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Theory for 1D GPR data inversion for a dissipative layered medium

机译:耗散分层介质的一维GPR数据反演理论

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We present a data driven method of full waveform inversion in one dimension. This means that the inversion is carried out as a sequence of processing steps. The first step is known as Marchenko redatuming. In this step we retrieve focusing functions from the measured data. In the second step we isolate the last event in the focusing function to obtain the local reflection coefficient of a particular reflecting boundary. This is done for the dissipative and equivalent effectual model. An effectual medium amplifies a propagating wave in the same way as a dissipative medium attenuates it. From these two models the reflection coefficient of the corresponding lossless medium can be computed. This is then inverted for the electric permittivity. Once the permittivity is found, the individual layer thicknesses are obtained from the travel times. The ratio of the reflection coefficient in the physical and effectual medium provides an estimate of the attenuation in each layer from which the conductivity in each layer can be found. We show that in this case the full waveform inversion is a linear problem. We need reflection and transmission data measured at two sides of the medium. We use an unconditionally convergent iterative technique to compute the focusing functions. The method only needs the up-and downgoing parts of the electric field at the receiver levels. A 1D numerical example with a lossy model shows that the proposed GPR inversion method is effective on modeled data.
机译:我们提出了一维全波形反演的数据驱动方法。这意味着反转是作为一系列处理步骤进行的。第一步称为Marchenko重新计算。在这一步中,我们从测量的数据中获取聚焦函数。在第二步中,我们隔离聚焦函数中的最后一个事件,以获得特定反射边界的局部反射系数。这是针对耗散等效等效模型完成的。有效介质以与耗散介质衰减传播波相同的方式放大传播波。从这两个模型可以计算出相应的无损介质的反射系数。然后将其反转为介电常数。一旦发现介电常数,就可以从行进时间中获得各个层的厚度。物理和有效介质中反射系数的比值提供了对每层衰减的估计,从中可以发现每层的电导率。我们表明,在这种情况下,全波形反转是一个线性问题。我们需要在介质两侧测量的反射和透射数据。我们使用无条件收敛的迭代技术来计算聚焦函数。该方法仅需要在接收器级别上电场的上升和下降部分。具有损耗模型的一维数值示例表明,所提出的GPR反演方法对建模数据有效。

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