An application of three-dimensional electrical resistivity imaging for the detection of an underground waste-water system

A 3D electrical resistivity imaging survey is presented in this paper. The objective was to investigate an underground wastewater system at the University of Malaya, Malaysia. Apparent resistivity data were collected along ten parallel lines using a Wenner-Schlumberger configuration; electrode cables were oriented in the x-direction with 3 m spacing. Roll-along measurements using a line spacing of 3 m were carried out covering a grid of 20 × 10 electrodes. All data sets were merged into a single data file in order to perform a 3D inversion. Two different 3D least squares algorithms, based on the robust inversion method and the smoothness-constrained technique, were used for the inversion of the apparent resistivity data. Both the horizontal and vertical extents of the anomalous zones found by inversion are displayed. The results indicate the superiority of the robust inversion method over the smoothness-constrained technique at this site. The results are in sufficient accordance with previously known information about the investigation area. The results show that 3D electrical resistivity imaging surveys, in combination with an appropriate 3D inversion method, can be highly useful for engineering and archaeological investigations as well as for environmental applications.     

Focused imaging of electrical resistivity data in archaeological prospecting

Electrical resistivity mapping and electrical resistivity profiling are powerful instruments for investigating archaeological structures. Interpretation of geoelectrical data is complicated by near-surface anomalies and the characteristics of the applied electrode arrays. Averaging Wenner α and Wenner β data as an alternative method of focused imaging is presented to overcome these problems. The mechanism of focused imaging is explained using the sensitivity distribution of the combined arrays. Various methods of imaging geoelectrical data are examined with synthetic and field data. In electrical resistivity mapping, inversion of the data is unnecessary when using focused imaging. In electrical resistivity profiling, focused imaging gives a first idea about the subsurface resistivity distribution without achieving the quality obtainable by inversion.     

Detection of sinkholes using 2D electrical resistivity imaging

Sinkholes in dolomitic areas are notoriously difficult geophysical targets, and selecting an appropriate geophysical solution is not straightforward. Electrical resistivity imaging, or tomography (RESTOM) is well suited to mapping sinkholes because of the ability of the technique for detecting resistive features and discriminating subtle resistivity variations. RESTOM surveys were conducted at two sinkhole sites near Pretoria, South Africa. The survey areas are located in the dolomites of the Lyttelton Formation, which forms part of the Malamani Subgroup and Chuniespoort Group of the Transvaal Supergroup. The survey results suggest that RESTOM is an ideal geophysical tool to aid in the detection and monitoring of sinkholes and other subsurface cavities.     

A numerical comparison of 2D resistivity imaging with 10 electrode arrays

Numerical simulations are used to compare the resolution and efficiency of 2D resistivity imaging surveys for 10 electrode arrays. The arrays analysed include pole‐pole (PP), pole‐dipole (PD), half‐Wenner (HW), Wenner‐α (WN), Schlumberger (SC), dipole‐dipole (DD), Wenner‐β (WB), γ‐array (GM), multiple or moving gradient array (GD) and midpoint‐potential‐referred measurement (MPR) arrays. Five synthetic geological models, simulating a buried channel, a narrow conductive dike, a narrow resistive dike, dipping blocks and covered waste ponds, were used to examine the surveying efficiency (anomaly effects, signal‐to‐noise ratios) and the imaging capabilities of these arrays. The responses to variations in the data density and noise sensitivities of these electrode configurations were also investigated using robust (L₁‐norm) inversion and smoothness‐constrained least‐squares (L₂‐norm) inversion for the five synthetic models. The results show the following. (i) GM and WN are less contaminated by noise than the other electrode arrays. (ii) The relative anomaly effects for the different arrays vary with the geological models. However, the relatively high anomaly effects of PP, GM and WB surveys do not always give a high‐resolution image. PD, DD and GD can yield better resolution images than GM, PP, WN and WB, although they are more susceptible to noise contamination. SC is also a strong candidate but is expected to give more edge effects. (iii) The imaging quality of these arrays is relatively robust with respect to reductions in the data density of a multi‐electrode layout within the tested ranges. (iv) The robust inversion generally gives better imaging results than the L₂‐norm inversion, especially with noisy data, except for the dipping block structure presented here. (v) GD and MPR are well suited to multichannel surveying and GD may produce images that are comparable to those obtained with DD and PD. Accordingly, the GD, PD, DD and SC arrays are strongly recommended for 2D resistivity imaging, where the final choice will be determined by the expected geology, the purpose of the survey and logistical considerations.     

Some considerations on electrical resistivity imaging for characterization of waterbed sediments

The paper focuses on defining the performance and limits of ERI in the detection and sedimentary characterization of near-bottom thin layers. The analysis of the resolution of floating and submerged cables, and the effect of the accuracy of a priori information (resistivity and thickness) in the data inversion, is based on theory, models and actual data. Theoretical models show that the actual reconstruction of the near water-bottom sediments, in terms of geometry and resistivity, can be obtained only with the submerged cable, however, the data, unlike that acquired with the floating cable, require a priori information on water resistivity and thickness for the data inversion. Theoretical forward models based on wrong a priori water thickness and resistivity information influence the inverted model in different ways, depending on the under- and over-estimation of water resistivity and thickness, and the resistivity contrast of the water–solid layer; however a water–solid resistivity contrast of less than 2 and within 10% of error in water resistivity has no effect. Overestimating water resistivity depicts a ground similar to the actual ground in terms of resistivity, more so than the underestimation of water resistivity. Moreover, the data inversion is less influenced by water parameter error in the case of low resistivity contrast in the water–solid layer, than it is for high resistivity contrast. Wenner and Schlumberger arrays give comparable results, while a dipole–dipole array seems to be more sensitive to the accuracy of apparent resistivity measurements and a priori information on water.The theoretical considerations were validated by actual data acquired with a submerged cable on the Tiber River. The study has shown that if highly accurate measurements are made of water thickness and resistivity, then electrical resistivity imaging from the submerged cable can be used in addition to, or even to substitute, seismic data for the reconstruction of the features and sedimentary characterization of near-bed sediments where seismic data fail to give a suitable resolution.     

Nonlinear inversion of electrical resistivity imaging using pruning Bayesian neural networks

Conventional artificial neural networks used to solve electrical resistivity imaging (ERI) inversion problem suffer from overfitting and local minima. To solve these problems, we propose to use a pruning Bayesian neural network (PBNN) nonlinear inversion method and a sample design method based on the K-medoids clustering algorithm. In the sample design method, the training samples of the neural network are designed according to the prior information provided by the K-medoids clustering results; thus, the training process of the neural network is well guided. The proposed PBNN, based on Bayesian regularization, is used to select the hidden layer structure by assessing the effect of each hidden neuron to the inversion results. Then, the hyperparameter α _k , which is based on the generalized mean, is chosen to guide the pruning process according to the prior distribution of the training samples under the small-sample condition. The proposed algorithm is more efficient than other common adaptive regularization methods in geophysics. The inversion of synthetic data and field data suggests that the proposed method suppresses the noise in the neural network training stage and enhances the generalization. The inversion results with the proposed method are better than those of the BPNN, RBFNN, and RRBFNN inversion methods as well as the conventional least squares inversion.     

The inversion of data from very large three-dimensional electrical resistivity tomography mobile surveys

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.     

Monitoring crack development in fiber concrete beam by using electrical resistivity imaging

Accurate detection of damaged concrete zones plays an important role in selecting the proper remedial technique. This study presents results from an application of the electrical imaging method to monitor the development of cracks in fiber concrete beams.The study showed that resistivity measurements on the concrete specimens were able to detect the increase of concrete resistivity with the curing time that reached about 65 Ωm after 28 days of curing. A similar development trend of concrete compressive strength was also found.Two types of cracks were investigated, i.e., artificial cracks made of plastic sheets inserted in concrete and cracks developed during a four-step loading test. A mini-electric imaging survey with Wenner array was conducted on the tension face of the beams. To deal with the effect of the beam size new procedures to correct resistivity measurements before inversion were proposed and successfully applied in this study. The results indicated that both crack direction and depth could be accurately determined in the inverted resistivity sections.     

Time‐lapse electrical resistivity imaging of solute transport in a karst conduit

The use of electrical resistivity surveys to locate karst conduits has shown mixed success. However, time‐lapse electrical resistivity imaging combined with salt injection improves conduit detection and can yield valuable insight into solute transport behaviour. We present a proof of concept above a known karst conduit in the Kentucky Horse Park (Lexington, Kentucky). A salt tracer solution was injected into a karst window over a 45‐min interval, and repeat resistivity surveys were collected every 20 min along a 125‐m transect near a monitoring well approximately 750 m downgradient from the injection site. In situ fluid conductivity measurements in the well peaked at approximately 25% of the initial value about 3 h after salt injection. Time‐lapse electrical resistivity inversions show two broad zones at the approximate conduit depth where resistivity decreased and then recovered in general agreement with in situ measurements. Combined salt injection and electrical resistivity imaging are a promising tool for locating karst conduits. The method is also useful for gaining insight into conduit geometry and could be expanded to include multiple electrical resistivity transects. Copyright © 2015 John Wiley & Sons, Ltd.     

强地震附近电阻率对称四极观测的探测深度

针对我国地震监测预报中固定地点和固定观测装置及参数的视电阻率观测,给出了半空间倾斜各向异性介质中电阻率对称四极观测的理论探测深度,研究了地震前兆信息的检测深度问题,得到：(1)在强地震、孕震晚期阶段,在震中区及附近可检测到地壳近地表较深部介质的电阻率变化,其深度大于或远大于均匀介质之;(2)震级、震中距、观测方向不同或在不同的孕震阶段,探测深度存在差异,甚至存在大的差异,且是动态变化的.并依据理论探测深度讨论了地震视电阻率前兆变化的复杂性、地电台址电性条件等问题.     

River terrace sand and gravel deposit reserve estimation using three-dimensional electrical resistivity tomography for bedrock surface detection

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.     

Field test to compare 3D imaging capabilities of three arrays in a site with high resistivity contrast regions

The applicability of three kinds of electrode configurations used to delineate a buried horizontal pipe was studied. A 3D resistivity imaging survey was carried out along eight parallel lines using pole-pole, pole-dipole, and dipole-dipole arrays with 1m minimum electrode spacings. Roll-along measurements were carried out to cover a rectangular grid. The 2D and 3D least squares algorithms based on the robust inversion method were used in the inversion of the apparent resistivity data sets. The 2D inversion of data sets could not delineate the orientation and dimension of the subsurface anomalies clearly. To obtain more accurate results, a 3D joint inversion of the pole-pole and pole-dipole data sets was performed, as well as of pole-pole and dipole-dipole data sets. In this case, both horizontal and vertical dimensions of subsurface structures were resolved. The resulting model obtained from each array was compared to those of joint inversion method. The result showed that the horizontal resolution does not improve so much as that in the vertical direction when joint inversion is applied.     

Anomalous electrical resistivity anisotropy in clean reservoir sandstones

We report novel laboratory measurements of the full electrical resistivity tensor in reservoir analogue quartzose sandstones with clay contents less than 1.5%. We show that clean, homogeneous, visually uniform sandstone samples typically display between 15% and 25% resistivity anisotropy with minimum resistivity normal to the bedding plane. Thin‐section petrography, analysis of fabric anisotropy, and comparison to finite‐element simulations of grain pack compaction show that the observed anisotropy symmetries and magnitudes can be explained by syn‐depositional and post‐depositional compaction processes. Our findings suggest that: electrical resistivity anisotropy is likely to be present in most clastic rocks as a consequence of ballistic deposition and compaction; compaction may be deduced from measurements of electrical anisotropy; and the anisotropy observed at larger scales in well logging and controlled‐source electromagnetic data, with maximum resistivity normal to bedding, is most likely the result of meso‐scale (10^?1 m–10¹ m) periodic layering of electrically dissimilar lithologies.     

Method for continuous monitoring of electrical rock resistivity

This paper presents the main results of developing a method for continuous monitoring of rock resistivity. The method uses continuous electromagnetic radiation of man-made or natural origin as a sounding signal. Underground electrical antennas are used as sensors. The physical basis of this method is the dependence of rock resistivity on the degree of fluid saturation, which changes under mechanical stress variations in geological media.     

Small-scale electrical resistivity tomography of wet fractured rocks

This paper describes a series of experiments that tested the ability of the electrical resistivity tomography (ERT) method to locate correctly wet and dry fractures in a meso-scale model. The goal was to develop a method of monitoring the flow of water through a fractured rock matrix. The model was a four by six array of limestone blocks equipped with 28 stainless steel electrodes. Dry fractures were created by placing pieces of vinyl between one or more blocks. Wet fractures were created by injecting tap water into a joint between blocks. In electrical terms, the dry fractures are resistive and the wet fractures are conductive. The quantities measured by the ERT system are current and voltage around the outside edge of the model. The raw ERT data were translated to resistivity values inside the model using a three-dimensional Occam's inversion routine. This routine was one of the key components of ERT being tested. The model presented several challenges. First, the resistivity of both the blocks and the joints was highly variable. Second, the resistive targets introduced extreme changes the software could not precisely quantify. Third, the abrupt changes inherent in a fracture system were contrary to the smoothly varying changes expected by the Occam's inversion routine. Fourth, the response of the conductive fractures was small compared to the background variability. In general, ERT was able to locate correctly resistive fractures. Problems occurred, however, when the resistive fracture was near the edges of the model or when multiple fractures were close together. In particular, ERT tended to position the fracture closer to the model center than its true location. Conductive fractures yielded much smaller responses than the resistive case. A difference-inversion method was able to correctly locate these targets.     

three-dimensional sensitivity coefficients of apparent resistivity and preliminary application

We calculate three-dimensional sensitivity coefficients distribution of apparent resistivity observation when Schlumberger array is used by using finite element method. Analysis results suggest that for the situation of one-dimensional positive or minus coefficient of surface medium, three-dimensional sensitivity coefficients distribution at surface shows similar patterns, and sensitivity coefficients distributions of different layered electric structures are also similar. There are two approximate ellipses at the two-dimensional surface plane between current electrodes and potential electrodes, where sensitivity coefficients are minus, and sensitivity coefficients at other areas are positive. Sensitivity coefficients at two approximate ellipses between current electrodes and potential electrodes are minus at the vertical section along monitoring line, while others are positive. From the three-dimensional view, minus sensitivity coefficients are at the two approximate half ellipsoids between current electrodes and potential electrodes when arrays are applied at surface. And coefficients near the electrodes are much greater than other areas. When resistivity of local areas at surface changes, we can qualitatively analyze the disturbing effects caused by the areas using three dimensional sensitivity coefficients distribution, and the analysis result can serve as reference for further experiment and numerical model quantitative analysis.     

The use of multi-electrode resistivity imaging in gravel prospecting

We investigated the potential of using a 24-electrode resistivity imaging apparatus for rapid reconnaissance surveys for natural-aggregate accumulation. The surveys were first calibrated at sites with known geometry of sand and gravel layers, which showed that subsurface accumulation of coarse material was accurately resolved with both 2- and 4-m electrode spacing. The inverted absolute resistivity of economically viable gravel deposits varied in the range of 300–1500 Ω m, depending on variation in ground-moisture levels. The exploration surveys were then conducted at seven sites where geomorphological analyses indicated a potential for gravel. Four of these sites, where subsurface resistivity did not exceed 30–40 Ω m, were found to have very little or no coarse material. The three remaining sites showed significant accumulations of high-resistivity material, two of which were subsequently augered for verification. The results of drilling demonstrated that resistivity images were an effective indicator of the presence of coarse material in the subsurface, allowing accurate determination of subsurface distribution and thickness of sand and gravel strata. The total volume of a deposit could easily be estimated from resistivity images. The absolute quality and economic value of the material, is, however, difficult to ascertain from resistivity images alone without drilling.     

Landslide monitoring in southwestern China via time-lapse electrical resistivity tomography

The dynamic monitoring of landslides in engineering geology has focused on the correlation among landslide stability, rainwater infiltration, and subsurface hydrogeology. However, the understanding of this complicated correlation is still poor and inadequate. Thus, in this study, we investigated a typical landslide in southwestern China via time-lapse electrical resistivity tomography (TLERT) in November 2013 and August 2014. We studied landslide mechanisms based on the spatiotemporal characteristics of surface water infiltration and flow within the landslide body. Combined with borehole data, inverted resistivity models accurately defined the interface between Quaternary sediments and bedrock. Preferential flow pathways attributed to fracture zones and fissures were also delineated. In addition, we found that surface water permeates through these pathways into the slipping mass and drains away as fissure water in the fractured bedrock, probably causing the weakly weathered layer to gradually soften and erode, eventually leading to a landslide. Clearly, TLERT dynamic monitoring can provide precursory information of critical sliding and can be used in landslide stability analysis and prediction.     

高密度电阻率法在地面塌陷调查中的应用

浙中的武义、永康、东阳等县市是浙江省最主要的萤石产区.由于疏于管理等原因，造成采坑和已经闭坑的矿山频繁地出现地面塌陷等地质灾害，已成为当地最严重和潜在的地质灾害.本文介绍高密度电阻率法在武义县荷叶塘矿区采空区探测中的方法和应用效果，建议在本区开展采空区勘察中将高密度电阻率法作为必需手段推广使用，并指出以α和α2为首选装置，A\|M等其他装置可根据需要备选或配合使用，以提高探测精度.