Journal of Jilin University(Earth Science Edition) ›› 2021, Vol. 51 ›› Issue (2): 561-570.doi: 10.13278/j.cnki.jjuese.20200038

Previous Articles    

GPR Impedance Inversion of Permittivity Based on Velocity Analysis

Wang Tianqi1, Li Jing1,2, Bai Lige1, Li Jing3, Li Feida4   

  1. 1. College of GeoExploration Science and Technology, Jilin University, Changchun 130026, China;
    2. Key Laboratory of Geophysical Exploration Equipment, Ministry of Education(Jilin University), Changchun 130026, China;
    3. College of Civil Engineering, Chongqing University, Chongqing 400000, China;
    4. Jilin Geophysics Prospecting Institute, Changchun 130062, China
  • Received:2020-05-19 Published:2021-04-06
  • Supported by:
    Supported by the National Natural Science Foundation of China (41874134), the Foundation for Excellent Young Scho-lars of Jilin Province (20190103142JH), the Youth Talent Project of China Association for Science and Technology (2019QNRC001) and the Technology Development Program of Jilin Province (20200201216JC)

PDF (PC)

219

Abstract: Impedance inversion is an important technique for estimating the parameters of underground media using the relationship between wave impedance and dielectric constant, which is widely used in GPR and post-stack seismic data interpretation. Conventional impedance inversion requires drilling or logging parameters as constraints, which directly affect the estimation accuracy of the final impedance inversion. In the practical application with lack of borehole data, how to carry out GPR impedance inversion is one of the important contents of the method. To solve the above problems, the authors proposed a GPR impedance inversion method based on velocity analysis. The basic idea is to carry out velocity spectrum analysis and Dix inversion based on multiple offset radar data to obtain velocity information of different depths as the constraint term of impedance inversion. At the same time, the K-means method can automatically pick up the velocity spectrum information, so as to greatly reduce the conventional manual picking error and improve the calculation efficiency. Through a typical random soil medium model, it is verified that the method can also obtain better dielectric constant estimation results without drilling data, and can test noise adaptability effectively. Based on the GPR data acquired from Wurtsmith AFB, in Oscoda area, Michigan, the method proposed in this paper has a good application effect in the parameter estimation of GPR measured data.

Key words: K-means velocity analysis, GPR, impedance inversion, constraints, permittivity

CLC Number: 

  • P631
[1] Hansen T B, Johansen P M. Inversion Scheme for Ground-Penetrating Radar that Takes into Account the Planar Air-Soil Interface[J]. IEEE Transactions on Geoscience and Remote Sensing, 2000, 38(1):496-506.
[2] 张进铎. 地震解释技术现状及发展趋势[J].地球物理学进展, 2006, 37(2):578-587. Zhang Jinduo. CurrentSituation and Development Trend of Seismic Interpretation Technology[J]. Progress in Geophysics, 2006,37(2):578-587.
[3] Schmelzbach C, Tronicke J, Dietrich P. High-Resolution Water Content Estimation from Surface-Based Ground-Penetrating Radar Reflection Data by Impedance Inversion[J].Water Resources Research, 2012, 48(8):64-69.
[4] Li J, Zeng Z, Chen L, et al. Estimation of Mixed Soil Water Content by Impedance Inversion of GPR Data[C]//Proceedings of the 15th International Conference on Ground Penetrating Radar. Brussels:IEEE, 2014:149-154.
[5] Zeng Z F, Chen X, Li J, et al. Recursive Impedance Inversion of Ground-Penetrating Radar Data in Stochastic Media[J]. Applied Geophysics, 2015, 12(4):615-625.
[6] Liu Y, Shi Z, Wang B, et al.GPR Impedance Inversion for Imaging and Characterization of Buried Archaeological Remains:A Case Study at Mudu City Cite in Suzhou, China[J]. Journal of Applied Geophysics, 2018, 148:226-233.
[7] 佘松盛. 探地雷达方法对近地表LNAPL污染物的探测研究[D].长春:吉林大学, 2019. She Songsheng. Study on Near-Surface the LNAPL Pollution by GPR Method[D].Changchun:Jilin University, 2019.
[8] 王焱,鹿琪,刘财,等. 利用GPR天线-目标极化的瞬时属性分析方法探测LNAPL污染土壤[J]. 吉林大学学报(地球科学版), 2018, 48(2):491-500. Wang Yan, Lu Qi, Liu Cai, et al. Using GPR Antenna-Target Polarization Instantaneous Attribute Analysis Method to Detect LNAPL Contaminated Soil[J]. Journal of Jilin University (Earth Science Edition), 2018, 48(2):491-500.
[9] 王春辉. 探地雷达方法测量近地表含水量及污染物探测研究[D].长春:吉林大学, 2007. Wang Chunhui. Near Surface Water Content Measurement and Contamination Detection Using Ground-Penetrating Radar:A Simulation Study[D]. Changchun:Jilin University, 2007.
[10] Forte E, Pipan M. Review of Multi-Offset GPR Applications:Data Acquisition, Processing and Analysis[J].Signal Processing, 2017, 132:210-220.
[11] Parsekian A D. Inverse Methods to Improve Accuracy of Water Content Estimates from Multi-Offset GPR Parsekian:Improved Accuracy of Water Content from GPR[J].Journal of Environmental and Engineering Geophysics, 2018, 23(3):349-361.
[12] 董泽君,鹿琪,冯晅,等. 探地雷达测量土壤含水量的应用研究[J].地球物理学进展, 2017, 32(5):2207-2213. Dong Zejun, Lu Qi, Feng Xuan, et al. Estimation of Soil Water Content Using Ground Penetrating Radar[J]. Progress in Geophysics, 2017, 32(5):2207-2213.
[13] 蔡佳琪. 利用探测雷达探测铁路路基含水率[D].长春:吉林大学, 2017. Cai Jiaqi. Detection Railway Subgrade Moisture Content by GPR[D].Changchun:Jilin University, 2017.
[14] Chen Yuqing, Gerard S. Automatic Semblance Picking by a Bottom-Up Clustering Method[C]//SEG 2018 Workshop:SEG Maximizing Asset Value Through Artificial Intelligence and Machine Learning. Beijing:SEG, 2018:27-30.
[15] Bradford J H.GPR Offset Dependent Reflectivity Analysis for Characterization of a High-Conductivity LNAPL Plume[C]//16th EEGS Symposium on the Application of Geophysics to Engineering and Environmental Problems. San Abtonio:SEG, 2003:238-252.
[16] Bermejo J L, Sauck W A, Atekwana E A. Geophysical Discovery of a New LNAPL Plume at the Former Wurtsmith AFB, Oscoda, Michigan[J]. Groundwater Monitoring & Remediation, 1997, 17(4):131-137.
[17] Annan A P. Ground-Penetrating Radar[M]//Near-Surface Geophysics. Tulsa:Society of Exploration Geophysicists, 2005:357-438.
[18] 刘钰. 探地雷达数据波阻抗反演方法及其应用研究[D].杭州:浙江大学, 2018. Liu Yu. The Study of Ground Penetrating Radar Impendance Inversion Method and Its Application[D]. Hangzhou:Zhejiang University, 2018.
[19] 刘钰,石战结,王帮兵,等. 探地雷达子波确定性稀疏脉冲反褶积技术[J]. 浙江大学学报(工学版), 2018, 52(9):1828-1836. Liu Yu, Shi Zhanjie, Wang Bangbing, et al. Deterministic-Wavelet Sparse Spike Deconvolution Technique for Ground Penetrating[J]. Journal of Zhejiang University (Engineering Edition), 2018, 52(9):1828-1836.
[20] 康治梁,张雪冰. 基于L1/2正则化理论的地震稀疏反褶积[J]. 石油物探, 2019, 58(6):855-863. Kang Zhiliang, Zhang Xuebing. Seismic Sparse Deconvolution Based on L1/2 Regularization[J]. Geophysical Prospecting for Petroleum, 2019, 58(6):855-863.
[21] 王铁兴,王德利,孙婧,等. 基于三维稀疏反演的混合震源数据分离与一次波估计[J]. 吉林大学学报(地球科学版), 2020, 50(3):895-904. Wang Tiexing, Wang Deli, Sun Jing, et al. Separation and Primary Estimation of Blended Data by 3D Sparse Inversion[J]. Journal of Jilin University (Earth Science Edition), 2020, 50(3):895-904.
[22] Li G F, Qin D H, Peng G X, et al. Experimental Analysis and Application of Sparsity Constrained Deconvolution[J].Applied Geophysics, 2013, 10(2):191-200.
[23] 李静. 随机等效介质探地雷达探测技术和参数反演[D]. 长春:吉林大学, 2014. Li Jing. Ground Penetrating Radar Detection and Parameter Inversion in Stochastic Effective Medium[D]. Changchun:Jilin University, 2014.
[24] Dix C H. Seismic Velocities from Surface Measurements[J].Geophysics, 1955, 20(1):68-86.
[1] Wang Wentian, Liu Sixin, Lu Qi, Li Hongqing, Fu Lei. 3D Imaging Algorithm of Directional Borehole Radar Based on Improved Residual Method [J]. Journal of Jilin University(Earth Science Edition), 2018, 48(2): 402-410.
[2] Feng Xuan, Liang Shuaishuai, Enhedelihai Nilot, Zhang Minghe, Dong Zejun, Zhou Haoqiu, Qi Jiahui, Zhao Weichang. Classification and Recognition Technology of Underground Pipelines with Full Polarimetric GPR [J]. Journal of Jilin University(Earth Science Edition), 2018, 48(2): 364-372.
[3] Zeng Zhaofa, Li Wenben, Xi Jianjun, Huang Ling, Wang Zhejiang. Inverse Direction Imaging Method of Array Type GPR Based on DOA Estimation [J]. Journal of Jilin University(Earth Science Edition), 2017, 47(4): 1308-1318.
[4] Xi Jianjun, Zeng Zhaofa, Huang Ling, Cui Dandan, Wang Zhejiang. Characteristics of the Signal Polarization Field in Array Type Ground Penetrating Radar [J]. Journal of Jilin University(Earth Science Edition), 2017, 47(2): 633-644.
[5] Meng Qingsheng, Han Kai, Liu Tao, Gao Zhen. Leakage Detection in Waterproof Curtain of Soft Soil Foundation Pit [J]. Journal of Jilin University(Earth Science Edition), 2016, 46(1): 295-302.
[6] Xue Linfu, Li Wenqing, Zhang Wei, Chai Sheli, Liu Zhenghong. A Method of Block-Divided 3D Geologic Modeling in Regional Scale [J]. Journal of Jilin University(Earth Science Edition), 2014, 44(6): 2051-2058.
[7] LIU Cai, YANG Bao-jun, LU Qi, FENG Xuan, LIU Yang, WANG Dian. Fundamental Geophysical Progress on Heilongjiang Plate Tectonics [J]. J4, 2012, 42(5): 1497-1505.
[8] ZHANG Li-li, LIU Si-xin, WU Jun-jun, JIA Liang, KANG Xiao-tao. Wavelet Extraction of GPR Signals Based on Fractional Fourier Transform [J]. J4, 2012, 42(2): 569-574.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
Copyright © Journal of Jilin University(Earth Science Edition), All Rights Reserved.
Tel: +86-431-88502374；13756165364　E-mail: xuebao1956@jlu.edu.cn
Powered by Beijing Magtech Co. Ltd