The Q Value Estimation Based On The Sparse Inversion Spectral Decomposition

The conventional time-frequency analysis method is a very important method in seismic data processing,which can make the interpretation more accurate.This method converts the original seismic signals from time domain to frequency domain and gets time-frequency spectrum.Thus the variation of frequency content with time in the seismic signal can be observed at the same time,and seismic interpretation and follow-up work are carried out by the information of time frequency spectrum.The sparse inversion spectral decomposition(SISD)method is an unconventional time-frequency analysis method.Compared with the conventional one,SISD has higher time frequency resolution.The estimation of the Q-value is always the key point in the seismic exploration field.The Q-value estimation based on SISD is a method that the Q-value is estimated by spectral ratio method in the frequency domain which means the time frequency spectrum gained by SISD.This method can effectively estimate the Q-value.In this paper on the one hand I discuss the influence factors in the process of using SISD,such as wavelet dictionary,regularization parameter,algorithm and so on,and introduce the application of SISD,such as denoising,identification of channel complex and multi-cave,on the other hand I state a new method of Q-value estimation and its successful application in numerical models and physical models.If this method can be applied in real seismic data,it definitely will have an important impact on the field of seismic exploration.