Migrating Steep-Obliquity Interfaces in GPR Images Based on a Crossed Differential Operator
Migrating Steep-Obliquity Interfaces in GPR Images Based on a Crossed Differential Operator
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基于交叉微分算子的探地雷达图像中大倾角界面的迁移
DOI：
10.1109/lgrs.2020.3028745
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发表时间：
2022
影响因子：
4.8
通讯作者：
Bin Zhang
中科院分区：
文献类型：
--
作者：
Qianwei Dai;Juntao Yin;Bin Zhang
利用探地雷达（GPR）数据的偏移成像可以实现地下填图。基于有限差分（FD）的偏移可以有效地实现横向非均质介质的快速成像。然而，在确定任何陡倾角界面的真实形态时，这种迁移固有地存在精度不足的问题。在这篇文章中，我们提出了一种基于交叉微分算子（CDO）和逆时偏移（RTM）策略的新算法，将反射重新聚焦到其精确位置。在非近似方程的基础上，采用不含算子近似的隐式Crank-Nicolson格式，可以近似沿波传播的特征方向外推波场。我们利用合成数据和现场数据确定了该算法的潜力。对于合成数据，我们考虑了多几何场景，包括不同角度的界面、不同尺寸的球体和横向非均质性。我们特别关注外推精度、幅频聚焦能力、熵分析和成像误差。在现场数据测试中，我们发现可以确定更细的陡斜界面形态。可解释性和可识别细节的数量也可以得到改善。这一改进使得基于cdo的偏移成为一种非常有前途的工具，用于更精细的浅层地下成像。
Subsurface mapping can be implemented by the migration imaging of ground penetrating radar (GPR) data. Finite difference (FD)-based migration can effectively achieve fast imaging in media with lateral heterogeneity. However, this migration inherently suffers from insufficient accuracy in determining the true morphology of any steep-obliquity interface. In this letter, we propose a new algorithm based on crossed differential operator (CDO) and reverse-time migration (RTM) strategy to refocus the reflections back into its precise location. By employing the implicit Crank–Nicolson scheme without any operator approximations, wave field can be extrapolated nearly along the characteristic directions of wave propagation based on the nonapproximate equations. We determined the potential of the algorithm using synthetic and field data. For synthetic data, we consider a multigeometry scenario, including different angle interfaces, different-sized spheres, and lateral heterogeneity. In particular, we focus on extrapolation accuracy, amplitude–frequency focusing ability, entropy analysis, and imaging errors. In the field data test, we found that the finer morphology of the steeper-obliquity interfaces can be determined,.the interpretability and amount of discernible details can also be improved. This improvement makes CDO-based migration a very promising tool for the finer imaging of shallow subsurface.