Abstract
Due to uneven earthquake source and receiver distributions, our abilities to isolate weak signals from interfering phases and reconstruct missing data are fundamental to improving the resolution of seismic imaging techniques. In this study, we introduce a modified frequency- wavenumber (fk) domain based approach using a 'Projection Onto Convex Sets' (POCS) algorithm. POCS takes advantage of the sparsity of the dominating energies of phase arrivals in the fk domain, which enables an effective detection and reconstruction of the weak seismic signals. Moreover, our algorithm utilizes the 2-D Fourier transform to perform noise removal, interpolation and weak-phase extraction. To improve the directional resolution of the reconstructed data, we introduce a band-stop 2-D Fourier filter to remove the energy of unwanted, interfering phases in the fk domain, which significantly increases the robustness of the signal of interest. The effectiveness and benefits of this method are clearly demonstrated using both simulated and actual broadband recordings of PP precursors from an array located in Tanzania. When used properly, this method could significantly enhance the resolution of weak crust and mantle seismic phases.
| Original language | English |
|---|---|
| Pages (from-to) | 1288-1301 |
| Number of pages | 14 |
| Journal | Geophysical Journal International |
| Volume | 212 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 1 Feb 2018 |
| Externally published | Yes |
Funding
We would like to thank Sergi Ventosa, an anonymous reviewer and the Editor Martin Schimmel for constructive and helpful reviews. The facilities of IRIS Data Services, and specifically the IRIS Data Management Center, were used for access to waveforms, related metadata and/or derived products used in this study. IRIS Data Services are funded through the Seismological Facilities for the Advancement of Geoscience and EarthScope (SAGE) Proposal of the National Science Foundation under Co-operative Agreement EAR-1261681. Codes, maps and figures were produced with Python (Python Software Foundation (2016)), data were processed using the python library ObsPy (Beyreuther et al. 2010). The work was partly financed by DFG (Deutsche Forschungs Gemeinschaft) grant TH1530/9-1.
Keywords
- Body waves
- Coda waves
- Fourier analysis
- Spatial analysis
- Time-series analysis
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