Fusion of Electrical Resistivity Tomography (ERT) and Resistivity Cone Penetrometry (RCPT) Data for Improved Hydrogeophysical Characterisation
Creators: name: Catt, Lucy
name: West, Jared
name: Clark, Roger
name: Catt, Lucy
Publisher: name: XVI International Conference on Computational Methods in Water Resources
Year: 2006

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.