Conveners
O3.5 Analysis of Seismic, Hydroacoustic and Infrasound Monitoring Data
- Christos Saragiotis (CTBTO Preparatory Commission)
- Ronan Le Bras (Former CTBTO Preparatory Commission)
Deep learning (DL) has shown to be a powerful method for seismic phase detection for single three-component station. Here, we explore the application of DL to enhance automatic array processing pipelines for seismic event detection. Our work focuses on three key tasks where DL could complement or potentially replace traditional methods: (1) seismic phase detection, (2) seismic phase...
Monitoring techniques based on infrasound arrays have contributed to the detection, location, characterisation, and quantification of volcanic and seismic activity at local as well as regional distances. Currently, the Azores infrasound network comprises an International Monitoring System (IMS) station IS42 on Graciosa Island and two low-cost arrays (SJ1 and TER), located on São Jorge and...
Distributed Acoustic Sensing (DAS) technology using fibre optic cables presents a promising tool for detecting, locating and characterizing seismic events, including explosions. This study, based on a real experiment, assesses DAS’s capability to enhance nuclear-test-ban monitoring, aligning with CTBT goals. With its ability to transform fibre optic infrastructure into extensive arrays of...
Accurate phase picking detection is crucial in seismic analysis, particularly in detecting underground nuclear explosions. Due to the overlapping wave characteristics, differentiation between seismic events caused by nuclear detonations and natural earthquakes is challenging. This study focuses on developing and applying advanced phase-picking techniques to identify and analyze nuclear...
Here, we use coda measurements and apply the waveform envelope spectral ratio method to obtain the measurements necessary for source discrimination and to determine absolute yield and depth of burial at globally distributed test sites. Studies of high‐frequency (>~1 Hz) source processes are crucial for both event discrimination and yield/magnitude determination of smaller seismic events....
We present a novel approach to the detection and parameter estimation of infrasonic signals: the Multi-Channel Maximum-Likelihood (MCML) method [https://doi.org/10.1093/gji/ggac377]. MCML is based on the likelihood function derived from a multi-sensor stochastic model expressed in different frequency bands. Using the likelihood function, we determine, for the detection problem, the Generalized...
