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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Volume 18, issue 11 | Copyright
Hydrol. Earth Syst. Sci., 18, 4349-4362, 2014
https://doi.org/10.5194/hess-18-4349-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 04 Nov 2014

Research article | 04 Nov 2014

Large-scale 3-D modeling by integration of resistivity models and borehole data through inversion

N. Foged1, P. A. Marker2, A. V. Christansen1, P. Bauer-Gottwein2, F. Jørgensen3, A.-S. Høyer3, and E. Auken1 N. Foged et al.
  • 1HydroGeophysics Group, Department of Geoscience, Aarhus University, Denmark
  • 2Department of Environmental Engineering, Technical University of Denmark, Denmark
  • 3Geological Survey of Denmark and Greenland, Groundwater and Quaternary Geology Mapping, Denmark

Abstract. We present an automatic method for parameterization of a 3-D model of the subsurface, integrating lithological information from boreholes with resistivity models through an inverse optimization, with the objective of further detailing of geological models, or as direct input into groundwater models. The parameter of interest is the clay fraction, expressed as the relative length of clay units in a depth interval. The clay fraction is obtained from lithological logs and the clay fraction from the resistivity is obtained by establishing a simple petrophysical relationship, a translator function, between resistivity and the clay fraction. Through inversion we use the lithological data and the resistivity data to determine the optimum spatially distributed translator function. Applying the translator function we get a 3-D clay fraction model, which holds information from the resistivity data set and the borehole data set in one variable. Finally, we use k-means clustering to generate a 3-D model of the subsurface structures. We apply the procedure to the Norsminde survey in Denmark, integrating approximately 700 boreholes and more than 100 000 resistivity models from an airborne survey in the parameterization of the 3-D model covering 156 km2. The final five-cluster 3-D model differentiates between clay materials and different high-resistivity materials from information held in the resistivity model and borehole observations, respectively.

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