[HTML][HTML] Machine learning in microseismic monitoring
The confluence of our ability to handle big data, significant increases in instrumentation
density and quality, and rapid advances in machine learning (ML) algorithms have placed …
density and quality, and rapid advances in machine learning (ML) algorithms have placed …
Current challenges in monitoring, discrimination, and management of induced seismicity related to underground industrial activities: A European perspective
Due to the deep socioeconomic implications, induced seismicity is a timely and increasingly
relevant topic of interest for the general public. Cases of induced seismicity have a global …
relevant topic of interest for the general public. Cases of induced seismicity have a global …
Earthquake transformer—an attentive deep-learning model for simultaneous earthquake detection and phase picking
Earthquake signal detection and seismic phase picking are challenging tasks in the
processing of noisy data and the monitoring of microearthquakes. Here we present a global …
processing of noisy data and the monitoring of microearthquakes. Here we present a global …
Machine learning in seismology: Turning data into insights
Q Kong, DT Trugman, ZE Ross… - Seismological …, 2019 - pubs.geoscienceworld.org
This article provides an overview of current applications of machine learning (ML) in
seismology. ML techniques are becoming increasingly widespread in seismology, with …
seismology. ML techniques are becoming increasingly widespread in seismology, with …
Convolutional neural network for earthquake detection and location
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 …
catalogs to improve seismic hazard assessment. Over the last decades, the volume of …
STanford EArthquake Dataset (STEAD): A global data set of seismic signals for AI
Seismology is a data rich and data-driven science. Application of machine learning for
gaining new insights from seismic data is a rapidly evolving sub-field of seismology. The …
gaining new insights from seismic data is a rapidly evolving sub-field of seismology. The …
Assessing whether the 2017 Mw 5.4 Pohang earthquake in South Korea was an induced event
The moment magnitude (M w) 5.4 Pohang earthquake, the most damaging event in South
Korea since instrumental seismic observation began in 1905, occurred beneath the Pohang …
Korea since instrumental seismic observation began in 1905, occurred beneath the Pohang …
Clustering earthquake signals and background noises in continuous seismic data with unsupervised deep learning
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 …
abilities for analysis, since to date, such datasets have been analyzed in a human-expert …
CRED: A deep residual network of convolutional and recurrent units for earthquake signal detection
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 …
algorithm should be sensitive to small and weak events with a variety of waveform shapes …
Searching for hidden earthquakes in Southern California
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 …
much more often than larger events. Earthquake catalogs are thus dominated by small …