HISTOGRAM MATCHING SEISMIC WAVELET PHASE ESTIMATION
The seismic wavelet phase can be estimated by histogram matching between seismic inverted reflectivity and well log reflectivity. Histogram matching is based on the convolutional model and assumes the wavelet is constant. The method is able to recover the wavelet phase information from seismic data with an error of less than 20 degrees if given high-quality seismic data and accurate wavelet amplitude estimation. This method doesn’t need a super-Gaussian-distribution assumption for the reflection series which is required by kurtosis phase estimation. The model tests show that a large amount of data is needed to stabilize the kurtosis phase estimation method. For 1000-sample traces, kurtosis phase estimation can estimate phase with an error of less than 20 degrees for only 57 of 100 tests. For 2000-sample traces, this number increases to 60 out of 100, and 74 out of 100 for the 4000-sample traces. Compared to the optimum Wiener filter wavelet estimation methods, the histogram matching method is not sensitive to an inaccurate timing relationship between seismic data and reflectivity from well log. A high-quality seismic dataset with high S/N is preferred to ensure an accurate phase estimation output. In addition, reflectivity skewness can be used to help identify polarity of the seismic wavelet.