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

Design and application of a multi-modal process tomography system

This paper presents a design and application study of an integrated multi-modal system designed to support a range of common modalities: electrical resistance, electrical capacitance and ultrasonic tomography. Such a system is designed for use with complex processes that exhibit behaviour changes over time and space, and thus demand equally diverse sensing modalities. A multi-modal process tomography system able to exploit multiple sensor modes must permit the integration of their data, probably centred upon a composite process model. The paper presents an overview of this approach followed by an overview of the systems engineering and integrated design constraints. These include a range of hardware oriented challenges: the complexity and specificity of the front end electronics for each modality; the need for front end data pre-processing and packing; the need to integrate the data to facilitate data fusion; and finally the features to enable successful fusion and interpretation. A range of software aspects are also reviewed: the need to support differing front-end sensors for each modality in a generic fashion; the need to communicate with front end data pre-processing and packing systems; the need to integrate the data to allow data fusion; and finally to enable successful interpretation. The review of the system concepts is illustrated with an application to the study of a complex multi-component process

A schema for generic process tomography sensors

A schema is introduced that aims to facilitate the widespread exploitation of the science of process tomography (PT) that promises a unique multidimensional sensing opportunity. Although PT has been developed to an advanced state, applications have been laboratory or pilot-plant based, configured on an end-to-end basis, and limited typically to the formation of images that attempt to represent process contents. The schema facilitates the fusion of multidimensional internal process state data in terms of a model that yields directly usable process information, either for design model confirmation or for effective plant monitoring or control, here termed a reality visualization model (RVM). A generic view leads to a taxonomy of process types and their respective RVM. An illustrative example is included and a review of typical sensor system components is given

Predicting the movements of permanently installed electrodes on an active landslide using time-lapse geoelectrical resistivity data only

If 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 2D 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 datasets 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 % 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

Geophysical-geotechnical sensor networks for landslide monitoring

Landslides are often the result of complex, multi-phase processes where gradual deterioration of shear strength within the sub-surface precedes the appearance of surface features and slope failure. Moisture content increases and the build-up of associated pore water pressures are invariably associated with a loss of strength, and thus are a precursor to failure. Consequently, hydraulic processes typically play a major role in the development of landslides. Geoelectrical techniques, such as resistivity and self-potential are being increasingly applied to study landslide structure and the hydraulics of landslide processes. The great strengths of these techniques are that they provide spatial or volumetric information at the site scale, which, when calibrated with appropriate geotechnical and hydrogeological data, can be used to characterise lithological variability and monitor hydraulic changes in the subsurface. In this study we describe the development of an automated time-lapse electrical resistivity tomography (ALERT) and geotechnical monitoring system on an active inland landslide near Malton, North Yorkshire, UK. The overarching objective of the research is to develop a 4D landslide monitoring system that can characterise the subsurface structure of the landslide, and reveal the hydraulic precursors to movement. The site is a particularly import research facility as it is representative of many lowland UK situations in which weak mudrocks have failed on valley sides. Significant research efforts have already been expended at the site, and a number of baseline data sets have been collected, including ground and airborne LIDAR, geomorphologic and geological maps, and geophysical models. The monitoring network comprises an ALERT monitoring station connected to a 3D monitoring electrode array installed across an area of 5,500 m2, extending from above the back scarp to beyond the toe of the landslide. The ALERT instrument uses wireless telemetry (in this case GPRS) to communicate with an office based server, which runs control software and a database management system. The control software is used to schedule data acquisition, whilst the database management system stores, processes and inverts the remotely streamed ERT data. Once installed and configured, the system operates autonomously without manual intervention. Modifications to the ALERT system at this site have included the addition of environmental and geotechnical sensors to monitor rainfall, ground movement, ground and air temperature, and pore pressure changes within the landslide. The system is housed in a weatherproof enclosure and is powered by batteries charged by a wind turbine & solar panels. 3D ERT images generated from the landslide have been calibrated against resistivity information derived from laboratory testing of borehole core recovered from the landslide. The calibrated images revealed key aspects of the 3D landslide structure, including the lateral extent of slipped material and zones of depletion and accumulation; the surface of separation and the thickness of individual earth flow lobes; and the dipping in situ geological boundary between the bedrock formations. Time-lapse analysis of resistivity signatures has revealed artefacts within the images that are diagnostic of electrode movement. Analytical models have been developed to simulate the observed artefacts, from which predictions of electrode movement have been derived. This information has been used to correct the ERT data sets, and has provided a means of using ERT to monitor landslide movement across the entire ALERT imaging area. Initial assessment of seasonal changes in the resistivity signature has indicated that the system is sensitive to moisture content changes in the body of the landslide, thereby providing a basis for further development of the system with the aim of monitoring hydraulic precursors to failure

Muons tomography applied to geosciences and volcanology

Imaging the inner part of large geological targets is an important issue in geosciences with various applications. Dif- ferent approaches already exist (e.g. gravimetry, electrical tomography) that give access to a wide range of informations but with identified limitations or drawbacks (e.g. intrinsic ambiguity of the inverse problem, time consuming deployment of sensors over large distances). Here we present an alternative and complementary tomography method based on the measurement of the cosmic muons flux attenuation through the geological structures. We detail the basics of this muon tomography with a special emphasis on the photo-active detectors.Comment: Invited talk at the 6th conference on New Developments In Photodetection (NDIP'11), Lyon-France, July 4-8, 2011; Nuclear Instruments and Methods in Physics Research Section A, 201

Time-lapse capacitive resistivity imaging: a new technology concept for the monitoring of permafrost

The British Geological Survey, in partnership with the Universities of Sussex and Bonn, is investigating and seeking to prove a new technology concept for the non-invasive volumetric imaging and routine temporal monitoring of the thermal state of permafrost (Figure 1), a key indicator of global climate change. Capacitive Resistivity Imaging (CRI), a technique based upon a low-frequency, capacitively-coupled measurement approach (Kuras et al., 2006) is applied in order to emulate Electrical Resistivity Tomography (ERT) methodology, but without the need for galvanic contact on frozen soils or rocks. Recent work has shown that temperature-calibrated ERT using galvanic sensors (Figure 2) is capable of imaging recession and re-advance of rock permafrost in response to the ambient temperature regime. However, the use of galvanic sensors can lead to significant practical limitations on field measurements due to high levels of and large variations in contact resistances between sensors and the host material as it freezes and thaws Figure 3). The capacitive technology developed here overcomes this problem and provides a more robust means of making high-quality resistance measurements with permanently installed sensors over time. Reducing the uncertainty associated with uncontrolled noise from galvanic sensors increases the value of time-lapse ERT datasets in the context of monitoring permafrost