Inspired by a popular song-matching app, Shazam, scientists have discovered a way to identify previously overlooked earthquakes in large databases of ground motion measurements.
Washington: Inspired by a popular song-matching app, Shazam, scientists have discovered a way to identify previously overlooked earthquakes in large databases of ground motion measurements.
They call their algorithm Fingerprint And Similarity Thresholding, or FAST, and it could transform how seismologists detect microquakes, temblors that don't pack enough punch to register as earthquakes when analyzed by conventional methods. While microquakes don't threaten buildings or people, monitoring them could help scientists predict how frequently, and where, larger quakes are likely to occur.
In the past decade or so, one of the major trends in seismology has been the use of waveform similarity to find weakly recorded earthquakes, said Greg Beroza from Stanford School of Earth, Energy & Environmental Sciences. The technique most commonly employed to do this, called template matching, functions by comparing an earthquake's seismic wave pattern against previously recorded wave signatures in a database.
The downsides of template matching are that it can be time-consuming and that it requires seismologists to have a clear idea of the signal they are looking for ahead of time.
The team believes the technology could be used in places like Oklahoma and Arkansas, where an increase in small quakes has been linked to hydraulic fracturing, or "fracking." FAST could help determine which areas are at risk for earthquakes.
The next step is to test the technology with multiple seismic stations over longer periods of time, something that could help researchers predict how often large, natural quakes will strike.
The study appears in Science Advances.