Seismic inversion works as a hot and pragmatic tool in parameters estimation in the fields of geosciences. Low frequency component of model parameter plays an important role in seismic inversion. However, the history researches on this topic are far below needs. A novel seismic Bayesian approach in the complex frequency domain is proposed to implement the estimation of low frequency component of model parameter. The proposed approach makes full use of the advantage of low frequency component of the damped wave fields in mixed Laplace and Fourier domain. The kernel function of this proposed inversion approach is built under Bayesian inversion scheme, and the prior probability distribution of model parameter merged in objective function is helpful to enhance the robustness of the inversion. Synthetic examples demonstrate the feasibility and robustness of the proposed inversion approach in the estimation of low frequency component of model parameter.
Presentation Date: Thursday, October 20, 2016
Start Time: 9:45:00 AM
Location: 143/149
Presentation Type: ORAL
