Time-varying wavelet estimation and its applications in deconvolution and seismic inversion

摘要

Wavelet holds an essential role in seismic data processing and characterization, for examples deconvolution and seismic inversion. Unfortunately, wavelet is an unknown data. Several existing methods attempt to estimate and extract the wavelet fromseismic data. However, the methods give only a single wavelet from one seismic trace. When seismic data are non-stationer,single wavelet usage will cause a problem, that is raising the error. This paper proposes a time-varying wavelet estimationmethod to accommodate this problem. It uses matrix diagonalization to estimate a set of wavelets. Next, the time-varyingwavelet is applied to deconvolution and seismic inversion. The experiment shows that time-varying wavelet improves theresults in both deconvolution and seismic inversion. The errors decreased and spectrum bandwidth broadened.