Method And Application Of Passive Surface-wave Analysis With Strong Localized Sources

After more than 40 years of rapid development,China’s urbanization level has steadily increased,and the urbanization construction in China has made great achievements.China’s urbanization process has now entered the "second half" : from mindless growth to the development quality improvement as the heart of the new urbanization phase.This presents a problem for the development and use of urban subsurface space.Currently,the depth of urban underground development has exceeded fifty meters and is continuing to extend deep,and the requirements for the precision of underground media detection are becoming increasingly high.Cities are full of electromagnetic and cultural noise,making it difficult to obtain high quality data by conventional geophysical methods.There is an urgent need for an effective and accurate method of imaging the subsurface medium to portray the urban underground structure.Passive surface wave methods,however,use noise records to retrieve surface wave information for investigating urban underground structures.The methods have been receiving increasingly more attention in the community of urban geophysicists.The passive surface wave methods rely on the assumption of a dense,homogeneous,and randomly distributed noise sources.Noise sources in cities,however,are plentiful but often limited in space,while local noise sources will seriously affect the quality of surface-wave dispersion energy.Localized noise sources far away from an array can cause high apparent velocities,and localized noise sources near an array will distort and fragment dispersion energy,also cause high apparent velocities.To eliminate the adverse effects of localized noise sources,I proposed a new passive surface wave analysis method in the presence of strong localized noise sources(localsource passive surface wave analysis,LSPSW).The LSPSW uses matched field processing(MFP)to locate sources and then produce the dispersion energy of surface waves.I used the array response function to prove the ability of MFP to localize noise sources,and also introduced the processing procedure of the LSPSW to extract dispersion curves.I then compared the LSPSW with several existing passive surface wave methods(i.e.,spatial autocorrelation,seismic interferometry,pseudo-linear array analysis of passive surface waves based on beamforming)in both synthetic and realworld cases.The results show the significant advantages of the LSPSW for dispersion energy extraction from ambient noise in the presence of localized noise sources.On the basis of the above theoretical simulation and experimental tests,I used the ambient noise data from Qianjiang area in Hangzhou as an example,extracted the dispersion curves using the LSPSW,which were inverted using the damped least squares method.An S-wave velocity model for the subsurface medium at a shallow depth of 100 m in the measurement area was obtained,which is coincided well with the logging data.The example shows that the LSPSW is efficient and accurate to use shorttime traffic noise record to detect the structure of underground medium.The example also provides valuable experience in the development of passive surface wave methods in urban areas,and can be used as a case study for the subsequent development of subsurface space investigation in densely populated and noise-rich areas.