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2D frequency-domain full-waveform inversion of GPR data: Permittivity and conductivity imaging

机译:GPR数据的二维频域全波形反演:介电常数和电导率成像

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Full waveform inversion of Ground Penetrating Radar data is a promising and challenging technique. As both dielectric permittivity and electrical conductivity should be recovered, the associated inverse problem is intrinsically multi-parameter. It requires to properly account for the influence of the Hessian matrix to mitigate the trade-offs between constitutive parameters. Recently, a first step in this direction was performed with the l-BFGS quasi-Newton method, which is based on an approximation of the inverse Hessian computed from previous gradient estimations. We propose to go further in solving locally the Newton equation related to the optimization workflow. For this purpose, we implement the truncated Newton method where the computation of the gradient and Hessian-vector products are respectively based on first-order and second-order adjoint state methods. On a synthetic case study, using the TE mode with borehole and surface acquisitions, we compare our results with those obtained using the l-BFGS method and we show an improvement in the precision of reconstructed parameters. A better decoupling between the two parameters is obtained with the truncated Newton method.
机译:探地雷达数据的全波形反演是一种很有前途且具有挑战性的技术。由于应同时恢复介电常数和电导率,因此相关的反问题本质上是多参数。它需要适当考虑Hessian矩阵的影响,以减轻本构参数之间的折衷。最近,使用l-BFGS拟牛顿法在该方向上迈出了第一步,该方法基于从先前的梯度估计中计算出的逆黑森州近似值。我们建议在本地求解与优化工作流相关的牛顿方程时要走得更远。为此,我们实现了截断牛顿法,其中梯度和Hessian向量乘积的计算分别基于一阶和二阶伴随状态方法。在一个综合案例研究中,将TE模式与井眼和地面采集一起使用,我们将我们的结果与使用l-BFGS方法获得的结果进行了比较,并显示了重构参数精度的提高。截断的牛顿法可以在两个参数之间实现更好的解耦。

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