Effect of Time Window and Spectral Measurement Options on Empirical Green's Function Analysis Using DAS Array and Seismic Stations
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1.
Texas A&M University
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2.
California Institute of Technology
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3.
Lawrence Livermore National Laboratory
Abstract
The recorded seismic waveform is a convolution of event source term, path term, and station term. Removing high-frequency attenuation due to path effect is a challenging problem. Empirical Green's function (EGF) method uses nearly collocated small earthquakes to correct the path and station terms for larger events recorded at the same station. However, this method is subject to variability due to many factors. We focus on three events that were well recorded by the seismic network and a rapid response distributed acoustic sensing (DAS) array. Using a suite of high-quality EGF events, we assess the influence of time window, spectral measurement options, and types of data on the spectral ratio and relative source time function (RSTF) results. Increased number of tapers (from 2 to 16) tends to increase the measured corner frequency and reduce the source complexity. Extended long time window (e.g., 30 s) tends to produce larger variability of corner frequency. The multitaper algorithm that simultaneously optimizes both target and EGF spectra produces the most stable corner-frequency measurements. The stacked spectral ratio and RSTF from the DAS array are more stable than two nearby seismic stations, and are comparable to stacked results from the seismic network, suggesting that DAS array has strong potential in source characterization.
Copyright and License
© 2025 Seismological Society of America.
Acknowledgement
The authors thank the Southern California Earthquake Center (SCEC) for supporting the Ridgecrest stress‐drop validation study. SCEC is funded by National Science Foundation (NSF) Cooperative Agreement EAR‐1033462 and U.S. Geological Survey (USGS) Cooperative Agreement G12AC20038. This is SCEC Contribution 14152. Chen and Wu acknowledge support from SCEC Award 21169. Chen is also partially supported by SCEC Award 21032, 22042, and NSF Award 2328485. Colin Pennington’s work was completed at Lawrence Livermore National Laboratory (LLNL) under Contract DE‐AC52‐07NA2734. The authors thank German Prieto for providing the MATLAB script for the multitaper algorithm (“mtspec” and “mtdeconv”). The authors thank editor Adrien Oth, reviewers Itzhak Lior, and Shanna Chu for detailed comments.
Data Availability
The seismic and distributed acoustic sensing (DAS) data can be accessed through Amazon Web Services (AWS): https://scedc.caltech.edu/data/cloud.html (last accessed September 2022). MATLAB R2022a (www.mathworks.com/products/matlab, last access September 2024) is used to analyze data and generate all the figures in the manuscript. The software package GISMO (Thompson and Reyes, 2018) is used to organize waveform data. The supplemental material contains additional figures for individual target–empirical Green’s function (EGF) pairs, a csv file with detailed event information, and a csv file with detailed corner‐frequency results for different options shown in Figure 4.
Supplemental Material
Files
bssa-2024156_supplement.pdf
Additional details
Funding
- National Science Foundation
- EAR-1033462
- United States Geological Survey
- G12AC20038
- Southern California Earthquake Center
- 21169
- Southern California Earthquake Center
- 21032
- Southern California Earthquake Center
- 22042
- National Science Foundation
- 2328485
- United States Department of Energy
- DE-AC52-07NA2734
Dates
- Available
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2025-03-04First online