Study on the influencing factors of combined processing of active and passive surface-wave data on dispersion imaging

Abstract

Active and passive surface-wave methods have garnered significant attention in the near-surface geophysical community for their non-destructive, non-invasive, low-cost, and accurate advantages in delineating subsurface shear (S)-wave velocity structures. They are increasingly being utilized to address numerous engineering and environmental problems. Surface waves obtained from actively excited sources such as a hammer and a harmonic shaker, however, lack low-frequency components, resulting in limited investigation depth. Conversely, passive surface waves such as microseisms (< 0.4 Hz, associated with natural ocean wave activity) and microtremor (>1 Hz, generated by cultural and wind sources) retrieved from ambient seismic noise typically lack high-frequency components, which is not conductive to characterizing fine near-surface structures. To overcome these frequency limitations, we employ a “mixed-source data” strategy, imposing active shot gathers into ambient noise data, to widen the frequency range of dispersion images and depth of investigative capabilities. We simulate both active and passive surface-wave data based on a two-layer model, noting that their dispersion images suffer from a mode kissing phenomenon at lower frequencies. By analyzing influencing factors such as the amplitude intensity, the signal-to-noise ratio and the excitation locations of active shot gathers, as well as the length of passive surface-wave data, we better understand their impacts on dispersion images from mixed-source surface-wave data. Simulation tests demonstrate that processing mixed-source data can effectively distinguish the mode kissing phenomenon. Moreover, the effectiveness of this strategy in enhancing the quality of dispersion image is verified, especially when surface-wave dispersion images perform poorly in either the low- or high-frequency bands. Additionally, a real-world example further demonstrates that processing mixed-source data offers significant advantages in improving the quality of dispersion images. This way provides a convenient and efficient measurement strategy for delineating shear-wave velocity profiles in finer shallow layers and deeper penetration depths.