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Site characterization using full waveform inversion

机译:使用全波形反演进行现场表征

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We discuss recent progress in the full-waveform-based imaging of probed soils, with geotechnical site characterization applications in mind. The primary goal is the reconstruction of the material profile of near-surface, arbitrarily heterogeneous formations, in terms of the formation's spatially distributed elastic properties, using elastic waves as the probing agent. We describe first the formulation and numerical resolution of the underlying time-dependent inverse medium problem; we report briefly on numerical experiments using synthetic data and artificial target soil profiles. These demonstrate robust reconstruction. We then report extensively on the details of a field experiment, whose records we subsequently used to drive the inversion algorithms in order to characterize the site where the field experiment took place. Lastly, we compare the inverted site profile with profiles obtained using the Spectral-Analysis-of-Surface-Waves (SASW) method, in an attempt to compare our methodology against a widely used concurrent inversion approach. We also compare the inverted profile at select locations with the results of independently performed CPT tests. Overall, whether exercised by synthetic or by physical data, the full waveform inversion method we discuss herein appears quite promising for the robust subsurface imaging of near-surface deposits in support of geotechnical site characterization investigations.
机译:我们讨论了在基于全波形的探测土壤成像中的最新进展,并牢记了岩土工程现场特征的应用。主要目标是使用弹性波作为探测剂,根据地层的空间分布弹性特性,重建近地表任意异质地层的材料剖面。我们首先描述基本的时变逆介质问题的公式和数值解析;我们简要介绍了使用合成数据和人工目标土壤剖面进行的数值实验。这些证明了健壮的重建。然后,我们对现场实验的细节进行了广泛的报告,随后将其记录用于驱动反演算法,以表征现场实验发生的地点。最后,我们将倒置站点剖面与使用“表面波谱分析”(SASW)方法获得的剖面进行比较,以尝试将我们的方法与广泛使用的并发倒置方法进行比较。我们还将所选位置的倒置轮廓与独立执行的CPT测试的结果进行比较。总体而言,无论是通过合成数据还是通过物理数据来执行,我们在此讨论的全波形反演方法对于支持岩土工地表征研究的近地表沉积物的鲁棒地下成像而言,似乎都是很有希望的。

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  • 来源
    《Soil Dynamics and Earthquake Engineering》 |2013年第4期|62-82|共21页
  • 作者单位

    Department of Civil Architectural and Environmental Engineering The University of Texas at Austin Austin TX 78712 USA The Institute for Computational Engineering and Sciences The University of Texas at Austin Austin TX 78712 USA;

    Department of Civil Architectural and Environmental Engineering The University of Texas at Austin Austin TX 78712 USA;

    Stress Engineering Services Inc. 13610 Westtand East Blvd. Houston TX 77041. USA;

    Department of Civil and Environmental Engineering Carnegie Mellon University Pittsburgh PA 15213 USA;

    The Institute for Computational Engineering and Sciences The University of Texas at Austin Austin TX 78712 USA;

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