Towards 3D full-wave inversion for GPR

Francis Watson
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引用次数: 5

Abstract

Full-wave inversion (FWI) for GPR is an imaging approach in which one tries to determine the parameters describing the subsurface (such as permittivity and permeability) which would best reproduce the observed data, via a non-linear least-squares optimisation problem. The approach can account for multiple-scattering and multi-path information in the data, and results in quantitative information about the subsurface. The method is now well studied for seismic imaging, as well as for GPR imaging in 2D. However, taking a 2D imaging approach limits the applicability and accuracy of FWI whenever significant 3D effects have been observed, such as out-of-plane scattering. We present a theoretical approach to FWI for GPR in 3D, which utilises Total Variation regularisation and a novel Hessian approximation, as well as a coupled finite-element boundary-integral solver for Maxwell's equations to simulate the GPR forward problem. We test the algorithm with a numerical experiment into the reconstruction of a domain containing nearby targets buried in a cluttered, stochastically varying, background soil medium.
探地雷达三维全波反演研究
GPR的全波反演(FWI)是一种成像方法,通过非线性最小二乘优化问题,试图确定描述地下的参数(如介电常数和渗透率),这些参数最能再现观测数据。该方法可以考虑数据中的多重散射和多路径信息,从而获得地下的定量信息。目前,该方法已经在地震成像和GPR二维成像中得到了很好的研究。然而,当观察到明显的3D效果(如面外散射)时,采用2D成像方法会限制FWI的适用性和准确性。我们提出了一种三维探地雷达FWI的理论方法,该方法利用全变分正则化和一种新的Hessian近似,以及麦克斯韦方程的耦合有限元边界积分求解器来模拟探地雷达正演问题。我们通过一个数值实验来测试该算法,以重建一个包含附近目标的区域,这些目标被埋在一个杂乱的、随机变化的背景土壤介质中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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