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3D Fault Detection Using Structure Prediction and Nonstationary Similarity
- Publisher: European Association of Geoscientists & Engineers
- Source: Conference Proceedings, 74th EAGE Conference and Exhibition incorporating EUROPEC 2012, Jun 2012, cp-293-00148
- ISBN: 978-90-73834-27-9
Abstract
Automatic detection of geological discontinuities, eg., faults, is a crucial problem in the interpretation of 3D seismic data. We present a new fault detection technique based on the nonstationary similarity attribute. We use local dip pattern to form a structural prediction of seismic traces from neighboring traces. Local similarity between original data and predicted data enhances the coherency-type analysis with identification. In comparison with coherency attribute using slide-window correlation, nonstationary similarity indicates local measurement of fault. Numerical tests using field data in 2D and 3D confirm the effectiveness of the proposed technique for 3D fault detection.