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首页> 外文期刊>Surveys in Geophysics: An International Review Journal of Geophysics and Planetary Sciences >Automated Data Selection in the Tau-p Domain: Application to Passive Surface Wave Imaging
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Automated Data Selection in the Tau-p Domain: Application to Passive Surface Wave Imaging

机译：TAU-P域中的自动数据选择：应用于被动表面波成像

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摘要

In the recent decades, passive surface wave methods have gained much attention in the near-surface community due to their ability to retrieve low-frequency surface wave information. Temporal averaging over a sufficiently long period of time is a crucial step in the workflow to fulfill the randomization requirement of the stationary source distribution. Because of logistical constraints, passive seismic acquisition in urban areas is mostly limited to short recording periods. Due to insufficient temporal averaging, contributions from non-stationary sources can smear the stacked dispersion measurements, especially for the low-frequency band. We formulate a criterion in the tau-p domain for selective stacking of dispersion measurements from passive surface waves and apply it to high-frequency (> 1 Hz) traffic noise. The criterion is based on the automated detection of input data with a high signal-to-noise ratio in a desired velocity range. Modeling tests demonstrate the ability of the proposed criterion to capture the contributions from the non-stationary sources and classify the passive surface wave data. A real-world application shows that the proposed data selection approach improves the dispersion measurements by extending the frequency band below 5 Hz and attenuating the distortion between 6 and 13 Hz. Our results indicate that significant improvements can be obtained by considering tau-p-based data selection in the workflow of passive surface wave processing and interpretation.
机译：近几十年来，由于它们检索低频表面波信息的能力，无源表面波方法在近表面群体中获得了很多关注。在足够长的时间段内的时间平均是工作流程中的重要步骤，以满足静止源分布的随机化要求。由于后勤限制，城市地区的被动地震采集大多少量录音时期。由于时间平均不足，非静止源的贡献可以涂抹堆叠的色散测量，特别是对于低频带。我们制定了TAU-P域中的标准，以选择性地堆叠来自无源表面波的色散测量，并将其应用于高频（> 1 Hz）交通噪声。该标准基于所需速度范围内具有高信噪比的输入数据的自动检测。建模测试展示了所提出的标准从非静止源捕获贡献的能力并分类被动表面波数据。实际应用表明，所提出的数据选择方法通过将频带扩展到5Hz以下并衰减6到13 Hz之间的失真来改善色散测量。我们的结果表明，通过考虑基于TAU-P的数据选择，可以在被动表面波处理和解释的工作流程中考虑显着的改进。

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