Published June 18, 2006
| Version v1
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Fusion of Electrical Resistivity Tomography (ERT) and Resistivity Cone Penetrometry (RCPT) Data for Improved Hydrogeophysical Characterisation
Creators
- 1. Earth Sciences, School of Earth and Environment, University of Leeds
Description
Electrical resistance tomography (ERT) is potentailly an appropriate subsurface
imaging tool for hydrogeophysical characterisation, due to strong correlations
between resistivity and hydrological parameters such as clay content and
permeability. However, the ability of ERT to locate accurately sharp boundaries, such
as permeability contrasts and wetting fronts, is rather poor because of the
relatively large measurement support volume of the technique. This poor ability to
locate interfaces also creates problems for ERT applications in geotechnical
engineering, where practitioners need accurate determination of lithological
interface depths. In contrast, the technique of resistivity cone-penetrometry (RCPT)
provides resistivity data with a high vertical resolution, allowing interfaces to be
located accurately. However, RCPT bores are usually widely spaced, so horizontal
resolution is poor. Hence, combination of RCPT and ERT has significant advantages.
Here, we investigate fusion of ERT and RCPT data for hydrogeophysical
characterisation. The ability of RCPT data to guide ERT inversion towards improved
solutions is investigated using both synthetic models and field data.
A series of synthetic RCPT and Wenner ERT data for a sand body
within a clay background was generated. The ERT data were contaminated with 2% and 5%
Gaussian noise. A series of reference models for ERT inversion was generated from the
synthetic RCPT data. The ERT data were inverted with and without these RCPT-derived
reference models. The models produced by inversion (the final models) with the best
fit to the original synthetic model were identified. The final models were then
ranked using a weighted sum of (i) the least-squares misfit of the original synthetic
data to the data produced via forward modelling from the final model, (ii) the least-
squares misfit between the final model and the reference model, and (iii) the final
model smoothness. This ranking technique identified the same best final models as
identified using the best fit to the synthetic model. This result indicates that the
reference model approach described here can safely be used with field data, i.e. for
an unknown 'true' resistivity distribution. Using RCPT data as a constraint
significantly improved interfacial depth accuracy and horizontal boundary location in
the final geoelectrical model.
RCPT and ERT data were collected from a coastal site near Withernsea, East Yorkshire,
UK, where fluvioglacial sand lenses exist within clay tills. The ERT data were
inverted with and without RCPT-derived reference models to produce range of
geoelectrical models. These were quantitatively assessed using the procedures
identified during the modelling stage. The models were then compared to a logged
cliff section. We discuss the implications for the design of combined ERT and RCPT
investigations.
Notes
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Fusion_of_Electrical_Resistivity_Tomography_ERT_and_Resistivity_Cone_Penetrometry_RCPT_Data_for_Improved_Hydrogeophysical_Characterisation.pdf
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