Search

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]

Previous studies show that optimized arrays generated using the ‘Compare R’ method have significantly better resolution than conventional arrays. This method determines the optimum set of arrays by selecting those that give the maximum model resolution. The number of possible arrays (the comprehensive data set) increases with the fourth power of the number of electrodes. The optimization method faces practical limitations for 2-D survey lines with more than 60 electrodes where the number of possible arrays exceeds a million. Several techniques are proposed to reduce the calculation time for such survey lines. A single-precision version of the ‘Compare R’ algorithm using a new ranking function reduces the calculation time by two to eight times while providing results similar to the double-precision version. Recent improvements in computer GPU technology can reduce the calculation time by about seven times. The calculation time is reduced by half by using the fact that arrays that are symmetrical about the center of the line produce identical changes in the model resolution values. It is further reduced by more than thirty times by calculating the Sherman–Morrison update for all the possible two-electrode combinations, which are then used to calculate the model resolution values for the four-electrode arrays. The calculation time is reduced by more then ten times by using a subset of the comprehensive data set consisting of only symmetrical arrays. Tests with a synthetic model and field data set show that optimized arrays derived from this subset produce inversion models with differences of less than 10% from those derived using the full comprehensive data set. The optimized data sets produced models that are more accurate than the Wenner–Schlumberger array data sets in all the tests. [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]

Abstract: There have been major improvements in instrumentation, field survey design and data inversion techniques for the geoelectrical method over the past 25years. Multi-electrode and multi-channel systems have made it possible to conduct large 2-D, 3-D and even 4-D surveys efficiently to resolve complex geological structures that were not possible with traditional 1-D surveys. Continued developments in computer technology, as well as fast data inversion techniques and software, have made it possible to carry out the interpretation on commonly available microcomputers. Multi-dimensional geoelectrical surveys are now widely used in environmental, engineering, hydrological and mining applications. 3-D surveys play an increasingly important role in very complex areas where 2-D models suffer from artifacts due to off-line structures. Large areas on land and water can be surveyed rapidly with computerized dynamic towed resistivity acquisition systems. The use of existing metallic wells as long electrodes has improved the detection of targets in areas where they are masked by subsurface infrastructure. A number of PC controlled monitoring systems are also available to measure and detect temporal changes in the subsurface. There have been significant advancements in techniques to automatically generate optimized electrodes array configurations that have better resolution and depth of investigation than traditional arrays. Other areas of active development include the translation of electrical values into geological parameters such as clay and moisture content, new types of sensors, estimation of fluid or ground movement from time-lapse images and joint inversion techniques. In this paper, we investigate the recent developments in geoelectrical imaging and provide a brief look into the future of where the science may be heading. [Copyright &y& Elsevier]

Electrical resistivity tomography (ERT) surveys are widely used in geological, environmental and engineering studies. However, the effectiveness of surface ERT surveys is limited by decreasing resolution with depth and near the ends of the survey line. Increasing the array length will increase depth of investigation, but may not be possible at urban sites where access is limited. One novel method of addressing these limitations while maintaining lateral coverage is to install an array of deep electrodes. Referred to here as the Multi-Electrode Resistivity Implant Technique (MERIT), self-driving pointed electrodes are implanted at depth below each surface electrode in an array, using direct-push technology. Optimal sequences of readings have been identified with the “Compare R” method of Wilkinson. Numerical, laboratory, and field case studies are applied to examine the effectiveness of the MERIT method, particularly for use in covered karst terrain. In the field case studies, resistivity images are compared against subsurface structure defined from borings, GPR surveys, and knowledge of prior land use. In karst terrain where limestone has a clay overburden, traditional surface resistivity methods suffer from lack of current penetration through the shallow clay layer. In these settings, the MERIT method is found to improve resolution of features between the surface and buried array, as well as increasing depth of penetration and enhancing imaging capabilities at the array ends. The method functions similar to a cross-borehole array between horizontal boreholes, and suffers from limitations common to borehole arrays. Inversion artifacts are common at depths close to the buried array, and because some readings involve high geometric factors, inversions are more susceptible to noise than traditional surface arrays. Results are improved by using errors from reciprocal measurements to weight the data during the inversion. [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 application of 3D electrical resistivity tomography (ERT) to the characterisation and reserve estimation of an economic fluvial sand and gravel deposit. Due to the smoothness constraints used to regularise the inversion, it can be difficult to accurately determine the geometry of sharp interfaces. We have therefore considered two approaches to interface detection that we have applied to the 3D ERT results in an attempt to provide an accurate and objective assessment of the bedrock surface elevation. The first is a gradient-based approach, in which the steepest gradient of the vertical resistivity profile is assumed to correspond to the elevation of the mineral/bedrock interface. The second method uses an intrusive sample point to identify the interface resistivity at a location within the model, from which an iso-resistivity surface is identified that is assumed to define the interface. Validation of these methods has been achieved through direct comparison with observed bedrock surface elevations that were measured using real-time-kinematic GPS subsequent to the 3D ERT survey when quarrying exposed the bedrock surface. The gradient-based edge detector severely underestimated the depth to bedrock in this case, whereas the interface resistivity method produced bedrock surface elevations that were in close agreement with the GPS-derived surface. The failure of the gradient-based method is attributed to insufficient model sensitivity in the region of the bedrock surface, whereas the success of the interface resistivity method is a consequence of the homogeneity of the mineral and bedrock, resulting in a consistent interface resistivity. These results highlight the need for some intrusive data for model validation and for edge detection approaches to be chosen on the basis of local geological conditions. [Copyright &y& Elsevier]

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]