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GRADIENT AND MID-POINT-REFERRED MEASUREMENTS FOR MULTI-CHANNEL 2D RESISTIVITY IMAGING Torleif Dahlin 1 and Bing Zhou 2 1 2

Dept of Geotechnology, Lund University, Box 118 S-221 00, Lund, Sweden Dept of Geology and Geophysics, University of Adelaide, SA 5005, Australia INTRODUCTION

Resistivity imaging now becomes more and more popular in electrical exploration, due to its ability to efficiently and effectively produce images of the subsurface as a result of the availability of automated data acquisition systems and efficient user-friendly inversion software. One of the major limitations of the technique today is the time-consuming measurement process that tempts data acquisition teams to reduce the data density in order to save expensive field operation time, which in turn can be devastating for the imaging quality. In this paper, two electrode configurations suitable for multi-channel-recording, called gradient array (GD) and the midpoint-potential-referred measurement (MPR), were numerically examined for 2D resistivity imaging. These electrode configurations are well suited for multi-channel data acquisition systems, so that many data-points can be recorded simultaneously for each current injection, so as to reduce fieldwork time very significantly without compromising the data density. First, numerical experiments were conducted to examine the spatial resolution and surveying efficiencies for different data acquisition schemes. The results are compared with the results achieved for the same models with the Wenner-α (WN), Schlumberger (SC), dipole-dipole (DD) and pole-dipole (PD) arrays (Dahlin and Zhou 2001). Then field experiments were done, and results from at a waste dump are presented here.

Figure 1: Schematic representations for (a) gradient array and (b) midpoint-potential-referred measurement. The background shows the sensitivity pattern of the configuration for the first potential electrode pair.

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MULTI-CHANNEL SURVEYING SCHEMES Multi-channel gradient surveying is carried out by injecting current with a separation (n+2)a and simultaneously or sequentially picking up all the potential differences between the potential electrodes with the spacing a. Here n is an integer. Figure 1a gives a schematic representation of this array, where the sensitivity function of the measurement with the first potential electrode pair is also shown in the background. Generally, the bigger separation of current electrodes, the deeper penetration of the configuration; the smaller spacing of potential electrodes, the more details of potential variation are obtained. In practical applications the selection of spacing a separation n will be a trade-off between noise sensitivity, horizontal detail and depth penetration. Another similar multi-channel configuration is shown in Figure 1b in which the current set-up is the same as GD but the potential values are measured at all the potential electrodes with the reference point at the mid-electrode of the configuration. Also in this plot the sensitivity function of the first measurement is shown in the background. So, we called it the midpoint-potentialreferred measurement (MPR). Like the GD survey, MPR also has many combinations between the spacing a and the separation n, which can be optimised for effectiveness and efficiency according to the practical considerations. NUMERICAL MODELLING To investigate the imaging capabilities of the two configurations and easily compare with other electrode arrays, the synthetic models used before to investigate the imaging quality of eight common electrode arrays were employed again (Dahlin and Zhou 2001). Five models intended to reflect geological or environmental situations were used in this work, namely a buried channel of coarse-grained sediments, a conductive dyke with overburden, a resistive dyke with overburden, dipping blocks of different widths and buried waste ponds. The imaging abilities of the electrode arrays were examined using robust (L1-norm) and least-squares (L2-norm) inversions with the five models, at different and array dependent noise levels and using different data densities of the same electrode layout. For GD and MPR measurements the signal-to-noise (S/N) analysis shows that MPR has better S/N ratio than GD, and both have better S/N-ratio than the DD array. In each surveying scheme, appropriate parameters a and n for the arrays were chosen so that they have similar numbers of data-points and data coverage, i.e. for the three measurement schemes, we used over 3500 data-points for Survey 1, around 2000 data-points for Survey 2 and about 1000 or less data-points for Survey 3. This makes them comparable in terms of imaging quality, and the different data densities examines the responses in imaging quality to data density of the arrays. In order to compare the imaging quality of the different electrode arrays the cross-correlation values between the inverted model and the true model were calculated, which may quantitatively indicate how close the inverted model is to the real model. Figure 2 is the result of the calculations in which six electrode configurations (PD, WN, SC, DD, GD and MPR) and the three surveying schemes with different data density. So, Figure 2 gives summary view of the imaging quality and makes a comprehensive comparison of these configurations. One can see that although the three surveying schemes have quite different data density the imaging quality is relatively robust, but it can pay off to increase the data density above the lowest level in some cases. It can be seen that MPR has an imaging quality at least as good as WN, while GD gives an image quality that is clearly competitive with PD, SC and DD.

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Figure 2: Cross-correlation between true and L1-norm inverted models for: (a) buried channel, (b) narrow conductive/resistive dyke, (c) dipping blocks and (d) waste ponds. Results for three different data densities are shown.

Figure 3: Inverted sections for the same line based on a) Wenner, b) gradient and c) dipoledipole array data. FIELD TEST A field test was carried out at the Härlöv waste deposit in southern Sweden. The waste is mainly of domestic origin, and covered by soil material that varies in thickness and character. The investigation was carried out with the purpose of mapping the soil cover. A line measured with three different electrode arrays, WN, GD and DD, is presented here. An electrode spacing of 1m 159

was used for high resolution of the shallow soil cover. A new instrument developed at Lund University was used together with standard relay switches and cables etc. from the ABEM Lund Imaging System, measuring in this case in three channels allowing rapid data acquisition. Inverted sections from the data are shown in Figure 3. According to shallow auger sampling there is 0.9 m fill consisting of mixed soil material at 32 m along the line, underlain by waste. At 82 m augering went through 2 m mixed soil fill without reaching the waste. Similar variation in depth was found by augering in more than 30 points in the vicinity, and the upper fill material consisted of sand, clay, clayey till, bricks, lime etc.. The main character of the inverted sections is similar between the arrays, and the results agree with what can be expected from the augering. In the deeper parts significant differences are evident. It may be noted that a narrow vertical zone at 70m is picked up by all three arrays. However, at 105-110m, the structure at the bottom of the section is mapped as high resistive by WN and GD but conductive by DD. This may be interpreted as being caused by deviations from the 2D assumption that affects the arrays differently depending on the different sensitivity patterns of the arrays. In this case GD and DD were equally efficient in terms of speed of data acquisition, and data quality is good for both although the model residuals are higher for DD. CONCLUSIONS Gradient measurement and mid-point-potential-referred survey are two electrode configurations highly suitable for multi-channel data acquisition systems. The numerical imaging experiments with five synthetic models show that GD scanning measurement can produce a competitive image with DD, SC and PD, which have good spatial resolution in resistivity imaging. MPR, comparing with GD, has a higher S/N-ratio but has a somewhat lower spatial resolution in the image. The resolution capability of MPR is at least as good as WN, but offers more efficient data acquisition with a multi-channel instrument. The imaging quality of both configurations is quite robust with respect to the data density, but in some cases a higher data density than the lowest can yield a better resolution. The field experiment confirms the applicability of GD to the real situations. If a data acquisition system with more channels would be available, and if longer electrode separations were employed, GD would have a clear advantage to DD in terms of signal-to-noise levels, as DD would suffer if both n-factors and electrode separations increased. The results suggest GD should, along with PD, be a prime choice for multi-channel resistivity imaging both in terms of resolution capability and measurement logistics, where the final choice would depend on site logistics. ACKNOWLEDGEMENTS The work presented here was supported by research grants from Elforsk, Svenska Kraftnät, DSIG (Dam Safety Interest Group), the Wenner-Gren Foundation, the Swedish Institute and Carl Trygger’s Foundation, which is gratefully acknowledged. We are indebted to Prof. Dale Morgan for sharing his experiences of the gradient array. REFERENCES Dahlin, T. and Zhou, B. (2001), A numerical comparison of 2D resistivity imaging with eight electrode arrays, Procs. 7th Meeting Environmental And Engineering Geophysics, Birmingham, England, 2-6 September 2001, ELEM01, 2p.

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