none 10.1190/1.1487136 Society of Exploration Geophysicists Society of Exploration Geophysicists 186 4728788 5981 2025121112425214400 10.1190 2025-12-11T17:42:59Z 2002-10-11T15:23:40Z 43 Geophysics 1942-2156 0016-8033 2001 01 01 2001 66 6 Philippe Steeghs ∗ Formerly Rice Consortium for Computational Seismic Interpretation, Department of Electrical and Computer Engineering, Rice University, Houston, Texas 77005–1892; presently TNO Physics and Electronics Laboratory, Post Office Box 96864, 2509 JG, The Hague, Netherlands. E-mail: steeghs@fel.tno.nl. Drijkoningen Guy ‡ Delft University of Technology, Department of Civil Engineering and Geosciences, P.O. Box 5028, 2600 GA, Delft, The Netherlands. E-mail: g.g.drijkoningen@ta.tudelft.nl. Abstract The variation of frequency content of a seismic trace with time carries information about the properties of the subsurface reflectivity sequence. As a result, analysis of the data in terms of the local frequency content can provide a worthwhile addition to the standard procedures that are used in seismostratigraphic interpretation. The theory of quadratic time-frequency representations provides a solid foundation for local frequency analysis of seismic data and seismic attribute extraction. Two applications of the quadratic time-frequency representations are demonstrated: seismic sequence analysis and seismic attribute extraction. The joint time-frequency representation of a seismic reflection pattern is often much more easily interpreted in terms of subsurface stratification than the time-or frequency-domain description alone. We show how the time-frequency representation can be used to delineate seismic sequences on the basis of the time-frequency characteristics of the signal. There exists a close relation between complex-trace attribute analysis and quadratic time-frequency representations. In the time-frequency approach, the seismic attributes are characteristics of the local spectrum. Extraction of the attributes from the time-frequency representation of the seismic trace leads to considerable improvement of the signal-to-noise ratio of the attributes. Furthermore, the classic set of seismic attributes of instantaneous amplitude, phase, and frequency can be easily extended with other parameters describing the local spectrum, such as instantaneous bandwidth, skewness, and kurtosis. 2001 01 01 2001 01 01 2001 1947 1959 10.1190/1.1487136 https://pubs.geoscienceworld.org/geophysics/article/66/6/1947/107219/Seismic-sequence-analysis-and-attribute-extraction https://pubs.geoscienceworld.org/seg/geophysics/article-pdf/66/6/1947/3694159/gsgpy_66_6_1947.pdf https://pubs.geoscienceworld.org/seg/geophysics/article-pdf/66/6/1947/3694159/gsgpy_66_6_1947.pdf http://geophysics.geoscienceworld.org/cgi/doi/10.1190/1.1487136 Signal Processing Baraniuk 32 263 1993 10.1016/0165-1684(93)90001-Q Signal dependent time-frequency analysis using a radially Gaussian kernel IEEE Trans. Signal Processing Baraniuk 41 1589 1993 10.1109/78.212733 A signal-dependent time-frequency representation: Optimal kernel design IEEE Trans. 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