## 5 Discussion  
Since the widespread application of passive seismic exploration, an increasing number of challenges have emerged. The primary issue is that passive seismic data typically suffer from a low signal-to-noise ratio, with various singles mixed together and difficult to separate. This makes it challenging to obtain high-quality surface wave signals and reflected signals from passive data, which impacts the quality of further processing results for surface waves and reflected waves. Consequently, it often becomes necessary to combine the results from active seismic exploration to infer information about both the shallow and deep subsurface. Conventional processing methods, such as bandpass filtering, are inadequate for effectively separating surface wave noise and body wave noise. This paper presents a method that combines SWT to identify body wave noise and surface wave noise in the  
Figure 10: Surface wave inversion results: (**a**) reconstruction of surface waves after SWT processing; (**b**) surface wave dispersion imaging; (**c**) surface wave inversion results, where blue represents the initial model, green represents the true model, and red represents the inversion result. original passive data and effectively reconstructs the body wave and surface wave signals. In this paper, we validate the effectiveness of the proposed method through numerical simulations. Additionally, we compare it with bandpass filtering to demonstrate the advantages of our approach. Additionally, the reconstructed surface waves and body waves are inverted separately, and by combining surface wave inversion for shallow velocity structures and reflection wave imaging for deeper structures, comprehensive subsurface information can be obtained. We compared the obtained subsurface velocity structure with the actual velocity model to verify the accuracy of the method, providing a feasible technical workflow for independent passive seismic exploration. For the processing of real data, the simulated data used in this study have relatively balanced energy, so amplitude balancing was not applied. In contrast, the signals collected by geophones in real data are more complex, and the data volume is significantly larger, and to address issues related to the unevenness of the frequency and amplitude spectra, we propose that the high-resolution characteristics of SWT in the time-frequency domain can be utilized for feature recognition of different wave signals. Energy balancing in the time-frequency domain can also enhance weaker high-frequency energy, making it easier to distinguish between surface wave noise and body wave noise. For the large volume of real passive seismic data and the computational challenges it presents, parallel processing using both CPU and GPU can be employed to accelerate the calculations ([PERSON] et al., 2022) [44]. Furthermore, regarding the numerical simulation of passive sources, this study currently employs the finite-difference method. However, handling boundary shapes in complex fluid regions is challenging with this approach. Numerical simulation based on lattice element modeling is more suitable for fine-scale structures and complex fluid regions ([PERSON] et al., 2016; [PERSON] et al., 2020) [45; 46; 47]. In future work, we will explore the application of lattice element modeling in passive seismic exploration and investigate the impact of fluid effects in fractured rock masses on the wavefield. Conceptualization, X.L. and Z.X. ; methodology, X.L. and F.Z. ; validation, X.L. and X.G. ; formal analysis, X.L. ; investigation, X.L. ; resources, X.G. and Z.X. ; data curation, X.L. and F.Z. ; writing--original draft preparation, X.L. ; writing--review and editing, Z.X. and F.Z. ; supervision, F.Z. All authors have read and agreed to the published version of the manuscript. This research was funded by the National Natural Science Foundation of China (Grant Nos. 42274164 and 42074151) and the Deep Earth Probe and Mineral Resources Exploration-National Science and Technology Major Project, 2024 ZD1004101.