<p>Full waveform inversion (FWI) using passive seismic data offers potential advantages for obtaining deep subsurface structural information. However, its application depends on a reliable background model and accurate source locations. Here, we introduce a joint inversion framework that uses virtual and actual passive seismic data to achieve velocity modeling and source localization. This method first retrieves the broadband virtual reflection responses at the surface by seismic interferometry. Then, the virtual responses are used as the basis for multiscale FWI to recover the subsurface velocity structures without knowledge of the actual passive source locations. Finally, using the inversion result as the initial model, alternately perform reverse-time wavefield scanning and FWI with actual passive-source data, enabling simultaneous inversion for source locations and velocity information and compensating for deep illumination. Numerical examples under various conditions of inhomogeneous passive-source distribution and signal-to-noise ratio (SNR) show that the proposed method can robustly recover the subsurface velocity structures using only passive seismic data, even when the initial model is rough, while accurately locating passive seismic events.</p>

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Joint full waveform inversion and source localization of virtual and actual passive source seismic data

  • Xujia Shang,
  • Liguo Han,
  • Pan Zhang,
  • Wensha Huang,
  • Donghao Zhang

摘要

Full waveform inversion (FWI) using passive seismic data offers potential advantages for obtaining deep subsurface structural information. However, its application depends on a reliable background model and accurate source locations. Here, we introduce a joint inversion framework that uses virtual and actual passive seismic data to achieve velocity modeling and source localization. This method first retrieves the broadband virtual reflection responses at the surface by seismic interferometry. Then, the virtual responses are used as the basis for multiscale FWI to recover the subsurface velocity structures without knowledge of the actual passive source locations. Finally, using the inversion result as the initial model, alternately perform reverse-time wavefield scanning and FWI with actual passive-source data, enabling simultaneous inversion for source locations and velocity information and compensating for deep illumination. Numerical examples under various conditions of inhomogeneous passive-source distribution and signal-to-noise ratio (SNR) show that the proposed method can robustly recover the subsurface velocity structures using only passive seismic data, even when the initial model is rough, while accurately locating passive seismic events.