1887

Abstract

Summary

One of the main limiting factors to the accuracy of large scale groundwater models is the scarcity of hydraulic data. High-resolution Airborne Electromagnetic Methods (AEM) are capable of mapping the electrical resistivity structure of the subsurface in great detail and covering large areas in short time and on a limited budget. As such, there is great potential in integrating AEM data in groundwater modeling as a supplementing source of an extensive amount of information. We have developed several novel techniques that in combination allows for bringing groundwater and AEM models much closer together, i.e.: (1) a novel, scalable inversion engine that allows the AEM inversion to handle arbitrarily large areas at a time; (2) the spatially-decoupled inversion approach, which decouples the inversion model from the acquisition points and can operate on the same grid/voxel cells as the groundwater model; (3) a custom regularization scheme that allows for producing geophysical models with sharp vertical/horizontal resistivity transitions. In this study we present the very first application of the sharp spatially-decoupled inversion on an AEM survey flown for improving the groundwater model in the Kasted area, in the north of Aarhus (Denmark).

Loading

Article metrics loading...

/content/papers/10.3997/2214-4609.201413884
2015-09-06
2019-12-11
Loading full text...

Full text loading...

References

  1. Auken, E., Christiansen, A.V., Kirkegaard, C., Fiandaca, G., Schamper, C., Behroozmand, A.A., Binley, A., Nielsen, E., Effersø, F., Christensen, N.B., Sørensen, K.I., Foged, N. and Vignoli, G.
    [2014] An overview of a highly versatile forward and stable inverse algorithm for airborne, ground-based and borehole electromagnetic and electric data. Explor. Geophys, 1–13.
    [Google Scholar]
  2. Farquharson, C.G. and Oldenburg, D.W.
    [1998] Non-linear inversion using general measures of data misfit and model structure. Geophysical Journal International, 134, 213–227.
    [Google Scholar]
  3. Fiandaca, G., Auken, E., Christiansen, A.V. and Kirkegaard, C.
    [2013] Voxel Inversion of Airborne EM Data. EAGE - Near Surface Geoscience 2013, Bochum, Germany.
    [Google Scholar]
  4. FiandacaG., KirkegaardC., ChristiansenA.V. and AukenE.
    [2015] Presenting a Spatially Decoupled Inversion scheme with applications in large scale airborne electromagnetics. in preparation.
    [Google Scholar]
  5. Kirkegaard, C. and Auken, E.
    [2014] A parallel, scalable and memory efficient inversion code for very large scale airborne EM surveys. Geophysical Prospecting, 63, 495–507.
    [Google Scholar]
  6. Menke, W.
    [1989] Geophysical data analysis: discrete inverse theory. Academic Press, San Diego.
    [Google Scholar]
  7. Vignoli, G., Fiandaca, G., Christiansen, A.V., Kirkegaard, C. and Auken, E.
    [2015] Sharp spatially constrained inversion with applications to transient electromagnetic data. Geophysical Prospecting, 63, 243–255.
    [Google Scholar]
http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609.201413884
Loading
/content/papers/10.3997/2214-4609.201413884
Loading

Data & Media loading...

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error