Recursive impedance inversion of ground-penetrating radar data in stochastic media
Zeng Zhao-Fa1, Chen Xiong1, Li Jing1,2, Chen Ling-Na1, Lu Qi1, and Liu Feng-Shan2
1. College of Geo-Exploration Science and Technology, Jilin University, Changchun 130026, China.
2. Applied Mathematics Research Center, Delaware State University, Dover, DE 19901, USA.
Abstract：
The travel time and amplitude of ground-penetrating radar (GPR) waves are closely related to medium parameters such as water content, porosity, and dielectric permittivity. However, conventional estimation methods, which are mostly based on wave velocity, are not suitable for real complex media because of limited resolution. Impedance inversion uses the reflection coefficient of radar waves to directly calculate GPR impedance and other parameters of subsurface media. We construct a 3D multiscale stochastic medium model and use the mixed Gaussian and exponential autocorrelation function to describe the distribution of parameters in real subsurface media. We introduce an elliptical Gaussian function to describe local random anomalies. The tapering function is also introduced to reduce calculation errors caused by the numerical simulation of discrete grids. We derive the impedance inversion workflow and test the calculation precision in complex media. Finally, we use impedance inversion to process GPR field data in a polluted site in Mongolia. The inversion results were constrained using borehole data and validated by resistivity data.
本研究由教育部博士点基金项目（编号：20130061110060博导类）、博士后基金项目（编号：2015M571366）和国家自然科学基金项目（编号：41174097）联合资助，也得到了美国DoD项目“先进数学算法中心”（编号：Center for Advanced Algorithms）和ARO（编号：W911NF-11-2-0046）项目支持。
Zeng Zhao-Fa,Chen Xiong,Li Jing et al. Recursive impedance inversion of ground-penetrating radar data in stochastic media[J]. APPLIED GEOPHYSICS, 2015, 12(4): 615-625.
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2015, Vol. 12 
