have received very little attention in the field of detection seismology because there are relatively few instances in which the form of an anticipated seismic signal is known a priori. Repeating events in highly confined geographical regions have been observed to produce very similar waveforms and good signals from events at a given site can be exploited to detect subsequent co-located events at lower magnitudes than would be possible using traditional power detectors. Even greater improvement in signal detectability can be achieved using seismic arrays; running correlation coefficients from single sensors can be stacked over an array or network to result in a network correlation coefficient displaying a significant array gain. If two events are co-located, the time separating the corresponding patterns in the wave train as indicated by the cross-correlation function is identical for all seismic stations and this property means that the correlation coefficient traces are coherent even when the waveforms are not. We illustrate the power of array-based waveform correlation using the 1997 August 16 Kara Sea event. The weak event that occurred 4 hr after the main event was barely detected using an STA/LTA detector on the SPITS array but is readily detected by signal matching on a single channel. The main event was also recorded by the far more distant NORSAR array but no conventional detection can be made for the second event. A clear detection is, however, made when the correlation coefficient traces are beamformed over all sensors of the array. We estimate the reduction in detection threshold of a test signal on a regional seismic array using waveform correlation by scaling down a master signal and immersing it into seismic noise. We show that, for this case, waveform correlation using a single channel detects signals of approximately 0.7 orders of magnitude lower than is possible using an STA/LTA detector on the array beam. Waveform matching on the full array provides an additional improvement of approximately 0.4 magnitude units. We describe a case study in which small seismic events at the Barentsburg coal mine on Spitsbergen were detected using the signals from a major rockburst as master waveforms. Many spurious triggers occurred in this study whereby short sections of signal exhibited coincidental similarity with unrelated incoming wave fronts. We demonstrate how such false alarms can almost always be identified and screened out automatically by performing frequency-wavenumber analysis upon the set of individual correlation coefficient traces.
Human activity causes vibrations that propagate into the ground as high-frequency seismic waves. Measures to mitigate the COVID-19 pandemic caused widespread changes in human activity, leading to a months-long reduction in seismic noise of up to 50%. The 2020 seismic noise quiet period is the longest and most prominent global anthropogenic seismic noise reduction on record. While the reduction is strongest at surface seismometers in populated areas, this seismic quiescence extends for many kilometers radially and hundreds of meters in depth. This provides an opportunity to detect subtle signals from subsurface seismic sources that would have been concealed in noisier times and to benchmark sources of anthropogenic noise. A strong correlation between seismic noise and independent measurements of human mobility suggests that seismology provides an absolute, real-time estimate of population dynamics.
SUMMARYIt has long been accepted that occurrences of a known signal are most effectively detected by cross-correlating the incoming data stream with a waveform template. Such matched signal detectors have received very little attention in the field of detection seismology because there are relatively few instances in which the form of an anticipated seismic signal is known a priori. Repeating events in highly confined geographical regions have been observed to produce very similar waveforms and good signals from events at a given site can be exploited to detect subsequent co-located events at lower magnitudes than would be possible using traditional power detectors. Even greater improvement in signal detectability can be achieved using seismic arrays; running correlation coefficients from single sensors can be stacked over an array or network to result in a network correlation coefficient displaying a significant array gain. If two events are co-located, the time separating the corresponding patterns in the wavetrain as indicated by the cross-correlation function is identical for all seismic stations and this property means that the correlation coefficient traces are coherent even when the waveforms are not. We illustrate the power of array-based waveform correlation using the 16 August 1997 Kara Sea event. The weak event which occurred four hours after the main event was barely detected using an STA/LTA detector on the SPITS array but is readily detected by signal matching on a single channel. The main event was also recorded by the far more distant NORSAR array but no conventional detection can be made for the second event. A clear detection is however made when the correlation coefficient traces are beamformed over all sensors of the array. We estimate the reduction in detection threshold of a test signal on a regional seismic array using waveform correlation by scaling down a master signal and immersing it into seismic noise. We show that, for this case, waveform correlation using a single channel detects signals of approximately 0.7 orders of magnitude lower than is possible using an STA/LTA detector on the array beam. Waveform matching on the full array provides an additional improvement of approximately 0.4 magnitude units. We describe a case study in which small seismic events at the Barentsburg coal mine on Spitsbergen were detected using the signals from a major rockburst as master waveforms. Many spurious triggers occurred in this study whereby short sections of signal exhibited coincidental similarity with unrelated incoming wavefronts. We demonstrate how such false alarms can almost always be identified and screened out automatically by performing frequency-wavenumber analysis upon the set of individual correlation coefficient traces.
Dynamic glacier activity is increasingly observed through passive seismic monitoring. We analysed near-regional-scale seismicity on the Arctic archipelago of Svalbard to identify seismic icequake signals and to study their spatialÁ temporal distribution within the 14-year period from 2000 until 2013. This is the first study that uses seismic data recorded on permanent broadband stations to detect and locate icequakes in different regions of Spitsbergen, the main island of the archipelago. A temporary local seismic network and direct observations of glacier calving and surging were used to identify icequake sources. We observed a high number of icequakes with clear spectral peaks between 1 and 8 Hz in different parts of Spitsbergen. Spatial clusters of icequakes could be associated with individual grounded tidewater glaciers and exhibited clear seasonal variability each year with more signals observed during the melt season. Locations at the termini of glaciers, and correlation with visual calving observations in situ at Kronebreen, a glacier in the Kongsfjorden region, show that these icequakes were caused dominantly by calving. Indirect evidence for glacier surging through increased calving seismicity was found in 2003 at Tunabreen, a glacier in central Spitsbergen. Another type of icequake was observed in the area of the Nathorstbreen glacier system. Seismic events occurred upstream of the glacier within a short time period between January and May 2009 during the initial phase of a major glacier surge. This study is the first step towards the generation and implementation of an operational seismic monitoring strategy for glacier dynamics in Svalbard.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.