Broadband Seismic Inversion for Low-Frequency Component of the Model Parameter
Broadband Seismic Inversion for Low-Frequency Component of the Model Parameter
复制标题
模型参数低频分量的宽带地震反演
DOI：
10.1109/tgrs.2018.2810845
复制
发表时间：
2018-03
影响因子：
8.2
通讯作者：
Yin Xingyao
中科院分区：
文献类型：
--
作者：
Zong Zhaoyun;Wang Yurong;Li Kun;Yin Xingyao
Seismic inversion is an important approach in parameters estimation in the fields of geosciences. The low-frequency component of the model parameter plays an important role in seismic inversion. The emergence of broadband seismic data acquisition and processing technologies is pushing the attention of the low frequency to a new level. With the review of the research status of the estimation of the low-frequency models in history and the low-frequency component contained in the complex frequency domain, a novel broadband seismic Bayesian inversion approach in the complex frequency domain is proposed to implement the estimation of the low-frequency component of the model parameter. The proposed approach makes full use of the advantage of broadband seismic data and the low-frequency component of the damped wave fields in the complex frequency domain. The kernel function of the proposed inversion approach is built with Bayesian inference. Synthetic examples demonstrate the feasibility and robustness of the proposed inversion approach in the estimation of the low-frequency component of the model parameter. A field data example verifies the feasibility and reasonability of the proposed inversion approach in application. Finally, the estimated low-frequency component of the model parameter is utilized as the initial model for the suggested seismic Bayesian inversion method in time domain. Model and field data examples further verify the effectiveness and superiority of the proposed inversion method in the final estimation of the model parameter by comparing with the conventional inversion approach.
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DOI：
10.1190/1.3513326
发表时间：
2010
期刊：
Seg Technical Program Expanded Abstracts
影响因子：
--
作者：
C. Reiser;C. Ribeiro
通讯作者：
C. Reiser;C. Ribeiro
影响因子：
2
作者：
A. Buland;M. Landrø
通讯作者：
A. Buland;M. Landrø
影响因子：
3.3
作者：
M. Landrø;L. Amundsen
通讯作者：
M. Landrø;L. Amundsen
影响因子：
2.8
作者：
C. Shin;Y. Cha
通讯作者：
C. Shin;Y. Cha
影响因子：
2.6
作者：
Sergio Carmo;L. Azevedo;A. Soares
通讯作者：
Sergio Carmo;L. Azevedo;A. Soares