Passive Surface Wave Imaging With Non-uniform Noise Sources: Methods And Applications

Passive surface wave methods can recover surface waves from ambient noises and use the dispersion characteristics of surface waves to image the subsurface shear-wave velocity structure,so as to realize the fine characterization of the near-surface medium.The random and uniform distribution of noise sources is the premise of obtaining reliable imaging results,complex human activities,however,often generate nonuniform ambient noise fields,which affect the accuracy of passive surface wave imaging.When the distribution of noise sources is unknown,in order to take into account both the efficiency of the array deployment and the accuracy of surface wave imaging,I propose to use a pseudo-linear array to perform surface wave imaging with non-uniform noise sources.When the noise sources are inline distributed,I suggest using a linear array for surface wave imaging and propose the multichannel-coherencyweighted stack method to suppress the interference of the noise sources inside the array and improve the imaging quality.When the energy of offline noise sources is strong,I propose to use the short-wavelength surface wave velocity as the scanning velocity window of the multichannel-coherency-weighted stack method to enhance the inline noise sources and improve the imaging accuracy.Aiming at the problem of passive surface wave imaging with non-uniform noise sources,the following aspects are mainly studied.When the distribution of noise sources is unknown,I point out the limitations of a linear array in characterizing non-uniform ambient noise fields that may cause the problem of overestimation of velocity.I suggest to add at least two sensors beside the linear array to form a pseudo-linear array.I propose the pseudo-linear-array analysis of passive surface waves method which combines the beamforming analysis method and the dispersion energy stacking method,and the accuracy of surface-wave imaging is improved.For the roadside linear array commonly used in the urban environment,I propose the multichannel-coherency-weighted stack method to make full use of the trafficinduced waves propagating along the road.The field data show that even with ultrashort ambient noise data,the proposed method can effectively suppress the interference of internal noise sources of the array and improve the quality of the retrieved surface waves.When the direction of the main noise source is known,I suggest deploying a linear array along the direction of the main noise source.It may still be interfered with by noise sources from other directions.Based on the stationary phase analysis,however,the short-wavelength surface wave is less affected by the non-uniformly distributed noise sources.Therefore,I propose to use the accurate short-wavelength surface wave velocity as the scanning velocity window of the multichannel-coherency-weighted stack method.The velocity of the stationary-phase-zone source is close to the true velocity and is within the velocity window,while the velocity of the non-stationaryphase-zone source is out of the velocity window.Therefore,only the sources in the stationary phase zone are emphasized after stacking.The real-world data demonstrate that this method can effectively enhance the surface waves propagating along the linear array,suppress the potential interference of noise sources from other azimuths,and significantly improve the accuracy of the surface-wave dispersion measurement.With the ultra-short recordings from a dense nodal array,I use beamforming analysis to obtain the distribution of noise sources,which changes over time.I recommend using the nighttime data,whose noise source distribution is relatively uniform,as a reference and choose to stack similar data to obtain more accurate surface waves.Then,a high-resolution three-dimensional shear wave velocity model with a depth of 80 meters below the parking lot in a karst area of Hangzhou was obtained by using the ambient noise surface-wave tomography method,and it corresponds well with the drilling results.The effectiveness of the method for processing surface wave data from non-uniformly distributed noise sources is therefore verified.