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Aiding Seismic Stratigraphic Interpretation With Spectral Decomposition


Stratigraphers use seismic data in two major ways: defining boundaries associated with sea level and topography between important depositional packages or sequences, and mapping individual components or “architectural elements” of a given depositional system. Using modern and paleo analogues as well as well control, the interpreter uses such boundaries and features to map seismic facies which in turn can be related to lithology. The interpretation of discrete stratigraphic features is limited by both the bandwidth and the signal-to-noise ratio of the seismic data. Unfortunately, well-resolved reflections from the top and base of subtle stratigraphic geologic boundaries occur only for thick features imaged by broad band data. Seismically thin stratigraphic features approaching a quarter wavelength thickness, give rise to composite or “tuned” seismic reflections. Direct estimation of stratigraphic thickness is more difficult, with the definition of many of the features of interest, such as channel systems becoming more muted. Fortunately, the tuning phenomena can also help delineate such unresolved features. Specifically, the composite amplitude of a thin layer is strongest (and usually has the highest signal-to-noise ratio) at the quarter wavelength tuning frequency. Thus, we can “probe” the subsurface with the correct frequency, and better delineate our target. Spectral decomposition is a useful tool that helps in the analysis of subtle stratigraphic plays and fractured reservoirs. It decomposes the seismic data into individual frequency components, within the seismic bandwidth, so that the same subsurface Geology can be seen at different frequencies. While the thick beds or features will be seen more clearly at lower frequencies, thin beds will have their characteristic expressions at higher frequencies. Because of tuning and variation of the signal-to-noise ratio with frequency, alternative spectral components can provide significant insight into the stratigraphic interpretation. We have shown how some channel and subtle fault features are seen clearly on selective spectral displays. Coherence or curvature attributes run on spectral data yields much better definition of the channel or subtle fault features, and so aids seismic stratigraphic interpretation.