Enhanced resolution for long electrode ERT

Rucker, Dale F.

doi:10.1111/j.1365-246x.2012.05643.x

Cited by 29 publications

(14 citation statements)

References 28 publications

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“…Following the first modeling and resolution studies of Ramirez et al (2003) and Rucker (2012), we carry out systematic synthetic simulations to obtain numerically safe routines and to demonstrate the ability of the method in the context of saltwater intrusion. Discretization parameters (electrode diameter and number of facets) were varied to appraise the numerical error and effort.…”

Section: Introductionmentioning

confidence: 99%

Numerical study of long-electrode electric resistivity tomography — Accuracy, sensitivity, and resolution

2015

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Electric resistivity tomography (ERT) is a widespread technique used for geologic and hydrological subsurface characterization. The 3D application is limited to small scales due to the enormous effort required for field surveys. Long-electrode (LE)-ERT using steel-cased boreholes can overcome small-scale limitations and has recently gained significant attention. However, no systematic investigation concerning the performance of long electrodes has been performed. We have conducted synthetic studies of LE-ERT to understand its advantages and limitations. We have compared three different approaches of modeling long electrodes, placing particular emphasis on the complete electrode model, to determine which reflects the physical reality best and thus can be used as a benchmark. The conductive cell model led to comparable results but was numerically more expensive. An interesting alternative approach was the shunt electrode model, which does not require discretizing the lateral extension of the casing. Systematic sensitivity studies revealed that model resolution could be enhanced in the borehole depth range through the use of electrodes of different lengths or surface electrodes. Varying contact impedances along different sections of the borehole can change the electric field visibly and influence four-point measurements. Even if large electrode segments show reduced coupling, the influence on voltage measurements was below 4% for realistic contact impedances. We have proven the applicability of LE-ERT for imaging lateral saltwater movement through the simulation of simple scenarios in the context of saltwater intrusion. Our synthetic examples determined the advantage of long electrodes compared with simulations using surface electrodes. The 3D inversion of synthetic data sets revealed that the modeled anomalies could be imaged in most cases. Different models revealed limitations due to poor vertical resolution and supported the usage of casings with different lengths or in combination with surface electrodes to improve resolution.

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Section: Introductionmentioning

confidence: 99%

Numerical study of long-electrode electric resistivity tomography — Accuracy, sensitivity, and resolution

2015

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“…It is observed from the table that for all the models, the reconstructed resistivity values of the blocks are underestimated compared to the resistivity of the true models, while for the background the reconstructed resistivity values are an overestimation. In essence, the amplitude of resistivity has been dampened and is a known feature inherent in resistivity imaging (RUCKER 2012). For the individual electrode arrays, it is observed that the dipoledipole images give better results than WennerSchlumberger and pole-dipole images.…”

Section: Synthetic Resultsmentioning

confidence: 89%

“…Several researchers have compared different electrode arrays individually on the basis of their sensitivity analysis, depth of investigations, and responses to resolving vertical or horizontal structures (SASAKI 1992;DAHLIN 2001;BENTLEY and GHARIBI 2004;FIANDACA et al 2005;CAPIZZI et al 2007;BERGE and DRAHOR 2009;MARTORANA et al 2009;NEYAMADPOUR et al 2010;RUCKER 2012). Meanwhile, in related studies, the use of joint inversion techniques have been introduced and used for combining two or more geophysical data into a single image for the cross gradients (GALLARDO and MEJU 2003 and structural approach (HABER and OLDENBURG 1997).…”

Section: Introductionmentioning

confidence: 99%

Combining Multiple Electrode Arrays for Two-Dimensional Electrical Resistivity Imaging Using the Unsupervised Classification Technique

Ishola

Nawawi

Abdullah

2014

Pure Appl. Geophys.

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This article describes the use of k-means clustering, an unsupervised image classification technique, to help interpret subsurface targets. The k-means algorithm is employed to combine and classify the two-dimensional (2D) inverse resistivity models obtained from three different electrode arrays. The algorithm is initialized through the selection of the number of clusters, number of iterations and other parameters such as stopping criteria. Automatically, it seeks to find groups of closely related resistivity values that belong to the same cluster and are more similar to each other than resistivity values belonging to other clusters. The approach is applied to both synthetic and field data. The 2D postinversions of the resistivity data were preprocessed by resampling and interpolating to the same coordinate. Following the preprocessing, the three images are combined into a single classified image. All the image preprocessing, manipulation and analysis are performed using the PCI Geomatics software package. The results of the clustering and classification are presented as classified images. An assessment of the performance of the individual and combined images for the synthetic models is carried out using an error matrix, mean absolute error and mean absolute percent error. The estimated errors show that images obtained from maximum values of the reconstructed resistivity for the different models give the best representation of the true models. Additionally, the overall accuracy and kappa values show good agreement between the combined classified images and true models. Depending on the model, the overall accuracy ranges from 86 to 99 %, while the kappa coefficient is in the range of 54-98 %. Classified images with kappa coefficients greater than 0.8 show strong agreement, while images with kappa coefficients greater than 0.5 but less than 0.8 give moderate agreement. For the field data, the k-mean classifier produces images that incorporate structural features of the three electrode array configurations. Consequently, some clusters that overwhelmingly correspond to the lithologic units of the investigated areas are better identified than the tomographic images of each data set considered separately, underscoring the relevance of the unsupervised classification technique in this study.

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“…To combat this, a different array could be used where model resolution is more evenly distributed throughout the domain. Many have recognized that particular optimized arrays can produce better subsurface images (e.g., Stummer, Maurer and Green 2004;Loke, Wilkinson and Chambers 2010;Wilkinson et al 2012), which could easily be employed here by transposing the pole-pole array to any desired four-pole array, as shown practically in Rucker (2012). When constrained by the electrical current information, it is anticipated that a new level of accuracy can be achieved in resistivity imaging.…”

Section: Discussionmentioning

confidence: 99%

“…Oldenburg and Li () presented a method to measure the DOI by quantifying how much each region of the resistivity image changed by analysing the difference in two or more inversion results with different model constraints (Freidel ). In our work (e.g., Rucker ), we have primarily focused on the model resolution to investigate the consequence of typical decisions made for conducting resistivity surveys to resolve a target, including model parameters (inverse model cell size) and acquisition parameters (electrode density and array type).…”

Section: Resitivity Acquisitonmentioning

confidence: 99%

Real‐time electrical monitoring of reagent delivery during a subsurface amendment experiment

Rucker

Crook

Winterton³

et al. 2013

Near Surface Geophysics

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An electrical resistivity monitoring survey was conducted on a mine heap to track reagent movement during high-pressure injections. The injections were designed to increase the dissolution of metallic gold from low-grade ore and enhance recovery after surface leaching had ceased. The main objective of the geoelectrical monitoring was to observe the effectiveness of the injection technique and provide feedback to optimize injection parameters in real time. Real-time assessment was achieved by monitoring the raw output current and transfer resistance on a network of borehole electrodes installed around the injection well. It was demonstrated that the output current increased significantly on particular borehole electrodes after commencement of reagent injection, when the wetting front arrived at the electrodes. When injection ceased, the electrical current returned to the initial baseline current values. The timing and distribution of the electrodes demonstrating this behaviour varied with injection depth. The internal structure of the heap was likely a controlling factor in reagent movement. Resistance, converted to apparent resistivity, was also shown to change significantly in the region near the injection. Verification of the real-time assessment was conducted with post-injection time-lapse 3D tomographic inversion. While inverse modelling provides a truer 3D representation of reagent injection, the cost was shown to be a time-lag of 3.5 days to complete the modelling. The simplicity of monitoring the raw current output and voltage can make this a powerful tool for real-time tracking of fluid movement in the subsurface.

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Enhanced resolution for long electrode ERT

Cited by 29 publications

References 28 publications

Numerical study of long-electrode electric resistivity tomography — Accuracy, sensitivity, and resolution

Numerical study of long-electrode electric resistivity tomography — Accuracy, sensitivity, and resolution

Combining Multiple Electrode Arrays for Two-Dimensional Electrical Resistivity Imaging Using the Unsupervised Classification Technique

Real‐time electrical monitoring of reagent delivery during a subsurface amendment experiment

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