Array optimisation for multichannel electrical resistivity tomography instruments

In recent years there has been considerable research into the selection of near-optimal arrays of electrode configurations that enhance the resolution of electrical resistivity tomography (ERT) images. Several algorithms have been developed that select resistivity measurements based on their contribution to the cumulative sensitivity of the array (Furman et al., 2004; Hennig and Weller, 2005) or its model resolution matrix (Stummer et al. , 2004; Wilkinson et al., 2006a; 2006b). Homogeneous subsurface resistivity distributions were assumed for these studies, although better results can be obtained using the same algorithms if the resistivity distribution is known a priori (Anthansiou, 2006). When compared to standard arrays, such as dipole-dipole or Wenner- Schlumberger, optimised arrays can substantially improve the resolution of the ERT image for the same number of measurements (Wilkinson et al., 2006b). The driver for researching array optimisation techniques has been the development of computer controlled ERT systems that can address arbitrary combinations of current and potential electrodes. Unfortunately all the published optimisation algorithms share a problem that is likely to impede their wider use: the arrays that they produce are inherently ‘single channel’ (SC). Since they do not take advantage of the multichannel (MC) capability of modern ERT instruments, the optimised arrays that they produce are rather inefficient to use compared to many standard arrays that are well suited to MC operation. However, we have developed a simple extension that constrains our previous algorithm to choose near-optimal configurations that also fit well into a MC measurement scheme. This extension could easily be adapted to work with the other optimisation schemes cited above

The detection and tracking of mine-water pollution from abandoned mines using electrical tomography

Increasing emphasis is being placed on the environmental and societal impact of mining, particularly in the EU, where the environmental impacts of abandoned mine sites (spoil heaps and tailings) are now subject to the legally binding Water Framework and Mine Waste Directives. Traditional sampling to monitor the impact of mining on surface waters and groundwater is laborious, expensive and often unrepresentative. In particular, sparse and infrequent borehole sampling may fail to capture the dynamic behaviour associated with important events such as flash flooding, mine-water break-out, and subsurface acid mine drainage. Current monitoring practice is therefore failing to provide the information needed to assess the socio-economic and environmental impact of mining on vulnerable eco-systems, or to give adequate early warning to allow preventative maintenance or containment. BGS has developed a tomographic imaging system known as ALERT ( Automated time-Lapse Electrical Resistivity Tomography) which allows the near real-time measurement of geoelectric properties "on demand", thereby giving early warning of potential threats to vulnerable water systems. Permanent in-situ geoelectric measurements are used to provide surrogate indicators of hydrochemical and hydrogeological properties. The ALERT survey concept uses electrode arrays, permanently buried in shallow trenches at the surface but these arrays could equally be deployed in mine entries or shafts or underground workings. This sensor network is then interrogated from the office by wireless telemetry (e.g: GSM, low-power radio, internet, and satellite) to provide volumetric images of the subsurface at regular intervals. Once installed, no manual intervention is required; data is transmitted automatically according to a pre-programmed schedule and for specific survey parameters, both of which may be varied remotely as conditions change (i.e: an adaptive sampling approach). The entire process from data capture to visualisation on the web-portal is seamless, with no manual intervention. Examples are given where ALERT has been installed and used to remotely monitor (i) seawater intrusion in a coastal aquifer (ii) domestic landfills and contaminated land and (iii) vulnerable earth embankments. The full potential of the ALERT concept for monitoring mine-waste has yet to be demonstrated. However we have used manual electrical tomography surveys to characterise mine-waste pollution at an abandoned metalliferous mine in the Central Wales orefield in the UK. Hydrogeochemical sampling confirms that electrical tomography can provide a reliable surrogate for the mapping and long-term monitoring of mine-water pollution

Non-invasive characterisation of road subgrade with towed-array capacitive resistivity imaging

A towed-array Capacitive Resistivity Imaging (CRI) system has been used in a controlled experiment to acquire multi-channel high-resolution ERT data on an asphalt road. Results from a CRI survey on a purpose-built trial road are discussed and compared to corresponding GPR profile data. It is demonstrated that CRI is particularly effective for the assessment of road subgrade condition. The technique is found to be sensitive to variations in moisture content and porosity in the subgrade layer, which can be used to distinguish areas of structural weakness in roadbeds. We conclude that CRI can be a valuable tool in pavement engineering as it provides complementary information to existing non-destructive testing techniques

The robustness and general applicability of Optimal Resistivity Surveys designed by maximising model resolution

Most optimal survey design algorithms for resistivity imaging have not incorporated prior knowledge of the resistivity of the subsurface. The resulting surveys are optimal for a homogeneous earth, but little investigation has yet been carried out to test whether they are robust, i.e. that they remain optimal when applied to imaging heterogeneous subsurface resistivity distributions. This paper compares a generic survey, which is designed to maximise the estimated model resolution evenly across a homogeneous earth, with specific surveys similarly designed for a number of heterogeneous resistivity distributions. In terms of both the average estimated model resolution and the correlations between the inverted and true resistivity models, the generic and heterogeneous survey designs give near-identical results. This suggests that surveys designed using homogeneous earth approximations are robust in the presence of resistivity heterogeneities and are therefore generally applicable. Traditional dipole-dipole surveys with the same number of measurements do not give such good inverted images, and their degree of optimality (measured either by average resolution or image correlation) is less robust in the presence of heterogeneity

Characterising sand and gravel deposits using electrical resistivity tomography (ERT) : case histories from England and Wales

Electrical Resistivity Tomography (ERT) is a rapidly developing geophysical imaging technique that is now widely used to visualise subsurface geological structure, groundwater and lithological variations. It is being increasingly used in environmental and engineering site investigations, but despite its suitability and potential benefits, ERT has yet to be routinely applied by the minerals industry to sand and gravel deposit assessment and quarry planning. The principal advantages of ERT for this application are that it is a cost-effective non-invasive method, which can provide 2D or 3D spatial models of the subsurface throughout the full region of interest. This complements intrusive sampling methods, which typically provide information only at discrete locations. Provided that suitable resistivity contrasts are present, ERT has the potential to reveal mineral and overburden thickness and quality variations within the body of the deposit. Here we present a number of case studies from the UK illustrating the use of 2D and 3D ERT for sand and gravel deposit investigation in a variety of geological settings. We use these case studies to evaluate the performance of ERT, and to illustrate good practice in the application of ERT to deposit investigation. We propose an integrated approach to site investigation and quarry planning incorporating both conventional intrusive methods and ERT

Detection of abandoned mineshafts using towed-array capacitive resistivity and real-time kinematic GPS navigation

The UK has a long history of mining but it was not until 1875 that the accurate mapping of mine workings and the submission of abandonment plans became a legal requirement. Where mineshafts are indicated on plans, they may be mislocated due to poor or inaccurate surveying. Consequently, the redevelopment of derelict land in the built environment frequently encounters potential geohazards, such as old adits, bell pits and shafts. These mining relics pose a serious risk to health and safety. This paper demonstrates how the combination of modem geophysical survey techniques with state-of-the-art satellite-based positioning may assist in the detection of such features. Recent advances in these fields offer the possibility of using towed-array resistivity instruments in conjunction with highly accurate (sub-decimetre) real-time kinematic global positioning systems (RTKGPS). Here we describe the use of multi-offset towed-array capacitive resistivity (CR) with GPS navigation for mapping resistivity over a known mineshaft in the historic mining area of Bonsall Leys in Derbyshire, UK

Tracking tracer motion in a 4-D electrical resistivity tomography experiment

A new framework for automatically tracking subsurface tracers in electrical resistivity tomography (ERT) monitoring images is presented. Using computer vision and Bayesian inference techniques, in the form of a Kalman filter, the trajectory of a subsurface tracer is monitored by predicting and updating a state model representing its movements. Observations for the Kalman filter are gathered using the maximally stable volumes algorithm, which is used to dynamically threshold local regions of an ERT image sequence to detect the tracer at each time step. The application of the framework to the results of 2-D and 3-D tracer monitoring experiments show that the proposed method is effective for detecting and tracking tracer plumes in ERT images in the presence of noise, without intermediate manual intervention

Scope to predict soil properties at within-field scale from small samples using proximally sensed γ-ray spectrometer and EM induction data

Spatial predictions of soil properties are needed for various purposes. However, the costs associated with soil sampling and laboratory analysis are substantial. One way to improve efficiencies is to combine measurement of soil properties with collection of cheaper-to-measure ancillary data. There are two possible approaches. The first is the formation of classes from ancillary data. A second is the use of a simple predictive linear model of the target soil property on the ancillary variables. Here, results are presented and compared where proximally sensed gamma-ray (γ-ray) spectrometry and electromagnetic induction (EMI) data are used to predict the variation in topsoil properties (e.g. clay content and pH). In the first instance, the proximal data is numerically clustered using a fuzzy k-means (FKM) clustering algorithm, to identify contiguous classes. The resultant digital soil maps (i.e. k = 2–10 classes) are consistent with a soil series map generated using traditional soil profile description, classification and mapping methods at a highly variable site near the township of Shelford, Nottinghamshire UK. In terms of prediction, the calculated expected value of mean squared prediction error (i.e. σ2p,C) indicated that values of k = 7 and 8 were ideal for predicting clay and pH. Secondly, a linear mixed model (LMM) is fitted in which the proximal data are fixed effects but the residuals are treated as a combination of a spatially correlated random effect and an independent and identically distributed error. In terms of prediction, the expected value of the mean squared prediction error from a regression (σ2p,R) suggested that the regression models were able to predict clay content, better than FKM clustering. The reverse was true with respect to pH, however. We conclude that both methods have merit. In the case of the clustering the approach is able to account for soil properties which have non-linearity's with the ancillary data (i.e. pH), whereas the LMM approach is best when there is a strong linear relationship (i.e. clay)

UK Geoenergy Observatories: new facilities to understand the future energy challenges

Decarbonisation of energy supplies will require development of new technologies to store energy, heat and waste gases and to act as alternatives to batteries are required for storing renewable energy to make it available during periods of peak demand. The subsurface has the potential to deliver these new technologies through Carbon Capture and Storage (CCS), aquifer storage of heat and compressed air, and extracting geothermal energy. The heterogeneity of the subsurface and lack of detailed knowledge of its static and dynamic properties makes modelling of the efficacy of such proposed technologies difficult. Geoscientists require new experimental facilities where subsurface properties can be studied at unprecedented detail to underpin realistic simulations. The British Geological Survey, on behalf of the Natural Environment Research Council, is developing two new experimental facilities. The planned UK Geoenergy Observatory at Ince Marshes in Cheshire will allow a wide variety of datasets to be gathered on rocks, fluids and fluid transport, bespoke experiments to be undertaken and the properties of a volume of the rock to be understood. It will consist of four different arrays of newly-drilled and extensively-cored boreholes which will characterize the subsurface in greater detail than has previously been possible