GUAN Jianbo, LI Yu, YIN Caiyun, YANG Zhi, JIN Chaobin, ZHAO Meng, YANG Hang. Love wave full waveform inversion via Pseudo-Hessian gradient pre-conditioning operator[J]. COAL GEOLOGY & EXPLORATION, 2021, 49(4): 49-59. DOI: 10.3969/j.issn.1001-1986.2021.04.007
Citation: GUAN Jianbo, LI Yu, YIN Caiyun, YANG Zhi, JIN Chaobin, ZHAO Meng, YANG Hang. Love wave full waveform inversion via Pseudo-Hessian gradient pre-conditioning operator[J]. COAL GEOLOGY & EXPLORATION, 2021, 49(4): 49-59. DOI: 10.3969/j.issn.1001-1986.2021.04.007

Love wave full waveform inversion via Pseudo-Hessian gradient pre-conditioning operator

  • The construction of near surface shear wave velocity is an important step in multi-component seismic data processing in coalfield. Compared with the multichannel analysis of surface wave, the full waveform inversion(FWI) has higher resolution in the construction of near surface shear wave velocity model. However, in the gradient-based FWI, the gradient operator is not scaled with increasing depth due to the narrow frequency band of seismic records, the non-uniform coverage of the wavefield, and the double scattering. The parameters of the deep model cannot be updated significantly. The Hessen operator of the objective function contains curvature information, which can clearly predict the defocusing phenomenon and the artifacts generated by double scattering in the gradient operator. The inverse Hessen operator can be used as a deconvolution operator to realize gradient pre-conditioning and enhance the illumination ability of the deep model. However, the explicit calculation of Hessian operator is very difficult because it has huge dimensions. Based on this, inverse scattering theory is referred to, the expression of the pseudo-Hessian operator of the objective function of full-waveform inversion is given, and a pre-conditioned gradient-based FWI method is developed. The proposed method was applied to the reconstruction tests of the fault model, subsidence model, and undulating interface model, respectively. The inversion results show that, compared with the classic conjugate gradient-based FWI, the pre-conditioned conjugate gradient method based on the pseudo-Hessian operator can accelerate the convergence rate and improve the inversion accuracy.
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