ABSTRACT The 2020–2023 southwestern Puerto Rico seismic sequence, still ongoing in
2023, is remarkable for its multiple‐fault rupture complexity and elevated aftershock …

Using P‐wave seismograms, we trained a seismic source classifier using a Convolutional
Neural Network. We trained for three classes: earthquake P‐wave, underground nuclear …

Fluid injection associated with oil field operations can induce earthquakes through
perturbation to the balance between fault strength and tectonic stress. Induced seismicity …

We use machine-learning and cross-correlation techniques to enhance earthquake
detectability by two magnitude units for the earthquake sequence near Musreau Lake …

Given the recent developments in machine-learning technology, its application has rapidly
progressed in various fields of earthquake seismology, achieving great success. Here, we …

Abstract After the 2011 M w 9.0 Tohoku earthquake, seismicity became extremely active
throughout Japan. Despite enormous efforts to detect the large number of earthquakes …

The detection and picking of seismic waves are the first step toward earthquake catalog
building, earthquake monitoring, and seismic hazard management. Recent advances in …

This study evaluates EQTransformer, a deep learning model, for earthquake detection and
phase picking using seismic data from the Southern Alps, New Zealand. Using a robust …

In land‐based seismology, modern automatic earthquake detection and phase picking
algorithms have already proven to outperform classic approaches, resulting in more …

The development of seismic event catalogs has undergone a revolution due to the
combination of increasingly available continuous waveform data with advanced methods for …