Surface waves can be categorized into active-source surface waves and noise-source surface waves based on their signal sources, corresponding to active source exploration and passive source exploration methods, respectively. Active source exploration requires artificial excitation, which not only damages the surrounding environment but is also susceptible to interference from ambient noise, thus demanding very high requirements for the measurement site. In contrast, passive source exploration does not require seismic source excitation, does not harm the environment, and has relatively simple data collection, making it cost-effective and environmentally friendly, with significant research value. This paper mainly introduces the imaging principle of ambient noise exploration methods. Under certain circumstances, ambient noise recorded over long periods between two stations can be used to derive dispersion curves through Green's functions, thus enabling the inversion of subsurface structures. To validate the method's effectiveness, Tesseral was used to establish a model (a simple horizontal layered model) to obtain noise data from different source locations and densities. Surface wave records were extracted and compared to analyze the intensity of surface wave records from different strata and source locations, studying the impact of different source densities and locations on surface wave imaging, and exploring the feasibility of the research. Then, high-quality fundamental mode dispersion curves from each group were extracted to analyze the reasons for varying quality in fundamental mode surface waves across different dispersion images, and the subsurface structure was inverted. Finally, practical data were used to test the applicability of the fundamental mode dispersion curve inversion.
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Yang Feng (2024) studied this question.
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