<i>PySolate</i> : A Python-Based Thresholding Tool to Denoise or Designal Seismic Waveforms Based on the Continuous Wavelet Transform

Abstract PySolate is a Python-based toolset that implements the continuous wavelet transform and nonlinear thresholding operations to denoise or designal seismic data, following Langston and Mousavi (2019). This filtering approach can remove microseismic noise to isolate intermediate-period seismic signals that are key to enabling full-waveform modeling and analysis of smaller-magnitude regional events. This approach is best for the application to signals with frequency or time separation of signal and noise, in contrast to Fourier analysis, which is effective when signal and noise are separated in frequency. We demonstrate the Python toolset using the six announced Democratic People’s Republic of Korea declared nuclear tests, showing the effectiveness of isolating the seismic signal compared to standard bandpass filtering. We also demonstrate the ease of using the toolset with any Python processing tools.

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Publication Details

Journal
Seismological Research Letters
Published
2025-08-15
DOI
https://doi.org/10.1785/0220250034
Primary Topic
Seismic Imaging and Inversion Techniques
Type
article
Field-Weighted Citation Impact
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article

PySolate : A Python-Based Thresholding Tool to Denoise or Designal Seismic Waveforms Based on the Continuous Wavelet Transform

Andrea Chiang, A. C. Aguiar, Stephen C. Myers
Seismological Research Letters
Seismic Imaging and Inversion Techniques
article

PySolate : A Python-Based Thresholding Tool to Denoise or Designal Seismic Waveforms Based on the Continuous Wavelet Transform

Andrea Chiang, A. C. Aguiar, Stephen C. Myers
article en

Abstract

Abstract PySolate is a Python-based toolset that implements the continuous wavelet transform and nonlinear thresholding operations to denoise or designal seismic data, following Langston and Mousavi (2019). This filtering approach can remove microseismic noise to isolate intermediate-period seismic signals that are key to enabling full-waveform modeling and analysis of smaller-magnitude regional events. This approach is best for the application to signals with frequency or time separation of signal and noise, in contrast to Fourier analysis, which is effective when signal and noise are separated in frequency. We demonstrate the Python toolset using the six announced Democratic People’s Republic of Korea declared nuclear tests, showing the effectiveness of isolating the seismic signal compared to standard bandpass filtering. We also demonstrate the ease of using the toolset with any Python processing tools.

Seismological Research LettersVol. 97(1)
Lawrence Livermore National Laboratory (US)
Openalex Percentile: Top 77%
Seismic Imaging and Inversion Techniques
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<i>PySolate</i> : A Python-Based Thresholding Tool to Denoise or Designal Seismic Waveforms Based on the Continuous Wavelet Transform — Andrea Chiang, A. C. Aguiar, et al. · Seismological Research Letters (2025) | TGRS Research Map | TGRS