S U M M A R YTwo strategies are presented for obtaining the maximum spatial resolution in electrical resistivity tomography surveys using a limited number of four-electrode measurement configurations. Both methods use a linearized estimate of the model resolution matrix to assess the effects of including a given electrode configuration in the measurement set. The algorithms are described in detail, and their execution times are analysed in terms of the number of cells in the inverse model. One strategy directly compares the model resolution matrices to optimize the spatial resolution. The other uses approximations based on the distribution and linear independence of the Jacobian matrix elements. The first strategy produces results that are nearer to optimal, however the second is several orders of magnitude faster. Significantly however, both offer better optimization performance than a similar, previously published, method. Realistic examples are used to compare the results of each algorithm. Synthetic data are generated for each optimized set of electrodes using simple forward models containing resistive and/or conductive prisms. By inverting the data, it is demonstrated that the linearized model resolution matrix yields a good estimate of the actual resolution obtained in the inverted image. Furthermore, comparison of the inversion results confirms that the spatial distribution of the estimated model resolution is a reliable indicator of tomographic image quality.

Capacitive resistivity (CR) is an emerging geophysical technique designed to extend the scope of the conventional methodology of DC resistivity to environments where galvanic coupling is notoriously difficult to achieve, for example across engineered structures (roads, pavements), hard rock, dry soil or frozen ground. Conceptually, CR is based on a four-point array capacitively coupled to the ground. Under A parametric study of the complex quasi-static transfer impedance reveals the existence of a restricted range of practical parameters that permits successful operation of CR instruments at low induction numbers. Theory predicts that emulation of the DC measurement is compromised if low-induction-number operation is not maintained throughout a survey area, for example in a zone of high conductivity.

S U M M A R YIf electrodes move during geoelectrical resistivity monitoring and their new positions are not incorporated in the inversion, then the resulting tomographic images exhibit artefacts that can obscure genuine time-lapse resistivity changes in the subsurface. The effects of electrode movements on time-lapse resistivity tomography are investigated using a simple analytical model and real data. The correspondence between the model and the data is sufficiently good to be able to predict the effects of electrode movements with reasonable accuracy. For the linear electrode arrays and 2-D inversions under consideration, the data are much more sensitive to longitudinal than transverse or vertical movements. Consequently the model can be used to invert the longitudinal offsets of the electrodes from their known baseline positions using only the time-lapse ratios of the apparent resistivity data. The example data sets are taken from a permanently installed electrode array on an active lobe of a landslide. Using two sets with different levels of noise and subsurface resistivity changes, it is found that the electrode positions can be recovered to an accuracy of 4 per cent of the baseline electrode spacing. This is sufficient to correct the artefacts in the resistivity images, and provides for the possibility of monitoring the movement of the landslide and its internal hydraulic processes simultaneously using electrical resistivity tomography only.

Abstract. We have investigated the potential of 2D electrical imaging for the characterization of seawater intrusion using field data from a site in Almeria, SE Spain. Numerical simulations have been run for several scenarios, with a hydrogeological model reflecting the local site conditions. The simulations showed that only the lower salt concentrations of the seawater-freshwater transition zone could be recovered, due to the loss of resolution with depth. We quantified this capability in terms of the cumulative sensitivity associated with the measurement setup and showed that the mismatch between the targeted and imaged parameter values occurs from a certain sensitivity threshold. Similarly, heterogeneity may only be determined accurately if located in an adequately sensitive area. At the field site, we identified seawater intrusion at the scale of a few kilometres down to a hundred metres. Borehole logs show a remarkable correlation with the image obtained from surface data but indicate that the electrically derived mass fraction of pure seawater could not be recovered due to the discrepancy between the in-situ and laboratory-derived petrophysical relationships.Surface-to-hole inversion results suggest that the laterally varying resolution pattern associated with such a setup dominates the image characteristics compared to the laterally more homogeneous resolution pattern of surface only inversion results, and hence surface-to-hole images are not easily interpretable in terms of larger-scale features. Our results indicate that electrical imaging can be used to constrain seawater intrusion models if image appraisal tools are appropriately used to quantify the spatial variation of sensitivity and resolution. The most crucial limitation is probably the apparent non stationarity of the petrophysical relationship during the imaging process.

. Electrical resistivity tomography applied to geological, hydrogeological and engineering investigations at a former waste disposal site. Geophysics, Vol. 71, B231-B239. ABSTRACTA former dolerite quarry and landfill site was investigated using 2D and 3D electrical resistivity tomography (ERT), with the aims of determining buried quarry geometry, mapping bedrock contamination arising from the landfill, and characterizing site geology. Resistivity data were collected from a network of intersecting survey lines using a Wenner-based array configuration. Inversion of the data was carried out using 2D and 3D regularized least-squares optimization methods with robust (L1-norm) model constraints. For this site, where high resistivity contrasts were present, robust model constraints produced a more accurate recovery of subsurface structures when compared to the use of smooth (L2-norm) constraints. Integrated 3D spatial analysis of the ERT and conventional site investigation data was shown in this case to provide a highly effective means of characterizing the landfill and its environs. The 3D resistivity model was successfully used to confirm the position of the landfill boundaries, which appeared as electrically well-defined features that corresponded extremely closely to both historic maps and intrusive site investigation data. A potential zone of leachate migration from the landfill was identified from the electrical models; the location of this zone was consistent with the predicted direction of groundwater flow across the site. Unquarried areas of a dolerite sill were imaged as a resistive sheet-like feature, whilst the fault zone appeared in the 2D resistivity model as a dipping structure defined by contrasting bedrock resistivities.3