Visual Event Screening of Continuous Seismic Data by Supersonograms

We present a new visualization method for human inspection of seismic data called supersonograms, which maximizes the amount of time and stations visible on screen while retaining the possibility to detect short and low-signal to noise ratio (SNR) signals. This visualization approach is integrated into a seismological software suite used in the seismic aftershock monitoring system (SAMS) of Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO) on-site inspections (OSI) to detect suspicious events eventually representing aftershocks from an underground nuclear explosion (UNE). During an OSI, huge amounts of continuous waveform data accumulate from up to 50 six-channel mini-arrays covering an inspection area of 1,000 square kilometers. Sought-after events can have magnitude as low as \(\hbox{M}_{\rm L}\,{-2.0}\) and duration of just a few seconds, which makes it particularly hard to discover them in large, noisy datasets. Therefore, the data visualization is based on nonlinearly scaled, noise-adapted spectrograms, i.e., sonograms, which help to distinguish weak signal energy from stationary background noise. Four single-trace sonograms per mini-array can be combined into supersonograms, since the array aperture is small and sonograms suppress differences of local site noise, allowing an analyst to check array-wide signal coherence quickly. In this paper, we present the supersonograms and the software on the basis of a dataset from a creeping, inhabited landslide in Austria where the same station layout is used as in an OSI. Detected signals are fracture processes in the sedimentary landslide, i.e., slidequakes, with \(\hbox{M}_{\rm L}\,{-0.5} \,\hbox{\,to}\,{-2.5}\) between July 2009 and July 2011. These signals are comparable in magnitude and duration to expected weak UNE aftershocks.