Yudi Pan

Reason and condition for mode kissing in MASW method

Identifying correct modes of surface waves and picking accurate phase velocities are critical for obtaining an accurate S-wave velocity in MASW method. In most cases, inversion is easily conducted by picking the dispersion curves corresponding to different surface-wave modes individually. Neighboring surface-wave modes, however, will nearly meet (kiss) at some frequencies for some models. Around the frequencies, they have very close roots and energy peak shifts from one mode to another. At current dispersion image resolution, it is difficult to distinguish different modes when mode-kissing occurs, which is commonly seen in near-surface earth models. It will cause mode misidentification, and as a result, lead to a larger overestimation of S-wave velocity and error on depth. We newly defined two mode types based on the characteristics of the vertical eigendisplacements calculated by generalized reflection and transmission coefficient method. Rayleigh-wave mode near the kissing points (osculation points) change its type, that is to say, one Rayleigh-wave mode will contain different mode types. This mode type conversion will cause the mode-kissing phenomenon in dispersion images. Numerical tests indicate that the mode-kissing phenomenon is model dependent and that the existence of strong S-wave velocity contrasts increases the possibility of mode-kissing. The real-world data shows mode misidentification caused by mode-kissing phenomenon will result in higher S-wave velocity of bedrock. It reminds us to pay attention to this phenomenon when some of the underground information is known.

Feasibility of Detecting Groundwater Flow via Analyzing Radial Anisotropy Estimated by Surface Waves

Summary Groundwater flow is one of the most important topics in water resource and agriculture. Most alluvial stratum consisted of heterogeneous sedimentary deposits has a different depositional structure. Because of depositional processes, the groundwater flow greatly influence the orientation of underground medium, which further affect the radial anisotropy of underground medium, and change the SH- or (and) SV- wave velocities. We propose to use radial anisotropy estimated by surface waves to detect ground water flow. SH- and SV-wave velocities are obtained from Love waves and Rayleigh waves acquired along the same survey line, respectively. By analyzing the radial anisotropy, we can detect the direction of ground water flow as well as the depth of it. Two field tests are performed at two different sites, both of which prove the feasibility of detecting groundwater flow by analyzing radial anisotropy.

Estimating Q Factor from Multi-mode Shallow-Seismic Surface Waves

Surface waves are widely used in delineating subsurface structures. Surface-wave phase information (phase velocity) can be used for estimating near-surface S-wave velocity, and its amplitude information (attenuation coefficient) is used for characterizing near-surface quality (Q) factor. Multi-modal phenomenon of surface waves is commonly seen in shallow seismic, however, the existence of higher modes will introduce errors in the calculated surface-wave attenuation coefficients, which further reduces the accuracy of estimated Q factors. We propose to separate surface waves of different modes, and calculate surface-wave attenuation coefficients using single mode. Two synthetic cases are presented to show that errors would be introduced in the attenuation coefficients when multi-mode surface waves and body waves exist, and can be excluded if different modes of surface waves and body waves are separated beforehand. A real-world case demonstrates the feasibility of inverting surface-wave attenuation coefficients for the estimation of Q factor with our proposed method.

Sequential Phase-velocity and waveform inversion of shallow-seismic surface waves : A field example for bedrock mapping

Summary Surface waves are widely used to determine near-surface S-wave velocity structures. The individual surface-wave phase-velocity inversion and waveform inversion suffers from relatively low resolution and high ambiguity, respectively. We propose to adopt a sequential phase-velocity and waveform inversion of surface waves to delineate near-surface materials. The phase-velocity inversion result is smoothed and used as the initial model for waveform inversion. We applied our method to a field data collected in Olathe, USA. Shape of the bedrock is clearly delineated in the inversion result. The sequential-inversion result nicely agrees with the borehole data, indicating relatively high reliability of it. This study shows that the sequential phase-velocity and waveform inversion can provide an effective way for high-resolution imaging of near-surface materials.