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ISSN 2096-7780 CN 10-1665/P

Li Qi, Zhang Zhi, Hou Jue, Yu Guiping, Wang Minling, Xu Tao. Research progress of the extraction body waves from ambient noise[J]. Progress in Earthquake Sciences, 2021, (10): 433-451. DOI: 10.3969/j.issn.2096-7780.2021.10.001
Citation: Li Qi, Zhang Zhi, Hou Jue, Yu Guiping, Wang Minling, Xu Tao. Research progress of the extraction body waves from ambient noise[J]. Progress in Earthquake Sciences, 2021, (10): 433-451. DOI: 10.3969/j.issn.2096-7780.2021.10.001

Research progress of the extraction body waves from ambient noise

  • The exploration of the deep structure of the earth is the core part of geophysical research. Seismic body waves can penetrate deep into the earth with a high resolution and it is an indispensable technical means for studying the internal structure of the earth. The rapid development of technology for extracting high signal-to-noise ratio body wave signals based on ambient noise has greatly promoted the development and application of seismology, making it increasingly play an important role in the imaging of deep earth structures and shallow urban space exploration. This article reviews in detail how to use seismic interferometry and array processing technology to extract various types of body wave signals for research on different detection scales (local, regional, global). Among them, the seismic interferometry cross-correlates the waveform signals recorded by the seismic stations to cancel out the coincident ray paths, and finally the seismic records between the station pairs are obtained; and the array processing method is based on the data developed by the receiver array processing means. This technology can not only further improve the signal-to-noise ratio (SNR), but also obtain position information. Generally speaking, since the energy of the body wave signal contained in the ambient noise is much weaker than that of the surface wave signal, it is difficult to extract. This article focuses on the Bin stack method, the double beamforming method (DBF) and the phase-weighted stacks method (PWS), and concludes the applicable conditions of the three methods.
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