Microseismic events from ocean waves are separated from volcanic signals using frequency filtering.
the verdict
INSUFFICIENT LEANING
refutedsupported
the weight of evidence
2 sources for · 0 against
Retrieved literature indicates that narrow frequency filtering can be applied alongside other analyses to determine whether seismic signals originate from ocean microseisms rather than volcanic sources, but does not fully establish that frequency filtering alone universally separates microseismic events from volcanic signals.
Seismograms contain multiple sources of seismic waves, from distinct transient signals such as earthquakes to continuous ambient seismic vibrations such as microseism. Ambient vibrations contaminate the earthquake signals, while the earthquake signals pollute the ambient noise’s statistical properties necessary for ambient-noise seismology analysis. Separating ambient noise from earthquake signals would thus benefit multiple seismological analyses. This work develops a multi-task encoder-decoder network named WaveDecompNet to separate transient signals from ambient signals directly in the time domain for 3-component seismograms. We choose the active-volcanic Big Island in Hawai’i as a natural laboratory given its richness in transients (tectonic and volcanic earthquakes) and diffuse ambient noise (strong microseism). The approach takes a noisy 3-component seismogram as input and independently predicts the 3-component earthquake and noise waveforms. The model is trained on earthquake and noise waveforms from the STandford EArthquake Dataset (STEAD) and on the local noise of seismic station IU.POHA. We estimate the network’s performance by using the Explained Variance (EV) metric on both earthquake and noise waveforms. We explore different neural network designs for WaveDecompNet and find that the model with Long-Short-Term-Memory (LSTM) performs best over other structures. Overall, we find that WaveDecompNet provides satisfactory performance down to a Signal-to-Noise-Ratio (SNR) of 0.1. The potential of the method is 1) to improve broadband SNR of transient (earthquake) waveforms and 2) to improve local ambient noise to monitor the Earth’s structure using ambient noise signals. To test this, we apply a Short-Time-Average to a Long-Time-Average (STA/LTA) filter and improve the number of detected events. We also measure single-station cross-correlation functions of the recovered ambient noise and establish their improved coherence through time and over different frequency bands. We conclude that WaveDecompNet is a promising tool for a broad range of seismological research.
This investigation deals with the nature of the long-period seismic signals (>1 s) observed at Stromboli and addresses the question whether they are of volcanic origin or produced by sources such as Ocean Microseisms (OMS). We present results from the analysis of seismic broadband data recorded during 1992 by an array of 9 Guralp CMG-3T seismometers. The determination of the Array Response Function (ARF) shows that array techniques like delay-and-sum beamforming cannot be applied for this purpose, as the extension of the array is limited by the geographical constraint of the island of Stromboli volcano, being simply too small. Spectral analysis reveals three main peaks with periods at 4.8 s, 6 s and 10 s which are not stable in time but vary according to the regional meteorological situation. Whereas 4.8 s and 10 s show up in amplitude spectra calculated during rainy and stormy weather, the 6 s period can be observed during a period of good weather. The signals were first narrowly filtered and then cross correlation, particle motion and amplitudes of the main long periods studied in detail. Relative arrival times as well as seismic amplitudes of the filtered traces do not show any systematic feature but vary with time. Particle motion analysis demonstrates that all long-period signals are recorded by the array as plane waves and that the main propagation direction of the 10 s signal is parallel to the wind direction. No correlation with volcanic activity is obvious. We conclude therefore that the three main long periods are not generated by a close volcanic source. We assume a local cyclone to be the seismic source at 4.8 s and 10 s, which represent the Double Frequency (DF-band) and the Primary Frequency (PF-band), respectively. Concerning the 6 s peak, we speculate a cyclone near the British Isles to act as a seismic source.
On the origin of the long-period tremor recorded at Stromboli volcano (Italy) | Annals of Geophysics Article Sidebar PDF Published: 1996-11-25 DOI: https://doi.org/10.4401/ag-3977 Keywords: lomg-period volcanic tremor, ocean microseisms, Stromboli volcano, seismic broad-band array Main Article Content T. Braun Institut für Geophysik, Stuttgart, Germany J. Neuberg Department of Earth Sciences, Leeds, U.K. M.
Ripepe Dipartimento di Scienze della Terra, Firenze, Italy Abstract This investigation deals with the nature of the long-period seismic signals (>1 s) observed at Stromboli and addresses the question whether they are of volcanic origin or produced by sources such as Ocean Microseisms (OMS). We present results from the analysis of seismic broadband data recorded during 1992 by an array of 9 Guralp CMG-3T seismometers.
The signals were first narrowly filtered and then cross correlation, particle motion and amplitudes of the main long periods studied in detail. Relative arrival times as well as seismic amplitudes of the filtered traces do not show any systematic feature but vary with time. Particle motion analysis demonstrates that all long-period signals are recorded by the array as plane waves and that the main propagation direction of the 10 s signal is parallel to the wind direction. No correlation with volcanic activity is obvious. We conclude therefore that the three main long periods are not generated by a close volcanic source.
We assume a local cyclone to be the seismic source at 4.8 s and 10 s, which represent the Double Frequency (DF-band) and the Primary Frequency (PF-band), respectively. Concerning the 6 s peak, we speculate a cyclone near the British Isles to act as a seismic source. Article Details Issue Vol. 39 No. 2 (1996) Section OLD Open-Access License No Permission Required Istituto Nazionale di Geofisica e Vulcanologia applies the Creative Commons Attribution License (CCAL) to all works we publish. Under the CCAL, authors retain ownership of the copyright for their article, but authors allow anyone to download, reuse, reprint, modify, distribute, so long as the original authors and source are cited.
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