Sensitivity analysis on synthetic 3D Deep ERT data for the example of Plombières, Belgium

Abstract

The E-TEST project (Einstein Telescope EMR Site & Technology) investigates the feasibility of constructing a large Laser Interferometer (Einstein Telescope) in the Euregio Rhine Meuse. The aim of this instrument is to detect gravitational waves. To reach a sufficient noise attenuation the telescope will be built deep underground (more than 200 meters depth). The infrastructure consists of multiple tunnels and caverns spanning several kilometers. As with any large-scale infrastructure, the geological model, especially the existence and orientation of faults, is of large importance for hydrogeophysical and geotechnical characterization. At such depths, few near-surface geophysical methods are able to provide information with enough details. The application of large 3D Deep ERT surveys helps understanding the local geological settings and to identify important geological features but suffers from ambiguous interpretation. However, such imaging requires measuring dipoles independent of the injection system (such as the Fullwaver System by IRIS Instruments) in contrast to conventional ERT Systems, and due to the large covered area, coarsely spaced. This results in a drastic decrease in resolution when compared to classical ERT measurements.Here, we present a sensitivity analysis on a dataset based on the geologic setting in Plombières, Belgium to identify the impact of geology and survey setup on Deep 3D ERT surveys. The utilized geologic model was created with the Open-Source 3D structural geomodelling software GemPy and used as an input for forward modelling using the Open-Source modelling and inversion library pyGIMLi.

Authors 7

1. Yannick Forth

   University of Liège

   Affiliation as printed

   Urban and Environmental Engineering, University of Liège, Liège, Belgium (yannick.forth@uliege.be)

2. Anne-Sophie Mreyen corresponding

   University of Liège

   Affiliation as printed

   Urban and Environmental Engineering, University of Liège, Liège, Belgium (yannick.forth@uliege.be)

3. Andreas Kemna

   University of Bonn

   Affiliation as printed

   Institut für Geowissenschaften und Meteorologie, University of Bonn, Bonn, Germany

4. Joost Hase

   University of Bonn

   Affiliation as printed

   Institut für Geowissenschaften und Meteorologie, University of Bonn, Bonn, Germany

5. Florian Wellmann corresponding Aachen Computational Geoscience and Reservoir Engineering (CGRE)

   RWTH Aachen University

   Affiliation as printed

   Computational Geoscience and Reservoir Engineering, RWTH Aachen, Aachen, Germany

6. Nils Chudalla Aachen Computational Geoscience and Reservoir Engineering (CGRE)

   RWTH Aachen University

   Affiliation as printed

   Computational Geoscience and Reservoir Engineering, RWTH Aachen, Aachen, Germany

7. Frédéric Nguyen corresponding

   University of Liège

   Affiliation as printed

   Urban and Environmental Engineering, University of Liège, Liège, Belgium (yannick.forth@uliege.be)