Determining subsurface structure from microtremors using passive arrays: An alternative to active seismic surveys
The amount of damage to a structure during an earthquake is related to the ground motion at that site. However, different types of rock and sediment react differently to seismic waves. Some units will have a tendency to amplify seismic energy while other units will attenuate energy. Therefore, it is important to study seismic waves that propagate through specific soil types to understand site response. Active seismic surveys are susceptible to noise interference and are limited due to spatial need, while boreholes are costly. I have applied a new method using a passive array to study Rayleigh waves from microtremors, waves originating from building appliances, cars, pedestrians walking, etc. Instead of using sines and cosines to estimate the signal, as in traditional Fourier transform analysis, I have developed a technique using a wavelet transform process to analyze the signal. The array was located in Rio Bosque Park east of El Paso, TX to image river sediments deposited by the Rio Grande River. By using everyday noises as the source, site-specific analysis can be performed in urban areas without worrying about noise interference or disturbing the public with explosions or other loud active sources. I compared results from the passive array to active seismic refraction data and data collected from a water well, including downhole seismic surveys and natural gamma, magnetic susceptibility, resistivity, and caliper logs. Results from all surveys show three distinct velocity layers: 150 m/s for 0-10 m depth, 200 m/s for 10-20 m depth, and 400 m/s for 20-50 m depth. The consistent results between the passive array and the ground truth model validate my approach of using passive noise to analyze the subsurface for earthquake hazard mapping. ^
Folger, Derek Scott, "Determining subsurface structure from microtremors using passive arrays: An alternative to active seismic surveys" (2006). ETD Collection for University of Texas, El Paso. AAI1434289.