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Deterministic deconvolution for GPR data in the t-f domain

机译:t-f域中GPR数据的确定性反卷积

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Deconvolution methods encounter difficulties in increasing the temporal resolution of GPR data due mainly to non-stationarity of the records. GPR wavelets are typically mixed phase, which is additionally a major failure of standard deconvolution methods. Here, we propose a deterministic deconvolution method for GPR data, implemented in the t-f domain, which utilizes narrow time windows and sets spectral balancing as a precondition. A reference wavelet is estimated experimentally for the calculation of a time varying deconvolution operator. Its phase variation is extracted from the spectrally balanced deconvolved GPR trace. The algorithm, tested on synthetic and real data, produces very promising results. In particular the deconvolved GPR section acquired over sands exhibits better temporal resolution and reveals reflected waves travelling through high loss media.
机译:去卷积方法在增加GPR数据的时间分辨率方面遇到困难,这主要是由于记录的不稳定。 GPR小波通常是混合相位,这是标准反卷积方法的主要失败。在此,我们提出了一种在t-f域中实现的GPR数据确定性反卷积方法,该方法利用狭窄的时间窗口并将频谱平衡设置为前提。通过实验估计参考小波以计算时变反卷积算子。它的相位变化是从频谱平衡的反卷积GPR迹线中提取的。该算法在合成和真实数据上进行了测试,产生了非常有希望的结果。特别是在砂岩上采集的反褶积GPR断面表现出更好的时间分辨率,并揭示了通过高损耗介质传播的反射波。

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