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Is Classifying Secondary Seismic Signals Scalable and Automatable?

Physical Sciences


Seismic waves from large-magnitude earthquakes sometime trigger small secondary earthquakes or tectonic tremor. These secondary signals are important to observe and study because their occurrence reflects on the state of stress of the subsurface, which is important for hazard assessment. Here we first report on how individual inspection by a human of over a thousand three-track time series leads to a few dozen identifications of such secondary signals. Secondly, we explore computational ways to scale this problem and make it more efficient. For example, we compute a signal to noise ratio and utilize a decision-tree algorithm to rank the time series for inspection.

Vivian Tang, et al.

Earth and Planetary Science

April, 2018

DOI: 10.21985/N2ND76