Research And Application Of Ultra-short Ambient Noise Processing Methods In Urban Areas

With the acceleration of urbanization,urban underground space exploration is playing an increasingly important role.Compared with the traditional active surface-wave exploration,passive surface-wave methods,which use ambient noise to characterize the underground space,can obtain deeper detection depth with lower costs.Passive surface-wave methods have been widely applied in densely populated urban areas in recent years.However,passive surface-wave methods also face many challenges in practical applications.For example,sometimes seismic instruments are not allowed to be deployed for a long time in urban areas.The uneven distribution of noise sources during the short acquisition time will seriously destroy imaging of surface waves.Besides,making use of the limited amount of noise data to improve the imaging quality as much as possible is expected.As a consequence,high-precision surface-wave imaging from ultra-short noise records is necessary and important.My research focuses ultra-short ambient noise in urban areas,studies the noise data processing methods,and summarizes the efficient and appropriate methods to improve surface-wave imaging.The current situation of passive surface-wave exploration is introduced first.Seismic interferometry has been widely used to reveal the underground spatial structure in urban areas by using anthropogenic noise.One-bit normalization(1B),as the most convenient temporal normalization method of seismic interferometry,is commonly used to attenuate transient signals with large amplitude and non-stationary noise sources near the stations.During the ultra-short roadside noise processing,however,synthetic tests and real-world examples demonstrate the pitfall of applying 1B in imaging.Considering this potential pitfall,I recommend an appropriate processing workflow without applying 1B to passive surface-wave imaging from ultra-short noise.In order to achieve high-precision imaging,I analyze stacking methods besides recombining preprocessing methods.The results show phase-weighted stacking(PWS)can use the limited noise data to obtain the high signal-to-noise cross-correlation functions and dispersion energy.On the basis of the above theoretical simulation and experimental verification,I take Qianjiang in Hangzhou as an example,not applying 1B and using PWS,to describe the top 100 m of the subsurface at the survey area from 10-minute records of ambient noise.The inverted shear-wave velocity model is basically consistent with the velocities obtained from logging data.The results show that using ultra-short records of traffic noise to characterize near-surface structures is accurate and efficient,which has great potential in monitoring variations of underground structure in urban areas.