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Frequency–Wavenumber (FK)-Based Data Selection in High-Frequency Passive Surface Wave Survey

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Abstract

Passive surface wave methods have gained much attention from geophysical and civil engineering communities because of the limited application of traditional seismic surveys in highly populated urban areas. Considering that they can provide high-frequency phase velocity information up to several tens of Hz, the active surface wave survey would be omitted and the amount of field work could be dramatically reduced. However, the measured dispersion energy image in the passive surface wave survey would usually be polluted by a type of “crossed” artifacts at high frequencies. It is common in the bidirectional noise distribution case with a linear receiver array deployed along roads or railways. We review several frequently used passive surface wave methods and derive the underlying physics for the existence of the “crossed” artifacts. We prove that the “crossed” artifacts would cross the true surface wave energy at fixed points in the fv domain and propose a FK-based data selection technique to attenuate the artifacts in order to retrieve the high-frequency information. Numerical tests further demonstrate the existence of the “crossed” artifacts and indicate that the well-known wave field separation method, FK filter, does not work for the selection of directional noise data. Real-world applications manifest the feasibility of the proposed FK-based technique to improve passive surface wave methods by a priori data selection. Finally, we discuss the applicability of our approach.

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Acknowledgements

This study is supported by the National Natural Science Foundation of China under Grant No. 41774115, the National Nonprofit Institute Research Grant of Institute for Geophysical and Geochemical Exploration, Chinese Academy of Geological Sciences under Grant No. WHS201306. The authors thank crews of AoCheng Technology for their help in data collection.

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Cheng, F., Xia, J., Xu, Z. et al. Frequency–Wavenumber (FK)-Based Data Selection in High-Frequency Passive Surface Wave Survey. Surv Geophys 39, 661–682 (2018). https://doi.org/10.1007/s10712-018-9473-3

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