Three-dimensional imaging of near-surface structure using P-wave extracted from traffic and urban noise sources at Xiadian fault: A case study

Abstract:

We performed the study to create a near-surface three-dimensional (3D) P-wave image using traffic and urban noise sources. Unlike the ambient noise measured over a long period of time, which is usually used in studies of imaging the macro-scale subsurface structures, the traffic and urban noise sources have different characteristics that signals are observed randomly with short cycles. Therefore, the proper processing of these signals affects significantly on the result of the image. In the imaging processing, an autocorrelation method was used to obtain the zero offset seismic traces at each measured receiver position because of relatively small influence from the rapid horizontal velocity variation.

Using the field data obtained from the Xiadian fault area, we suggested the effective processing flow of 3D body wave imaging through the analysis of field data and noise identification. Removal of surface wave with consistent and high amplitude is key parameter in successful data processing. To reduce the effect of surface wave, we introduced three noise suppression processes.

For verifying the validity of the constructed 3D body wave image cube, we compared our P-wave image with the S-wave velocity section obtained by ambient noise tomography using passive surface waves at this region. Even though the relatively short periods of recorded data were used this study, we could delineate the variation of the subsurface structure on the left and right sides of the fault.