Shallow Subsurface Detection with the Resonance Characteristics of Ambient Noise Recording

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Abstract Imaging near-surface structures, such as voids, tunnels, or high-contrast anomalies, is an essential and critical task in urban area underground engineering projects; the required accuracy is within a few meters vertically and horizontally, which poses considerable challenges to geophysical surveys in shallow subsurface detection. Geophysical methods like seismic are great tools for subsurface exploration with high resolution. Currently, since explosive sources are prohibited in urban areas, passive seismic methods that record the constant vibration signals generated by natural and human activities have become more desirable. Thus, this abstract presents a novel non-destructive geophysical approach using ambient noise recording, namely seismo-acoustic resonance imaging. This approach is mainly based on the analysis of the resonance frequencies content information within the data, related to the mechanical properties of structures under investigation. These resonance frequencies will then be translated into depth-domain images using a kind of layer-stripping strategy; Further, the images are combined with results of other geophysical methods (GRP, surface wave analysis, autocorrelation, etc.) for necessary interpretation. In practice, as a low-cost single-station geophysical technique, resonance imaging is readily applicable to a broad range of scales, which meets the need for spatial suitability, and efficiency in engineering investigations. Two examples are presented in the paper, as the first is elaborated on a known metro tunnel, and the second is demonstrated in an unknown investigation site. The results of two experiments have shown resonance imaging to be very well adapted for shallow subsurface detection.

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