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New developments in mobile resistivity meter instrumentation have made it possible to survey large areas with dense data coverage. The mobile system usually has a limited number of electrodes attached to a cable that is pulled along behind an operator so that a large area can be covered within a short time. Such surveys can produce three‐dimensional datasets with hundreds of thousands of electrodes positions and data points. Similarly, the inverse model used to interpret the data can have several hundred thousand cells. It is impractical to model such large datasets within a reasonable time on microcomputers used by many small companies employing standard inversion techniques. We describe a model segmentation technique that subdivides the finite‐element mesh used to calculate the apparent resistivity and Jacobian matrix values into a number of smaller meshes. A fast technique that optimizes the calculation of the Jacobian matrix values for multi‐channel systems was also developed. A one‐dimensional wavelet transform method was then used to compress the storage of the Jacobian matrix, in turn reducing the computer time and memory required to solve the least‐squares optimization equation to determine the inverse model resistivity values. The new techniques reduce the calculation time and memory required by more than 80% while producing models that differ by less than 1% from that obtained using the standard inversion technique with a single mesh. We present results using a synthetic model and a field dataset that illustrates the effectiveness of the proposed techniques. [ABSTRACT FROM AUTHOR]

ABSTRACT The use of optimized arrays generated using the 'Compare R' method for cross-borehole resistivity measurements is examined in this paper. We compare the performances of two array optimization algorithms, one that maximizes the model resolution and another that minimizes the point spread value. Although both algorithms give similar results, the model resolution maximization algorithm is several times faster. A study of the point spread function plots for a cross-borehole survey shows that the model resolution within the central zone surrounded by the borehole electrodes is much higher than near the bottom end of the boreholes. Tests with synthetic and experimental data show that the optimized arrays generated by the 'Compare R' method have significantly better resolution than a 'standard' measurement sequence used in previous surveys. The resolution of the optimized arrays is less if arrays with both current (or both potential) electrodes in the same borehole are excluded. However, they are still better than the 'standard' arrays. [ABSTRACT FROM AUTHOR]

The geoelectrical imaging method is a tool for mapping the intrusion boundary between fresh water and saline water due to its inherent capability to delineate the lateral changes in pore-water salinity. A new field survey technique that can be used for environmental and geotechnical investigations has been developed. This study evaluates the multiscale survey technique as a tool employed in electrical imaging to detect the salt-water intrusion boundary in Yan, State of Kedah, northwest Malaysia. The technique was incorporated into these surveys, and it has proved to be a robust method for accurately mapping the fresh-water/saline-water boundary. The resulting resistivity sections from these surveys were consistent with both the available geological and borehole information from the area and the previous resistivity surveys conducted by the Geological Survey of Malaysia at those sites. [ABSTRACT FROM AUTHOR]

The optimized ‘Compare R’ (CR) method is considered one of the best algorithms to automatically generate a set of electrode arrays that maximizes the model resolution for electrical resistivity imaging. In its original version, the calculation time to generate a set of arrays, even for a short resistivity line, required several hours. Recently, researchers spent considerable effort to reduce execution time. In addition, other modifications have been made to improve the practical aspects, such as minimizing the electrode polarization effects and incorporating errors in the data. In line with this approach, the effectiveness of the optimized arrays that are generated based on a modified version of ‘Compare-R' optimization algorithm is demonstrated through a comprehensive and quantitative comparison with the conventional Dipole-Dipole (DD) and Wenner-Schlumberger (WS) arrays. Four different synthetic models were generated and noisy data cases were considered. The results show that the optimized array has significantly better resolution and target detail than conventional arrays. This is clear in enhancing the detectability accuracy in the deepest part of the inversion models. Of the conventional arrays, the DD array provides inversion images mostly closely related to the performance of the optimized array models. [ABSTRACT FROM AUTHOR]

Abstract: We describe the use of a fully volumetric geophysical imaging approach, three-dimensional electrical resistivity (3D ERT), for bedrock detection below mixed sand and gravel deposits typical of fluvial valley-fill terraces. We illustrate the method through an analysis of terrace deposits of the Great Ouse River (UK), where up to 4m of sand and gravel have filled the valley bottom during the latest Pleistocene. We use an edge detector to identify the steepest gradient in first-derivative resistivity profiles, which yields an estimate of bedrock depth (verified by drilling) to a precision better than 0.2m (average) and 0.4m (standard deviation). Comparison of a range of drilling techniques at the site has revealed that borehole derived interface depths suffered from levels of uncertainty similar to those associated with the 3D ERT — indicating that the reliability of bedrock interface depths determined using these two approaches is comparable in this case. The 3D ERT method provides a high spatial resolution that enabled a previously unknown erosional bedrock structure, associated with the change from deeper first terrace to second terrace deposits, to be identified in the Great Ouse valley. The method provides a relatively quick method to quantify terrace fill volume over large sites to a greater degree of precision than currently available. [Copyright &y& Elsevier]