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Reconstruction, with tunable sparsity levels, of shear wave velocity profiles from surface wave data
Geophysical Journal International ( IF 2.8 ) Pub Date : 2021-02-17 , DOI: 10.1093/gji/ggab068
Giulio Vignoli 1, 2 , Julien Guillemoteau 3 , Jeniffer Barreto 1 , Matteo Rossi 4
Affiliation  

SUMMARY The analysis of surface wave dispersion curves is a way to infer the vertical distribution of shear wave velocity. The range of applicability is extremely wide: going, for example, from seismological studies to geotechnical characterizations and exploration geophysics. However, the inversion of the dispersion curves is severely ill-posed and only limited efforts have been put in the development of effective regularization strategies. In particular, relatively simple smoothing regularization terms are commonly used, even when this is in contrast with the expected features of the investigated targets. To tackle this problem, stochastic approaches can be utilized, but they are too computationally expensive to be practical, at least, in case of large surveys. Instead, within a deterministic framework, we evaluate the applicability of a regularizer capable of providing reconstructions characterized by tunable levels of sparsity. This adjustable stabilizer is based on the minimum support regularization, applied before on other kinds of geophysical measurements, but never on surface wave data. We demonstrate the effectiveness of this stabilizer on (i) two benchmark—publicly available—data sets at crustal and near-surface scales and (ii) an experimental data set collected on a well-characterized site. In addition, we discuss a possible strategy for the estimation of the depth of investigation. This strategy relies on the integrated sensitivity kernel used for the inversion and calculated for each individual propagation mode. Moreover, we discuss the reliability, and possible caveats, of the direct interpretation of this particular estimation of the depth of investigation, especially in the presence of sharp boundary reconstructions.

中文翻译:

从表面波数据重建剪切波速度剖面,稀疏度可调

总结 面波频散曲线分析是推断横波速度垂直分布的一种方法。适用范围非常广泛:例如,从地震学研究到岩土特征和勘探地球物理学。然而,离散曲线的反演是严重不适定的,并且在开发有效的正则化策略方面只付出了有限的努力。特别是,通常使用相对简单的平滑正则化项,即使这与所研究目标的预期特征相反。为了解决这个问题,可以使用随机方法,但它们的计算成本太高而无法实用,至少在大型调查的情况下是这样。相反,在确定性框架内,我们评估了正则化器的适用性,该正则化器能够提供以可调稀疏度为特征的重建。这种可调稳定器基于最小支持正则化,以前应用于其他类型的地球物理测量,但从未应用于表面波数据。我们证明了这种稳定器在 (i) 两个基准(公开可用的)地壳和近地表尺度的数据集和 (ii) 在充分表征的地点收集的实验数据集的有效性。此外,我们讨论了估计调查深度的可能策略。该策略依赖于用于反演的集成灵敏度内核,并针对每个单独的传播模式进行计算。此外,我们讨论了可靠性和可能的​​警告,
更新日期:2021-02-17
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