Distributed acoustic sensing (DAS) is a new, relatively inexpensive technology that is rapidly
demonstrating its promise for recording earthquake waves and other seismic signals in a …

Deep-seated slow slip and tremor (SST), including slow slip events, episodic tremor and
slip, and low-frequency earthquakes, occur downdip of the seismogenic zone of numerous …

This article provides an overview of current applications of machine learning (ML) in
seismology. ML techniques are becoming increasingly widespread in seismology, with …

Abstract National Research Institute for Earth Science and Disaster Resilience (NIED)
integrated the land observation networks established since the 1995 Kobe earthquake with …

The continuously growing amount of seismic data collected worldwide is outpacing our
abilities for analysis, since to date, such datasets have been analyzed in a human-expert …

Earthquake signal detection is at the core of observational seismology. A good detection
algorithm should be sensitive to small and weak events with a variety of waveform shapes …

Earthquakes follow a well-known power-law size relation, with smaller events occurring
much more often than larger events. Earthquake catalogs are thus dominated by small …

Hydraulic fracturing has been inferred to trigger the majority of injection-induced
earthquakes in western Canada, in contrast to the Midwestern United States, where massive …

We apply machine learning to data sets from shear laboratory experiments, with the goal of
identifying hidden signals that precede earthquakes. Here we show that by listening to the …

Slow earthquakes represent an important conundrum in earthquake physics. While regular
earthquakes are catastrophic events with rupture velocities governed by elastic wave speed …