PySolate: A Python‐Based Thresholding Tool to Denoise or Designal Seismic Waveforms Based on the Continuous Wavelet Transform
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. In conclusion, we also demonstrate the ease of using the toolset with any Python processing tools.
- Research Organization:
- Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
- Sponsoring Organization:
- USDOE National Nuclear Security Administration (NNSA), Office of Defense Nuclear Nonproliferation
- Grant/Contract Number:
- AC52-07NA27344
- OSTI ID:
- 3017596
- Report Number(s):
- LLNL--JRNL-868619
- Journal Information:
- Seismological Research Letters, Journal Name: Seismological Research Letters Journal Issue: 1 Vol. 97; ISSN 0895-0695; ISSN 1938-2057
- Publisher:
- Seismological Society of AmericaCopyright Statement
- Country of Publication:
- United States
- Language:
- English
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