Local wavelet attributes (amplitude, phase and scale) for geological characterization

Attributes remain to be of the utmost importance for the characterization of seismic data. Especially in the scale-range where tuning effects play, the understanding of what is happening, and the subsequent technology to extract the proper attributes from the huge seismic data-volumes remains current. This study starts with the analysis of a set of typical petrophysical log shapes. These log shapes have a thickness of 5 to 50 meter, commonly below the seismic resolution, in the region of tuning effects. The synthetic seismic reponses for these logs indicated that the local shape of the wavelet could be indicative. From the vast range of wavelet-transform based tools, the matching pursuit analysis approach using a specific type of Gabor-atoms was selected. This was done because of the attractive Rickerwavelet shape of these atoms, a shape commonly found in seismic data. This method proved to be able to extract the phase attribute (along with other attributes) from real seismic data. Distinct populations in the phase attributes were found that could be related to facies-types in a delta-system. This method is compared with the well-established concept of the analytic trace. The proposed method is extracting information on a larger scale compared to the principal components from the analytic trace, making it less sensitive to noise. This has a draw-back in a lower resolution in the time direction, but due to the choice of a very seismic (Ricker) wavelet, this is not so troublesome.