Abstract Detection of near-surfaces features such as voids and faults is challenging due to the complexity of near-surface materials and the limited resolution of geophysical methods. Although multichannel, high-frequency, surface-wave techniques can provide reliable shear (S)-wave velocities in different geological settings, they are not suitable for detecting voids directly based on anomalies of the S-wave velocity because of limitations on the resolution of S-wave velocity profiles inverted from surface-wave phase velocities. Therefore, we studied the feasibility of directly detecting near-surfaces features with surface-wave diffractions. Based on the properties of surface waves, we have derived a Rayleigh-wave diffraction traveltime equation. We also have solved the equation for the depth to the top of a void and an average velocity of Rayleigh waves. Using these equations, the depth to the top of a void/fault can be determined based on traveltime data from a diffraction curve. In practice, only two diffraction times are necessary to define the depth to the top ofa void/fault and the average Rayleigh-wave velocity that generates the diffraction curve. We used four two-dimensional square voids to demonstrate the feasibility of detecting a void with Rayleigh-wave diffractions: a 2 m by 2 m with a depth to the top of the void of 2 m, 4 m by 4 m with a depth to the top of the void of 7 m, and 6 m by 6 m with depths to the top of the void 12 m and 17 m. We also modeled surface waves due to a vertical fault. Rayleigh-wave diffractions were recognizable for all these models after FK filtering was applied to the synthetic data. The Rayleigh-wave diffraction traveltime equation was verified by the modeled data. Modeling results suggested that FK filtering is critical to enhance diffracted surface waves. A real-world example is presented to show how to utilize the derived equation of surface-wave diffractions. © 2006 Elsevier B.V All rights reserved.

Abstract High-frequency surface-wave methods can provide reliable near-surface shear-wave (S-wave) velocity, which is a key parameter in many shallow-engineering applications, groundwater and environmental studies, and petroleum exploration. Recent research and key accomplishments at the China University of Geosciences at Wuhan into nearfield effects on surface-wave analysis provide not only insight into minimum-source geophone offsets required for generating high-quality surface-wave images but also provide a better understanding of the propagation characteristics of seismic wavefields through near-surface materials. New numerical modeling and dispersion-analysis algorithms are key tools used routinely in those studies. The modeling results illustrate very different energy-partitioning characteristics for Rayleigh and Love waves. Using a high-resolution linear Radon transform produces dispersion images with much better resolution and therefore represents a tool for more accurate separation and determination of phase velocities for different modes. Mode separation results in wavefield components that individually possess great potential for increasing horizontal resolution of S-wave velocity-field determinations. Amplitude corrections can significantly improve the accuracy of phase-velocity estimates from mixed-modal wavefields. Results from two simple models demonstrate how dramatic topographic changes can distort wavefields. This finding was the catalyst for suggesting that a topographic correction should be considered for surface-wave data acquired on a rugged ground surface. Phase-velocity inversion is an ill-posed problem. Rayleigh-wave sensitivity analysis reveals the difficulty in estimating S-wave velocities for a model with a low-velocity layer. Constraints in the model space are therefore necessary. Approximating cutoffs could help build a better initial model and provide critical information about the subsurface when higher modes are present.