Source-Independent Waveform Inversion Method for Ground Penetrating Radar Based on Envelope Objective Function

被引:4
作者
Liu, Xintong [1 ,2 ]
Liu, Sixin [2 ,3 ]
Luo, Chaopeng [2 ]
Jiang, Hejun [2 ]
Li, Hong [2 ]
Meng, Xu [4 ]
Feng, Zhihui [1 ]
机构
[1] Jilin Jianzhu Univ, Sch Geomat & Prospecting Engn, Changchun 130026, Peoples R China
[2] Sci & Technol Near Surface Detect Lab, Wuxi 214035, Jiangsu, Peoples R China
[3] Jilin Univ, Coll Geoexplorat Sci & Technol, Changchun 130026, Peoples R China
[4] Guangzhou Univ, Sch Civil Engn, Guangzhou 510000, Peoples R China
基金
中国国家自然科学基金;
关键词
GPR; FWI; envelope; source-independent; multi-scale inversion; FREQUENCY-DOMAIN; TOMOGRAPHY; LIMITS; PHASE;
D O I
10.3390/rs14194878
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
For the full waveform inversion, it is necessary to provide an accurate source wavelet for forwarding modeling in the iteration. The source wavelet estimation method based on deconvolution technology can solve this problem to some extent, but we find that the estimated source wavelet is not accurate and needs to be manually corrected repeatedly in the iteration. This process is highly operator-intensive, and the update process is time-consuming and increases the potential for errors. We propose a source-independent waveform inversion (SIEWI) scheme for cross-hole GPR data, and use the envelope objective function combined with this method to effectively reduce the nonlinearity of inversion. The residual field used by SIEWI to construct the gradient inherits the characteristics of the envelope wavefield. Compared with full waveform inversion (FWI), SIEWI is more robust and less sensitive to frequency components and inaccurate source wavelet. To avoid cycle jumping, the multi-scale strategy effectively utilizes the properties of convolutional wavefields. In one iteration, the wavefield is decomposed into multiple frequency bands through multiple convolutions in the time domain to construct a multi-scale inversion strategy that preferentially inverts low-frequency information.
引用
收藏
页数:22
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