戴前伟, 宁晓斌, 张彬. 基于共中心点道集约束的探地雷达波阻抗反演[J]. 煤田地质与勘探, 2020, 48(3): 211-218. DOI: 10.3969/j.issn.1001-1986.2020.03.030
引用本文: 戴前伟, 宁晓斌, 张彬. 基于共中心点道集约束的探地雷达波阻抗反演[J]. 煤田地质与勘探, 2020, 48(3): 211-218. DOI: 10.3969/j.issn.1001-1986.2020.03.030
DAI Qianwei, NING Xiaobin, ZHANG Bin. Common midpoint gather constraint-based impedance inversion of ground penetrating radar[J]. COAL GEOLOGY & EXPLORATION, 2020, 48(3): 211-218. DOI: 10.3969/j.issn.1001-1986.2020.03.030
Citation: DAI Qianwei, NING Xiaobin, ZHANG Bin. Common midpoint gather constraint-based impedance inversion of ground penetrating radar[J]. COAL GEOLOGY & EXPLORATION, 2020, 48(3): 211-218. DOI: 10.3969/j.issn.1001-1986.2020.03.030

基于共中心点道集约束的探地雷达波阻抗反演

Common midpoint gather constraint-based impedance inversion of ground penetrating radar

  • 摘要: 探地雷达(GPR)波阻抗反演是一种准确获取地下介质本征参数的有效方法,该方法依赖于测井资料提供的低频信息,而在GPR实际应用中,钻孔资料很少。为此,提出利用共中心点(CMP)速度分析为波阻抗反演提供大尺度纵向约束,实现在CMP速度分析结果的约束框架下,精细重构介质的介电参数信息。首先,以层状模型为算例,验证了CMP速度分析结果作为波阻抗反演的初始模型约束的可行性;在此基础上,开展了2个随机介质模型的波阻抗反演测试,反演结果的整体结构与模型接近,细微结构得到了较好的重构,与理论值的平相对误差为8.73%。结果表明,该方法在随机介质模型的探地雷达的波阻抗反演中更高效和经济,并且成像结果中包含着丰富的细节信息,在土壤介质其他物理参数估计中具有可行性和适用性。

     

    Abstract: GPR impedance inversion is an effective method to obtain accurately the intrinsic parameters of the subsurface medium. This method relies on low frequency information provided by logging data, but it is rarely accompanied by drilling in practical applications. To solve the problem, the common midpoint velocity analysis is employed to provide more low frequency component information for impedance inversion of GPR to finely reconstruct the dielectric parameter of subsurface in the framework of velocity-constrained inversion technique. Firstly, a layer model is specifically set up as an example to verify the feasibility of the developed velocity- constrained inversion to regulate the initial model. Then, the impedance inversion test is performed on two random media models, result of mean relative error from the true model is 8.73%, which show that the overall structure is more consistent with the real model, and more importantly, the microstructure is also finely depicted. The proposed method is more efficient and economical in impedance inversion of ground penetrating radar with random medium model, with more detailed information contained in imaging results, the method is very feasible and applicable in the estimation of other physical parameters in soil investigation.

     

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