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Underwater ERT surveying in water with resistivity layering with example of application to site investigation for a rock tunnel in central StockholmNormal access

Authors: T. Dahlin and M.H. Loke
Journal name: Near Surface Geophysics
Issue: Vol 16, No 3, June 2018 pp. 230 - 237
DOI: 10.3997/1873-0604.2018007
Special topic: Urban Geophysics: New Developments and Research
Language: English
Info: Article, PDF ( 1.04Mb )
Price: € 30

Summary:
We present an approach to underwater electrical resistivity tomography surveying under conditions with several water layers with different resistivity in the water above the electrode layout. The approach is verified against a synthetic model example and tested in full scale on data from a field survey. The field survey was carried out in central Stockholm as part of pre-investigations for a new metro train (T-bana) tunnel planned to pass under seawater. The water passage is associated with major tectonic zones that can potentially be very difficult from a tunnel construction point of view. The aim was to identify variations in depth of the bottom sediments and variations in rock quality including the possible presence of weak zones in the rock. Survey conditions are complicated by boat traffic and electrical disturbances from the power grid and train traffic. The water depth was mapped using sonar combined with recording pressure transducers, and water resistivity as a function of water depth was recorded using geophysical borehole logging equipment. Water resistivity as a function of depth was integrated in the inversion model. The results show that the rather difficult survey conditions could be handled in a satisfactory way thanks to adequate equipment, careful planning, and attention to details. The measured data contain information that is relevant for creating coherent models of the variation in depth to rock, which corresponds well with data from drilling. The results also indicate that information in variation in rock quality that can be of critical importance for planning of underground construction can be derived from the data.


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