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Influence of subtle paleo-tectonics on facies and reservoir distribution in epeiric carbonates: Integrating stratigraphic analysis and modelling (U. Muschelkalk, SW Germany)

Warnecke, M., Aigner, T.
Sedimentary geology 2019 v.383 pp. 82-100
Triassic period, basins, carbonates, dolomite, gamma radiation, models, prediction, retrogradation, Germany, Middle East
The Middle Triassic Upper Muschelkalk carbonate ramp deposits in SW-Germany provide an excellent ‘laboratory scale’ analogue for vast epeiric basin fills such as in the Middle East. The Upper Muschelkalk and the entire Mesozoic overburden in SW-Germany were deposited on a complex mosaic of three major, differentially subsiding Variscan paleo-tectonic blocks: the Rhenohercynian, Saxothuringian and Moldanubian - subtly influencing the depositional facies pattern for long periods of time. This study is based on detailed sedimentological logs of 41 boreholes and surface outcrop sections and 39 gamma-ray logs, lithofacies analysis, and a 1-D and 2-D sequence stratigraphic analysis leading to a regional correlation integrating sequence architecture and marker beds. Using the subsurface 3D modelling tool Petrel, two nested geocellular reservoir models were generated: (i) a basin scale (201.5 × 325 km) Lithofacies Associations (LFA) model based on truncated Gaussian simulation (TGS); (ii) a field scale (50 × 50 km) Lithofacies Types (LFT) model based on sequential indicator simulation (SIS). The integrated 3D facies models reveal landward facies retrogradation with patchy isolated shoal bodies during the transgressive hemisequence and basinward facies progradation with well-connected large shoals within the regressive hemisequence. Models combined with structural maps show the influence of large Variscan block segments and smaller scale internal structural elements on the distribution, and the size of reservoir analogues, both shoal- and dolomite bodies. This relationship offers a new tool for exploration in epeiric carbonates using deep-seated paleo-tectonic patterns for the prediction of both hydrocarbon and geothermal reservoirs.