Surface Wave Methods for Near-Surface Site Characterization

2014 ◽  
Author(s):  
Sebastiano Foti ◽  
Carlo Lai ◽  
Glenn J. Rix ◽  
Claudio Strobbia
2016 ◽  
Vol 4 (4) ◽  
pp. SQ59-SQ69 ◽  
Author(s):  
Mitchell Craig ◽  
Koichi Hayashi

Seismic surface wave methods are effective tools for estimating S-wave velocity in urban areas for near-surface site characterization and geologic hazard assessment. A surface wave survey can provide quantitative site-specific measurement of physical properties needed for the design of earthquake-resistant structures. We successfully used a combined active and passive seismic surface wave method to estimate the S-wave velocity in the upper 30 m at sites with a range of geologic conditions. At five of the six sites, multichannel analysis of surface waves (MASW) and microtremor array method (MAM) methods were used. The MAM method could not be used at one site due to insufficient ambient noise. Data from the active method (MASW) contained higher frequencies that contributed to higher resolution of the near-surface zone, whereas passive data (MAM) contained lower frequencies that provided deeper penetration. Phase velocities from the two methods were in good agreement in the frequency range where they overlapped. Surface wave dispersion curves from the two methods were used to prepare an initial velocity model, and a nonlinear inversion was performed to obtain an improved velocity-depth profile. The use of a multimethod data set provided greater confidence in velocity measurements. The six sites of this study may be classified as belonging to two main groups based on S-wave velocities and geologic materials. Two sites are located in the East Bay Hills on Mesozoic bedrock, and four sites are located on Holocene sedimentary units. The highest [Formula: see text] was [Formula: see text] (class C), at a site with fractured and weathered bedrock exposed in a geotechnical trench at 1–2 m depth. The four sites on Holocene sedimentary units have [Formula: see text] values ranging from 207 to [Formula: see text] (class D).


Geophysics ◽  
2019 ◽  
Vol 84 (1) ◽  
pp. B95-B105 ◽  
Author(s):  
Yao Wang ◽  
Richard D. Miller ◽  
Shelby L. Peterie ◽  
Steven D. Sloan ◽  
Mark L. Moran ◽  
...  

We have applied time domain 2D full-waveform inversion (FWI) to detect a known 10 m deep wood-framed tunnel at Yuma Proving Ground, Arizona. The acquired seismic data consist of a series of 2D survey lines that are perpendicular to the long axis of the tunnel. With the use of an initial model estimated from surface wave methods, a void-detection-oriented FWI workflow was applied. A straightforward [Formula: see text] quotient masking method was used to reduce the inversion artifacts and improve confidence in identifying anomalies that possess a high [Formula: see text] ratio. Using near-surface FWI, [Formula: see text] and [Formula: see text] velocity profiles were obtained with void anomalies that are easily interpreted. The inverted velocity profiles depict the tunnel as a low-velocity anomaly at the correct location and depth. A comparison of the observed and simulated waveforms demonstrates the reliability of inverted models. Because the known tunnel has a uniform shape and for our purposes an infinite length, we apply 1D interpolation to the inverted [Formula: see text] profiles to generate a pseudo 3D (2.5D) volume. Based on this research, we conclude the following: (1) FWI is effective in near-surface tunnel detection when high resolution is necessary. (2) Surface-wave methods can provide accurate initial S-wave velocity [Formula: see text] models for near-surface 2D FWI.


2019 ◽  
Vol 217 (1) ◽  
pp. 206-218 ◽  
Author(s):  
Khiem T Tran ◽  
Majid Mirzanejad ◽  
Michael McVay ◽  
David Horhota

Sign in / Sign up

Export Citation Format

Share Document