Surface wave methods, commonly applied in diverse fields, encounter challenges in complex subsurface environments due to limitations inherent in traditional inversion techniques. Conventional one-dimensional inversion (1DI), with its reliance on fixed grids and deterministic linear approaches, often introduces biases, diminishing lateral resolution. Laterally constrained inversion (LCI) improves robustness by addressing lateral coherency but falls short in delineating arbitrary interfaces due to its dependency on fixed grid models. The advent of Distributed Acoustic Sensing (DAS) technology offers extensive seismic data, yet its potential for high-resolution imaging remains underutilized. We introduce a Multigrid Spatially Constrained Dispersion Curve Inversion (MCI) method to overcome these challenges, aiming to harness high-resolution DAS surface wave imaging capabilities. This paper details the MCI scheme, evaluates its efficacy through synthetic tests, and applies it to a DAS field study in Imperial Valley, California. Our findings demonstrate a refined, higher-resolution S-wave velocity model, offering new insights into the region’s fault system and emphasizing the necessity of improved spatial resolution in large-scale geophysical studies.

Surface wave methods are non-invasive, low-cost, and robust approaches to image near-surface S-wave velocity (Vs) structure. In terms of the energy source types, they can be classified in two groups: active-source surface wave methods and passive-source surface wave methods. A clean and high-resolution dispersion image is critical for the subsequent dispersion curve picking as well as Vs inversion for either the active-source surface wave methods or the passive-source surface wave methods. However, aliasing or other artifacts are almost inevitable in surface wave dispersion measurements in practice, and they can seriously pollute the measured dispersion spectra. It is significant to figure out how they are generated, how they affect the dispersion measurement, and how they can be attenuated. We provide the first comprehensive review on artifacts that are frequently observed in surface wave dispersion measurements, and summary them into three general types, including artifacts from spare spatial sampling, artifacts from array response, and artifacts from weak coherent signals. Both numerical and field examples, as well as mathematic derivations, are presented to help reader understand the generations of the various types artifacts and the way to attenuate them. This work will help us understand the complex components on the measured surface wave dispersion spectra, and lead to potential improvements on dispersion measurements.

Tomographic imaging based on long-term ambient seismic noise measurements, mainly the phase information from surface waves, has been shown to be a powerful tool for geothermal reservoir imaging and monitoring. In this study, we utilize seismic noise data from a dense nodal array (192 3C nodes within 20km2) over a ultra-short observation period (4.7 days) to reconstruct surface waves and determine the high-resolution (0.2km) three-dimensional (3-D) S wave velocity structure beneath a rural town in Zhejiang, China. We report the advantage of cross-coherence over cross-correlation in suppressing pseudo-arrivals caused by persistent sources. We use ambient noise interferometry to retrieve high quality Rayleigh waves and Love waves. Body waves are also observed on the R-R component interferograms. We apply phase velocity dispersion measurements on both Rayleigh waves and Love waves and automatically pick more than 23,000 dispersion curves by using a Machine Learning technique. 3-D surface wave tomographic results after depth inversion indicate low-velocity anomalies (between -1% and -4%) from the surface to 2km depth in the central area. Combined with the conductive characteristics observed on resistivity profile, the low-velocity anomalies are inferred to be a fluid saturated zone of highly fractured rock. Joint interpretation based on HVSR measurements, and existing temperature and fluid resistivity records observed in a nearby well, suggests the existence of the high-temperature geothermal field through the fracture channel. Strong correlation between HVSR measurements and S wave velocity model sheds light on the potential of extraction of both amplitude and phase information from ambient noise.