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Synthetic seismic models from outcrop-derived reservoir-scale three-dimensional facies models: The Eocene Ainsa turbidite system (southern Pyrenees)

AuthorsFalivene, O.; Arbués, P.; Ledo, Juanjo; Benjumea, Beatriz; Muñoz, Josep A.; Fernández, O.; Martínez-Loriente, S. CSIC ORCID
Issue DateMar-2010
PublisherAmerican Association of Petroleum Geologists
CitationAAPG Bulletin 94(3): 317-343 (2010)
AbstractThis study uses one-dimensional convolution seismic models to better understand which features of slope turbidite systems can (or cannot) be observed on real seismic data, aiming to improve subsurface seismic interpretation. Synthetic seismic sections and cubes were built from reservoir-scale three-dimensional facies models of the outcropping Ainsa turbidite system. This turbidite system developed in a foredeep and wedge-top depositional setting within a slope system. The turbidite system consists of laterally and vertically stacked sandstone- and debrite-dominated channel fills, grading into heterolithic and mudstone units, with intercalations of slump-deformed mudstone-rich units. Typical petrophysical values for subsurface Cenozoic sediments were assumed for the seismic models, which are presented at 25-, 50-, and 75-Hz resolution. Seismic models enabled the comparison between architectural and facies distributions observed in the outcrops and the geological models to their possible seismic expression in the subsurface. Comparisons show how seismic expression degrades when seismic resolution decreases. By using models at different geological scales, the effects of each heterogeneity scale are identified. Precise delineation of the internal architecture and facies distribution within channel complexes is beyond the reach of all seismic frequencies. The position of channel complex tops and margins is uncertain because of their gradual character. Differentiating between sandstone- and debrite-filled channels is not straightforward, and bed-scale heterogeneities within the sandstone-dominated channels are barely distinguishable in the seismic data. The net-to-gross predictive capability of root-mean-square amplitude extractions varies depending on the seismic frequency and unit thickness
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Identifiersissn: 0149-1423
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