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Published as Geophysics, 80, A75-A82, (2015)

Velocity analysis using similarity-weighted semblance

Yangkang Chen% latex2html id marker 1944
\setcounter{footnote}{1}\fnsymbol{footnote}, Tingting Liu% latex2html id marker 1945
\setcounter{footnote}{2}\fnsymbol{footnote}and Xiaohong Chen% latex2html id marker 1946
\setcounter{footnote}{2}\fnsymbol{footnote}
% latex2html id marker 1947
\setcounter{footnote}{1}\fnsymbol{footnote}Bureau of Economic Geology
John A. and Katherine G. Jackson School of Geosciences
The University of Texas at Austin
University Station, Box X
Austin, TX 78713-8924
ykchen@utexas.edu

% latex2html id marker 1948
\setcounter{footnote}{2}\fnsymbol{footnote}State Key Laboratory of Petroleum Resources and Prospecting
China University of Petroleum
Fuxue Road 18th
Beijing, China, 102200
liutingjiy@126.com & chenxh@cup.edu.cn


Abstract:

Weighted semblance can be used for improving the performance of the traditional semblance for specific datasets. We propose a novel approach for prestack velocity analysis using weighted semblance. The novelty comes from a different weighting criteria in which the local similarity between each trace and a reference trace is used. On one hand, low similarity corresponds to a noise point or a point indicating incorrect moveout, which should be given a small weight. On the other hand, high similarity corresponds to a point indicating correct moveout, which should be given a high weight. The proposed approach can also be effectively used for analyzing AVO anomalies with increased resolution compared with AB semblance. Both synthetic and field CMP gathers demonstrate higher resolution using the proposed approach. Applications of the proposed method on a prestack dataset further confirms that the stacked data using the similarity-weighted semblance can obtain better energy-focused events, which indicates a more precise velocity picking.




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Next: Introduction Up: Reproducible Documents

2015-06-25