Electric resistivity and seismic refraction tomography, a challenging
joint underwater survey at Äspö Hard Rock Laboratory
Abstract. Tunnelling below water passages is a challenging task in terms of planning, pre-investigation and construction. Fracture zones in the underlying bedrock lead to low rock quality and thus reduced stability. For natural reasons they tend to be more frequent at water passages. Ground investigations that provide information of the subsurface are necessary prior to the construction phase, but can be logistically difficult. Geophysics can help close the gaps between local point information and produce subsurface images. An approach that combines seismic refraction tomography and electrical resistivity tomography has been tested at the Äspö Hard Rock Laboratory (HRL). The aim was to detect fracture zones in a well-known but logistically and, from a measuring perspective, challenging area. The presented surveys cover a water passage along a part of a tunnel that connects surface facilities with an underground test laboratory. The tunnel is approximately 100 m below and 20 m east of the survey line and gives evidence for one major and several minor fracture zones. The geological and general test site conditions, e.g. with strong powerline noise from the nearby nuclear power plant, are challenging for geophysical measurements. Co-located positions for seismic and ERT sensors and source positions are used on the 450 m long underwater section of the 700 m long profile. Because of a large transition zone that appeared in the ERT result and the missing coverage of the seismic data, fracture zones at the southern and northern part of the underwater passage cannot be detected by separated inversion. A simple synthetic study shows significant three dimensional artefacts corrupting the ERT model that have to be taken into account while interpreting the results. A structural coupling cooperative inversion approach is able to image the northern fracture zone successfully. In addition, previously unknown sedimentary deposits with a significant large thickness are detected in the otherwise unusually well documented geological environment. The results significantly improve imaging of some geologic features, which would have been not detected or misinterpreted otherwise, and combines the images by means of cluster analysis to a conceptual subsurface model.