- journal_title：AAPG Bulletin
- Contributor：Menno J. De Ruig ; Stephen M. Hubbard
- Publisher：American Association of Petroleum Geologists (AAPG)
- Date：2006-
- Format：text/html
- Language：en
- Identifier：10.1306/10210505018
- journal_abbrev：AAPG Bulletin
- issn：0149-1423
- volume：90
- issue：5
- firstpage：735
- section：REGULAR ARTICLES
Oligocene–Miocene deep-water deposits of the Puchkirchen and basal Hall formations contain the main gas reservoirs of the Austrian Molasse Basin. A new seismostratigraphic model, based on a 2000-km2 (772-mi2), regional, three-dimensional (3-D) seismic data set, has fundamentally changed our understanding of the depositional processes and reservoir distribution in this classic deep-water foreland basin.
Regional 3-D seismic attribute maps, calibrated by nearly 350 wells, reveal that sedimentation occurred primarily within the confines of a large (3–5 km [1.8–3.1 mi] wide by >100 km [>62 mi] long), low-sinuosity channel belt that occupied the Molasse Basin foredeep. The channel fill consists predominantly of turbiditic conglomerate and sandstone, as well as chaotic slump and debris-flow deposits. Overbank areas are characterized by fine-grained turbiditic sandstone and mudstone. Incised canyons and ponded slope fans were active along the southern basin margin; lateral tributary channels intersected the axial channel belt in the north. Significant accumulations of gas are stratigraphically and structurally trapped in channel thalweg and slope-fan sandstones, with more modest amounts in overbank lobe and tributary-channel deposits.
Basin geometry had a profound effect on the architecture of the channel belt and subsequent sediment distribution. Large-scale deep-water channel systems are poorly documented from foreland basins; the depositional model developed for the Puchkirchen Formation was made possible through the use of high-quality seismic data and an extensive drill-core database. The depositional model may be a useful analog for other elongate, deep-water basins, especially those that lack extensive, modern data sets.