APPLIED GEOPHYSICS
 
        Home  |  Copyright  |  About Journal  |  Editorial Board  |  Indexed-in  |  Subscriptions  |  Download  |  Contacts Us  |  中文
APPLIED GEOPHYSICS  2020, Vol. 17 Issue (1): 143-153    DOI: 10.1007/s11770-020-0801-2
article Current Issue | Next Issue | Archive | Adv Search Previous Articles  |  Next Articles  
Second-generation wavelet fi nite element based on the lifting scheme for GPR simulation*
Feng De-Shan 1,2, Zhang Hua 1,2, and Wang Xun 1,2
1. School of Geosciences and Info-Physics, Central South University, Changsha 410083, China.
2. Key Laboratory of Metallogenic Prediction of Nonferrous Metals, Ministry of Education, Changsha 410083, China.                            
 Download: PDF (927 KB)   HTML ( KB)   Export: BibTeX | EndNote (RIS)      Supporting Info
Abstract Ground-penetrating radar (GPR) is a highly efficient, fast and non-destructive exploration method for shallow surfaces. High-precision numerical simulation method is employed to improve the interpretation precision of detection. Second-generation wavelet finite element is introduced into the forward modeling of the GPR. As the finite element basis function, the second-generation wavelet scaling function constructed by the scheme is characterized as having multiple scales and resolutions. The function can change the analytical scale arbitrarily according to actual needs. We can adopt a small analysis scale at a large gradient to improve the precision of analysis while adopting a large analytical scale at a small gradient to improve the efficiency of analysis. This approach is beneficial to capture the local mutation characteristics of the solution and improve the resolution without changing mesh subdivision to realize the efficient solution of the forward GPR problem. The algorithm is applied to the numerical simulation of line current radiation source and tunnel non-dense lining model with analytical solutions. Result show that the solution results of the secondgeneration wavelet finite element are in agreement with the analytical solutions and the conventional finite element solutions, thereby verifying the accuracy of the second-generation wavelet finite element algorithm. Furthermore, the second-generation wavelet finite element algorithm can change the analysis scale arbitrarily according to the actual problem without subdividing grids again. The adaptive algorithm is superior to traditional scheme in grid refi nement and basis function order increase, which makes this algorithm suitable for solving complex GPR forward-modeling problems with large gradient and singularity.
Service
E-mail this article
Add to my bookshelf
Add to citation manager
E-mail Alert
RSS
Articles by authors
Key wordsGround penetrating radar   wave equation   second-generation wavelet finite element method   lifting scheme   forward modeling     
Received: 2018-10-01; Published: 2020-09-04
Fund:

This work was supported by the National Natural Science Foundation of China (Nos. 41574116 and 41774132) and Hunan Provincial Innovation Foundation for Postgraduate (Grant Nos. CX2017B052) and the Fundamental Research Funds for the Central Universities of Central South University (Nos. 2018zzts693)

Corresponding Authors: Wang Xun (E-mail: wangxun0727@csu.edu.cn)   
 E-mail: wangxun0727@csu.edu.cn
About author: Feng De-shan, professor, doctoral supervisor. He received Ph.D. (2006) in Geophysical Prospecting and Information Technology from Central South University. Visiting scholar at Rice University, USA, 2013-2014. He is interested in the theory and application of GPR, forward modeling and inversion, and wavelet analysis. E-mail: fengdeshan@126.com Wang Xun, Corresponding author, received his M.S. (2016) in Geological Engineering f r o m C e n t r a l S o u t h U n i v e r s i t y. He is presently a Ph.D. candidate in Geophysical Prospecting and Information Technology at Central South University. His main interests is numerical simulation of electromagnetic method. E-mail: wangxun0727@csu.edu.cn.
Cite this article:   
. Second-generation wavelet fi nite element based on the lifting scheme for GPR simulation*[J]. APPLIED GEOPHYSICS, 2020, 17(1): 143-153.
 
No references of article
[1] Lv Yu-zeng, Wang Hong-hua, Gong Jun-bo. Application of GPR reverse time migration in tunnel lining cavity imaging*[J]. APPLIED GEOPHYSICS, 2020, 17(2): 277-284.
[2] Cui Fan , Li Shuai, Yuan Jiong-Xuan, Bai Jie-Bin , Zhao Yu-Xuan, and Zhou Ying-Ging. GPR based RTM imaging technology for estimating rhizome diameters and application in the western China mining area*[J]. APPLIED GEOPHYSICS, 2020, 17(1): 154-166.
[3] Zhang Zhen-Bo, Xuan Yi-Hua, and Deng Yong. Simultaneous prestack inversion of variable-depth streamer seismic data*[J]. APPLIED GEOPHYSICS, 2019, 16(1): 99-108.
[4] Huang Xin, Yin Chang-Chun, Cao Xiao-Yue, Liu Yun-He, Zhang Bo, Cai Jing. 3D anisotropic modeling and identification for airborne EM systems based on the spectral-element method[J]. APPLIED GEOPHYSICS, 2017, 14(3): 419-430.
[5] Yin Chang-Chun, Zhang Ping, Cai Jing. Forward modeling of marine DC resistivity method for a layered anisotropic earth[J]. APPLIED GEOPHYSICS, 2016, 13(2): 279-287.
[6] Zhang Gong, Li Ning, Guo Hong-Wei, Wu Hong-Liang, Luo Chao. Fracture identification based on remote detection acoustic reflection logging[J]. APPLIED GEOPHYSICS, 2015, 12(4): 473-481.
[7] Zeng Zhao-Fa, Chen Xiong, Li Jing, Chen Ling-Na, Lu Qi, Liu Feng-Shan. Recursive impedance inversion of ground-penetrating radar data in stochastic media[J]. APPLIED GEOPHYSICS, 2015, 12(4): 615-625.
[8] Zhu Chao, Guo Qing-Xin, Gong Qing-Shun, Liu Zhan-Guo, Li Sen-Ming, Huang Ge-Ping. Prestack forward modeling of tight reservoirs based on the Xu–White model[J]. APPLIED GEOPHYSICS, 2015, 12(3): 421-431.
[9] Zhang Jun-Hua, Zhang Bin-Bin, Zhang Zai-Jin, Liang Hong-Xian, Ge Da-Ming. Low-frequency data analysis and expansion[J]. APPLIED GEOPHYSICS, 2015, 12(2): 212-220.
[10] YANG Jia-Jia, HE Bing-Shou, ZHANG Jian-Zhong. Multicomponent seismic forward modeling of gas hydrates beneath the seafloor[J]. APPLIED GEOPHYSICS, 2014, 11(4): 418-428.
[11] ZHAO Hu, YIN Cheng, HOU Peng-Jun, PU Long-Chuan, HUANG Yong, YUAN Guo-Hui. An automatical infill shot method for uniform imaging of target layer[J]. APPLIED GEOPHYSICS, 2013, 10(2): 222-228.
[12] DUAN Yu-Ting, HU Tian-Yue, YAO Feng-Chang, ZHANG Yan. 3D elastic wave equation forward modeling based on the precise integration method[J]. APPLIED GEOPHYSICS, 2013, 10(1): 71-78.
[13] ZHANG Sheng-Qiang, HAN Li-Guo, LIU Chun-Cheng, ZHANG Yi-Ming, GONG Xiang-Bo. Inverting reservoir parameters in a two-phase fractured medium with a niche genetic algorithm[J]. APPLIED GEOPHYSICS, 2012, 9(4): 440-450.
[14] ZHAO Wen-Ke, TIAN Gang, WANG Bang-Bing, SHI Zhan-Jie, LIN Jin-Xin. Application of 3D GPR attribute technology in archaeological investigations[J]. APPLIED GEOPHYSICS, 2012, 9(3): 261-269.
[15] SONG Jian-Yong, ZHENG Xiao-Dong, QIN Zhen, SU Ben-Yu. Multi-scale seismic full waveform inversion in the frequency-domain with a multi-grid method[J]. APPLIED GEOPHYSICS, 2011, 8(4): 303-310.
Copyright © 2011 APPLIED GEOPHYSICS
Support by Beijing Magtech Co.ltd support@magtech.com.cn