Convolutional neural network for earthquake detection and location

  title={Convolutional neural network for earthquake detection and location},
  author={Thibaut Perol and Micha{\"e}l Gharbi and Marine A. Denolle},
  journal={Science Advances},
ConvNetQuake is the first neural network for detection and location of earthquakes from seismograms. The recent evolution of induced seismicity in Central United States calls for exhaustive catalogs to improve seismic hazard assessment. Over the last decades, the volume of seismic data has increased exponentially, creating a need for efficient algorithms to reliably detect and locate earthquakes. Today’s most elaborate methods scan through the plethora of continuous seismic records, searching… 

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Artificial neural network-based seismic detector

  • Jin WangT. Teng
  • Geology, Computer Science
    Bulletin of the Seismological Society of America
  • 1995

Earthquake detection through computationally efficient similarity search

FAST detected most (21 of 24) cataloged earthquakes and 68 uncataloged earthquakes in 1 week of continuous data from a station located near the Calaveras Fault in central California, achieving detection performance comparable to that of autocorrelation, with some additional false detections.

Hundreds of Earthquakes per Day: The 2014 Guthrie, Oklahoma, Earthquake Sequence

Online Material: Gutenberg–Richter plot, b ‐values and associated p ‐values, magnitudes and number of detections per day, and earthquake catalog. A remarkable increase in seismic activity in

Data space reduction, quality assessment and searching of seismograms: autoencoder networks for waveform data

A demonstration in which 512-point waveforms are compressed to 32-element encodings, and it is demonstrated that the mapping from data to encoding space, and its inverse, are well behaved, as required for many applications.

An Empirical Approach to Subspace Detection

Correlation methods have been used on mining‐induced seismicity, in nuclear test ban treaty verification research, and to understand tectonic tremor as a swarm of low‐frequency earthquakes.

A comparison of select trigger algorithms for automated global seismic phase and event detection

While no algorithm was clearly optimal under all source, receiver, path, and noise conditions tested, an STA/LTA algorithm incorporating adaptive window lengths controlled by nonstationary seismogram spectral characteristics was found to provide an output that best met the requirements of a global correlated event-detection and location system.

A 15 year catalog of more than 1 million low‐frequency earthquakes: Tracking tremor and slip along the deep San Andreas Fault

Low‐frequency earthquakes (LFEs) are small, rapidly recurring slip events that occur on the deep extensions of some major faults. Their collective activation is often observed as a semicontinuous

Injection-Induced Earthquakes

The current understanding of the causes and mechanics of earthquakes caused by human activity, including injection of wastewater into deep formations and emerging technologies related to oil and gas recovery, is reviewed.

Subspace Detectors: Theory

Broadband subspace detectors are introduced for seismological applications that require the detection of repetitive sources that produce similar, yet significantly variable seismic signals. Like