Imaging subsurface structure over the Xiadian fault using P waves extracted from urban traffic noise

Abstract

The imaging of subsurface structures is an essential task in subsurface engineering projects; it provides information regarding the locations of active faults and layer boundaries. Among the methods available for imaging of subsurface structures, the body wave imaging method using urban traffic noise has recently attracted attention because it permits continuous measurement at low cost in urban areas. however, because the urban traffic noise signal used for imaging on the engineering scale has characteristics that differ from the ambient noise used on the crustal scale, the conventional crustal-scale data processing workflow should be modified through systematic data analysis. In this study, traffic noise sources were systematically analysed using field data obtained over the Xiadian fault in Hebei province, China. The traffic noise signals were recorded in various patterns because of diverse incoming directions and show marked amplitude changes depending on time of recording. The overlapping signals originating from opposite directions generate spurious events and noise in the seismic interferometry images; constant processing parameters cannot respond to the large amplitude changes. In this study, to remove surface waves with markedly changing amplitude, we applied actively varying threshold values to each set of traces using the moving average of amplitude changes within the trace. In addition, the signals originating from diverse directions were separated into negative and positive slopes through the f-k filter; the interference generated by overlapping signals was minimized by applying data processing (e.g. median filtering and high amplitude removal) separately to the negative and positive slopes of each simultaneously acquired trace gather. Due to the modified data processing workflow, most spurious events were successfully suppressed in the final stacked image compared with those produced using the conventional data processing workflow, and reflections were imaged more clearly. Fault spatial locations and layer boundary depth variation in the final image obtained by the modified processing workflow were similar to those reported in previous studies.