Time-varying Wavelet Estimation by Hybrid Method
W. Feng, T. Hu, Y. Zhang and F.C. Yao
Event name: 77th EAGE Conference and Exhibition 2015
Session: Transforms in Seismic Signal Processing
Publication date: 01 June 2015
Info: Extended abstract, PDF ( 1.32Mb )
Price: € 20
Seismic wavelet estimation is an important part of seismic data processing and interpretation, whose preciseness is directly related to the results of deconvolution and inversion. The methods for seismic wavelet estimation can be classified into two basic types: deterministic and statistical. By combining the two types of methods, spectral coherence method (Walden & White, 1998) of deterministic method and skewness attribute method (Fomel & Van der Baan, 2014) of statistical method, the amplitude and phase of the time-varying wavelet are estimated separately. The skewness attribute is used to estimate time-varying phase of propagating wavelet instead of locally observed wavelet. Phase-only corrections can then be applied by means of a time-varying phase rotation. Alternatively, amplitude and phase deconvolution can be achieved to enhance the resolution. We illustrate the method on both synthetic and real data examples.