3D fold and fault reconstruction with an uncertainty model: An example from an Alpine tunnel case study
Section snippets
Introduction and motivation
3D geological models that are based on field data aim at predicting geological conditions at depth, but are strongly affected by different sources of uncertainty. These sources include the overall structural and stratigraphic complexity of the site, the required depth of the prediction, topography, regional attitude of geological structures and the continuity of bedrock outcrops.
Traditionally, sub-surface models are based on a network of cross-sections, sometimes constructed using sound
Regional framework
The Alps originated by subduction and closure of the Mesozoic Tethyan ocean (Cretaceous–Eocene) and subsequent collision between the European passive continental margin and the Adriatic (African) active plate margin (Dal Piaz et al., 2003, and refs. therein). This geodynamic evolution generated a collisional wedge that in the Eastern Alps (Fig. 1) consists, from top to bottom, of (1) the Adria-derived Austroalpine continental basement and cover nappe system; (2) the Penninic system exposed in
3D geological modeling
Geological modeling for the sector between Fortezza (N of Bressanone) and the Italy–Austria political boundary was carried out taking into account structural data and detailed geological maps organized in a geological database (GeoDB) implemented in ArcGIS®. Structural stations were located and georeferenced in 2D with the help of a GPS, whilst elevations were determined by means of projection onto a high-resolution digital elevation model (DEM). The polygon and polyline features of the
Evaluation of geological uncertainty
When dealing with the estimation of uncertainties associated with the projection to depth of geological structures observed at surface, there is an obvious difference between interpolation of surfaces within the domain where data points are present, and extrapolation outside of this domain. In interpolation, the shape of the surface is strongly constrained by the data themselves and uncertainty can be defined on a rigorous statistical basis (geostatistics). In contrast, when it is necessary to
Discussion
The 3D geological modeling of a wide sector of the eastern Alps carried out using two different methodologies (pseudo-3D modeling in ArcGIS® environment and a true 3D model with gOcad®) has highlighted the fundamental difference between “data-driven” interpolation and “knowledge-based” extrapolation, a difference that needs to be considered in uncertainty estimates. In the case of interpolation, the shape of the interpolated surface is strongly constrained by the data themselves and uncertainty
Acknowledgments and notes on the project
Field data used in this project were collected during two mapping campaigns, in 2000 and 2004, funded by an EU research grant and by BBT SE, the Italian–Austrian railway company in charge of the Brenner Basistunnel project, whose kind help is acknowledged. A first draft of the geological model described here was developed by the CFR (Consorzio Ferrara Ricerche) working group and delivered to BBT SE as a result of this project. This model was developed in 2D, using a network of interconnected
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