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Journal ArticleDOI

2.5D resistivity modeling of embankment dams to assess influence from geometry and material properties

02 Jun 2006-Geophysics (Society of Exploration Geophysicists)-Vol. 71, Iss: 3, pp 107-114
TL;DR: In this article, the influence from 3D effects created by specific dam geometry and effects of water level fluctuations in the reservoir was evaluated by modeling two rockfill embankment dams with central till cores in the north of Sweden.
Abstract: Repeated resistivity measurement is a potentially powerful method for monitoring development of internal erosion and anomalous seepage in earth embankment dams. This study is part of a project to improve current longterm monitoring routines and data interpretation and increasing the understanding when interpreting existing data. This is accomplished by modeling various occurrences typical of embankment structures using properties from two rockfill embankment dams with central till cores in the north of Sweden. The study evaluates the influence from 3D effects created by specific dam geometry and effects of water level fluctuations in the reservoir. Moreover, a comparison between different layout locations is carried out, and detectability of internal erosion scenarios is estimated through modeling of simulated damage situations. Software was especially developed to model apparent resistivity for geometries and material distributions for embankment dams. The model shows that the 3D effect from the embankment geometry is clearly significant when measuring along dam crests. For dams constructed with a conductive core of fine-grained soil and high-resistive rockfill, the effect becomes greatly enhanced. Also, water level fluctuations have a clear effect on apparent resistivities. Only small differences were found between the investigated arrays. A layout along the top of the crest is optimal for monitoring on existing dams, where intrusive investigations are normally avoided, because it is important to pass the current through the conductive core, which is often the main target of investigation. The investigation technique has proven beneficial for improving monitoring routines and increasing the understanding of results from the ongoing monitoring programs. Although the technique and software are developed for dam modeling, it could be used for estimation of 3D influence on any elongated structure with a 2D cross section.

Summary (3 min read)

INTRODUCTION

  • Internal erosion is one of the major causes of embankment dam failures.
  • This method has been shown to be effective in revealing information about conditions in the core itself.
  • This means that application of standard 2D techniques on embankment dams with measurement layouts along the crest of the dam cannot be used without cau-tion because of the obvious 3D effects from the dam geometry.
  • The study covered several situations and scenarios essential for interpreting and evaluating data from resistivity measurements on embankment dams.

Software description

  • Software written for 2D resistivity/IP modeling was modified to simulate a dam-monitoring survey by allowing dam geometries in the 2D-model parameterization and a 3D measurement, which means that the current injection and potential pickup may be at any point in the dam.
  • Assumed resistivities must be constant in the electrode-layout direction, i.e., along the dam, and variable in the dam cross section, whereas the electrodes can be placed anywhere in all three dimensions.
  • Such 2.5D modeling is simply accomplished by involving the inverse Fourier transform for an electrode array parallel to the strike direction ͑Dey and Morrison, 1979a, b; Queralt et al., 1991͒.
  • The software uses the finite-element method because this method makes it easier to deal with the dam geometry, compared to the finite-difference method.
  • The authors compared the results with different element sizes and wavenumber sampling schemes.

Model geometry, material properties, and damage types

  • The dam model is a zoned embankment dam with a central till core, surrounding filter zones, and support rockfill ͑Figure 1͒.
  • Because of difficulties in estimating electrical properties of involved materials and lack of appropriate data in literature, some uncertainties are connected to these parameters.
  • For this study, the core resistivity was estimated from existing monitoring data from two Swedish dams ͑Johansson et al., 2000͒ together with laboratory resistivity measurements of similar till samples ͑Bergström, 1998͒ -even though an unsatisfying variation was found in this data.
  • Damaged zones often have this kind of extended shape because the dam is constructed in layers.
  • A resistivity increase of five times in the core was assumed because of internal erosion.

Modeling strategies

  • To evaluate responses from different electrode arrays, four arrays were selected for all modeling situations.
  • An electrode spacing of 5 m was selected for the dam model because that gives a reasonable relation between electrode spacing and dam height similar to what could be expected in an actual in situ situation.
  • All combinations, including a-spacings from one to seven ͑multiples of five͒ and n-factors ͑one to six͒, were used for the calculations.
  • Of the four examined arrays, dipole-dipole is by its nature most different from the others, and in some situations, it gave responses that were different than the others.
  • Only when examining special cases, such as cylindrical damages or elongated damage zones with lim-.

3D effects

  • The 3D effects and their dependency on material parameters were examined for a dam with the model cross section described in Figure 1 .
  • The effects were estimated by comparing the responses from two models: a 2.5D model and a 1D model with the properties of the model midsection, i.e., the section with the electrode layout extended to horizontal layers.
  • Sample results for the dipole-dipole and the Schlumberger arrays are shown in Figure 2 .
  • Next, the dependency of input-material parameters was similarly evaluated using a model with constant resistivity for the whole dam cross section, including the reservoir water.
  • It is obvious that most of the huge 3D effect arises from the contrast between the relatively conductive core and the high resistivity of the main part of the dam cross section.

Reservoir-level fluctuations

  • The effect of lowering the reservoir was examined, using the dam model in Figure 1 .
  • 3D effects estimated as relation between 1D and 2.5D models with assumed material properties for the modeled cross section and reservoir.
  • For both arrays, a-spacing is the spacing between potential electrodes, and n-factor is the shortest distance between potential and current electrode divided by the a-spacing.
  • The calculations were made once for each depth.
  • For the large lowering of the reservoir, the same effect was estimated to be moving toward approximately 40% ͑1.40 times͒ for the largest electrode distances.

Detectability of internal erosion zones

  • When internal erosion occurs, the material properties of the eroded zone will change as porosity increases and fines are washed away.
  • A permanent or possibly semipermanent change ͑because it may heal by itself͒ in the resistivity characteristics of the dam core will occur.
  • To estimate the imaging potential of the damages, standard 1D, multilayer, smooth inversion ͑Auken et al., 2004͒ was carried out on the forward model responses.
  • The anomaly effect is enhanced through inversion, but effects from the dam geometry cause the damage to localize at a shallower level than the real case ͑Figure 9͒.
  • It is not likely that the damages would be detected by a single survey, but with repeated measurements the possibilities would be fair.

Comparison of different layout locations

  • Modeling of different layout placements is helpful for interpreting data from Swedish dam monitoring, especially at the Hällby Dam, where layouts are not only placed along the crest but also on a line along the upstream and the downstream side ͑Johansson et al., 2000͒.
  • All of them are placed directly beneath the surface of the dam.
  • For the layouts along the upstream toe and the mid-upstream slope, the upstream electrodes are placed below the water table.
  • The calculated-anomaly effects are less than 1% ͑Ͻ1.01 times͒ for all different placements of the layouts, re- gardless of the damage location.
  • Obviously, the channeling effect that concentrates current flow within the conductive dam core is an important factor.

DISCUSSION AND CONCLUSIONS

  • Resistivity measurements on embankment dam geometries are influenced by many factors, such as effects caused by the geometry and variation in material properties across the dam cross section, impact of water-level changes, and electrode-layout location.
  • The influence is similar for all of the examined arrays, ranging from three to seven times the value of the standard 1D model for the geometry and material properties assumed.
  • Resistivities measured along the dam crest were shown to be significantly influenced by fluctuations in the reservoir level.
  • It is unlikely that such damages could be detected by a single resistivity survey using surface electrodes.
  • Also note that all damage types were shaped as extended layers and that the results may not be fully applicable, for instance, to a cylindrically shaped damage and other damage zones with limited extent along the dam.

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2.5D resistivity modeling of embankment dams to assess influence from geometry and
material properties
Sjödahl, Pontus; Dahlin, Torleif; Zhou, Bing
Published in:
Geophysics
DOI:
10.1190/1.2198217
2006
Link to publication
Citation for published version (APA):
Sjödahl, P., Dahlin, T., & Zhou, B. (2006). 2.5D resistivity modeling of embankment dams to assess influence
from geometry and material properties.
Geophysics
,
71
(3), G107-G114. https://doi.org/10.1190/1.2198217
Total number of authors:
3
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2.5D resistivity modeling of embankment dams to assess
influence from geometry and material properties
Pontus Sjödahl
1
, Torleif Dahlin
1
, and Bing Zhou
2
ABSTRACT
Repeated resistivity measurement is a potentially powerful
method for monitoring development of internal erosion and
anomalous seepage in earth embankment dams. This study is
part of a project to improve current longterm monitoring rou-
tines and data interpretation and increasing the understanding
when interpreting existing data. This is accomplished by mod-
eling various occurrences typical of embankment structures us-
ing properties from two rockfill embankment dams with central
till cores in the north of Sweden. The study evaluates the influ-
ence from 3D effects created by specific dam geometry and ef-
fects of water level fluctuations in the reservoir. Moreover, a
comparison between different layout locations is carried out,
and detectability of internal erosion scenarios is estimated
through modeling of simulated damage situations. Software
was especially developed to model apparent resistivity for ge-
ometries and material distributions for embankment dams. The
model shows that the 3D effect from the embankment geometry
is clearly significant when measuring along dam crests. For
dams constructed with a conductive core of fine-grained soil
and high-resistive rockfill, the effect becomes greatly enhanced.
Also, water level fluctuations have a clear effect on apparent re-
sistivities. Only small differences were found between the in-
vestigated arrays. A layout along the top of the crest is optimal
for monitoring on existing dams, where intrusive investigations
are normally avoided, because it is important to pass the current
through the conductive core, which is often the main target of
investigation. The investigation technique has proven beneficial
for improving monitoring routines and increasing the under-
standing of results from the ongoing monitoring programs. Al-
though the technique and software are developed for dam mod-
eling, it could be used for estimation of 3D influence on any
elongated structure with a 2D cross section.
INTRODUCTION
Internal erosion is one of the major causes of embankment dam
failures. Monitoring systems can significantly improve the safety
of such dams. However, to detect erosion early, monitoring sys-
tems must be highly sensitive and, at the same time, sufficiently
cover the embankment area. In addition, it should be possible to in-
stall such monitoring systems in existing dams, and these systems
should be capable of identifying small seepage changes, as well as
leakage. Experience from research and field installations carried
out in Sweden since 1993 indicates that monitoring systems based
on resistivity measurements may be able to meet this need Johans-
son and Dahlin, 1996; Johansson and Dahlin, 1998; Johansson et
al. 2000. In addition, using a resistivity monitoring technique is
essentially nondestructive. This is particularly important when
working with embankment dams, where drilling and other pen-
etrating investigations are normally avoided.
An electrode layout along the top of the dam core is the most
practical and favorable method of installing resistivity monitoring
systems on existing dams. This will be shown later in the paper.
This method has been shown to be effective in revealing informa-
tion about conditions in the core itself. In addition, good electrode
grounding conditions can be provided in the fine-grained environ-
ment commonly found in the dam core Dahlin et al., 2001. Stan-
dard 2D-inversion schemes are a common technique for processing
data from resistivity profiling Smith and Vozoff, 1984; Tripp et al.,
1984; Li and Oldenburg, 1992; Loke and Barker, 1995; LaBrecque
et al., 1996.
When doing 2D inversion, it is assumed that the properties of
the ground are constant in the third dimension, i.e., the direc-
tion perpendicular to the electrode layout. Deviations from this are
commonly referred to as 3D effects. This means that application of
standard 2D techniques on embankment dams with measurement
layouts along the crest of the dam cannot be used without cau-
Manuscript received by the Editor March 25, 2004; revised manuscript received August 13, 2005; published online May 24, 2006.
1
Lund University, Engineering Geology, Box 118, 221 00 Lund, Sweden. E-mail: pontus.sjodahl@tg.lth.se; torleif.dahlin@tg.lth.se.
2
University of Adelaide, Department of Physics, School of Chemistry & Physics, South Australia 5005, Australis. E-mail: bing.zhou@adelaide.edu.au.
© 2006 Society of Exploration Geophysicists. All rights reserved.
GEOPHYSICS, VOL. 71, NO. 3 MAY-JUNE 2006; P. G107–G114, 9 FIGS., 3 TABLES.
10.1190/1.2198217
G107

tion because of the obvious 3D effects from the dam geometry. It is
possible to use 3D inversion techniques Park and Van, 1991;
Sasaki, 1994; Zhang et al., 1995; Loke and Barker, 1996. How-
ever, they still may not be convenient for repeated measurements,
mainly because of limitations in computational resources and be-
cause data sets are 2D if only measured along the crest. Therefore,
a reasonable approach is to use common 2D techniques and then
estimate the distortions and errors that are induced in the process.
Heretofore, the terms 3D effect refer to the errors received when
measuring along an embankment, assuming standard 2D condi-
tions. The most obvious effect is the embankment topography;
however, the most significant effect might come from the variation
in electrical properties of the construction materials in the zoned
embankment dam.
The aim of this study was to improve current, longterm monitor-
ing routines on two embankment dams in the north of Sweden. The
study covered several situations and scenarios essential for inter-
preting and evaluating data from resistivity measurements on em-
bankment dams. Investigations of these different situations were
carried out through numerical calculations. The influence of the
specific dam geometry and zoned construction materials was in-
vestigated via dedicated, 2.5D software. Effects of reservoir water
level and natural, seasonal resistivity variation in the water were
examined as well. Moreover, a comparison was carried out to de-
termine the differences in the efficiency in detecting seepage zones
for four different electrode arrays.
Much work has been done on resistivity forward modeling in 2D
and 3D using the finite-difference method Mufti, 1976; Dey and
Morrison, 1979a, b; Fox et al., 1980 and the finite-element method
Pridmore et al., 1981; Queralt et al., 1991; Sasaki, 1994; Zhou and
Greenhalgh, 2001. Investigative resistivity surveys on embank-
ments to detect structural defects or anomalous seepage are fairly
widespread Abuzeid, 1994; Engelbert et al., 1997; Titov et al.,
2000; Van Tuyen et al., 2000; Buselli and Lu, 2001; Panthulu et al.,
2001; Voronkov et al., 2004. However, modeling studies to find
out more about typical effects from dam geometries is less com-
mon.
If 3D modeling were to be used for our study, large and compu-
tationally heavy models would have been needed to assess the 3D
effects without influence from the finite length of the model.
Therefore, software capable of handling typical dam geometries
was developed for the numerical calculations. This software is a
useful tool for optimizing the monitoring program design and to
improve the interpretation of collected data. It uses forward model-
ing to find the apparent resistivity distribution in earth embank-
ment dams for a given geometry and measurement layout. Addi-
tionally, it is general and may be utilized for many types of
elongated structures, as long as they can be described with an arbi-
trary although constant geometry in the plane perpendicular to
the electrode layout direction.
NUMERICAL MODELING
Software description
Software written for 2D resistivity/IP modeling was modified to
simulate a dam-monitoring survey by allowing dam geometries in
the 2D-model parameterization and a 3D measurement, which
means that the current injection and potential pickup may be at any
point in the dam. The original 2D software was written for 2D-
resistivity tomography and used the common practical situation,
where resistivity tomographic-imaging surveying is conducted in
the plane perpendicular to the strike direction, allowing arbitrary
variation of resistivity in that plane.
More precisely, the modification of the software was done in two
parts. The first considered adjustments of the elements to fit best
the outline and the inner structure of the dam Figure 1, which was
done by applying the finite-element method Zhou, 1998; Zhou
and Greenhalgh, 1999. The second part regarded the calculation
of the potentials parallel to the strike direction. This was accom-
plished by performing the inverse, Fourier-cosine transform with
nonzero y-coordinate of the potential position, according to the
method described by Queralt et al. 1991.
Hence, the modified software is applicable for modeling of the
resistivity structure with surface profile or crosshole survey. How-
ever, because the current electrodes and the potential measure-
ments must be modeled in 3D for the dam survey, we refer to it as
2.5D modeling. Assumed resistivities must be constant in the
electrode-layout direction, i.e., along the dam, and variable in the
dam cross section, whereas the electrodes can be placed anywhere
in all three dimensions. Such 2.5D modeling is simply accom-
plished by involving the inverse Fourier transform for an electrode
array parallel to the strike direction Dey and Morrison, 1979a, b;
Queralt et al., 1991. The approach is more efficient than a full 3D
model, and for an elongated embankment with constant cross sec-
tion, the drawbacks are moderate. Hence, it is an efficient tool for
assessing 3D effects on 1D and 2D resistivity surveying.
The software uses the finite-element method because this
method makes it easier to deal with the dam geometry, compared to
the finite-difference method. It is valid for calculating potential,
apparent resistivity, or IP responses for a model with arbitrary re-
sistivity distribution in the plane perpendicular to the electrode-
layout direction and for any electrode configurations, e.g., surface,
crosshole, or mise-a-la-masse, off-line and in-line measurements
with pole-pole, pole-dipole, dipole-dipole, Schlumberger, and
mixed arrays Zhou and Greenhalgh, 1999.
The accuracy of 2.5D modeling has been checked by comparing
it with some known analytic solutions Zhou, 1998. It has been
shown that the modeling accuracy mainly depends on the element
size, electrode spacings that give different ranges of the wave-
number, and the wavenumber sampling for accurate inverse-
Fourier transform. To obtain satisfactory results for the dam mod-
eling, we determined the accuracy-control parameters by applying
the dam geometry and the electrode layouts employed in the fol-
lowing simulations. We compared the results with different ele-
ment sizes and wavenumber sampling schemes. We found that the
results showed relative errors less than 1%, using element sizes of
about 1 m and 40 wavenumber sampling points.
Model geometry, material properties,
and damage types
The dam model is a zoned embankment dam with a central till
core, surrounding filter zones, and support rockfill Figure 1. This
is the most common design of large Swedish embankment dams.
Geometry and design values are given in Table 1. The electrode
layout is buried 1 m into the top of the core at the midpoint of the
cross section.
Because of difficulties in estimating electrical properties of in-
volved materials and lack of appropriate data in literature, some
uncertainties are connected to these parameters. Here, the rockfill
G108 Sjödahl et al.

was treated as an insulated matrix with all electrical conduction
concentrated to the pore spaces. Thus, Archie’s law was used using
porosity estimates. However, the porosity estimates are to some
extent uncertain in themselves. Regarding the core, the matrix can
no longer be considered an insulator, and other material models
must be used. For this study, the core resistivity was estimated
from existing monitoring data from two Swedish dams Johansson
et al., 2000 together with laboratory resistivity measurements of
similar till samples Bergström, 1998 even though an unsatis-
fying variation was found in this data.
The resistivity of the filter zones has less influence on the mod-
eling results and was assumed to be somewhere between the resis-
tivity of the core and the rockfill. The resistivity of the reservoir
water was taken from monitoring data Johansson et al., 2000.
Electrical material properties are listed in Table 2. In an interna-
tional perspective, these values are quite high, mainly because of
the high resistivity of the water. Assuming a porosity of approxi-
mately 25% may lead to resistivities of several thousand ohmme-
ters in the saturated rockfill. Keep in mind that the main factor in-
fluencing the results is the relative differences in resistivities for
the involved materials.
The simulated damages were studied for two different depths
Table 3. They could be physically interpreted as damaged layers,
possibly resulting from less compaction at initial construction and
possibly worsened as a consequence of regional piping causing a
transport of fines from the core to the filter and fill. The damages
were extended along the full length of the dam. Damaged zones of-
ten have this kind of extended shape because the dam is con-
structed in layers. Even though an extension along the full length
of the dam is not realistic, simulating these kinds of scenarios still
yields useful information. Furthermore, because of software re-
strictions, the modeled-dam cross section must be identical along
the whole length of the dam. Therefore, for example, it was impos-
sible to simulate a concentrated, cylindrical, damage zone through
the dam.
A resistivity increase of five times in the core was assumed be-
cause of internal erosion. Experiments on similar tills have shown
that resistivity can increase up to 10 times because of removal of
fines under water-saturated conditions Bergström, 1998. How-
ever, this should be handled with care because internal erosion in-
creases porosity, affecting the resistivity in the opposite direction.
The resistivity of the filter and fill was assumed not to change be-
cause of the simulated damages.
Modeling strategies
To evaluate responses from different electrode arrays, four ar-
rays were selected for all modeling situations. The dipole-dipole,
pole-dipole, Wenner-Schlumberger, and gradient arrays were cho-
sen because they have shown robust imaging quality in prior mod-
eling studies Dahlin and Zhou, 2004. An electrode spacing of
5 m was selected for the dam model because that gives a reason-
able relation between electrode spacing and dam height similar to
what could be expected in an actual in situ situation. All combina-
tions, including a-spacings from one to seven multiples of five
and n-factors one to six, were used for the calculations. The total
was 42 individual measurements for each array. Generally, the four
different arrays demonstrated similar responses for the different
modeled situations. This was particularly true for the pole-dipole,
Wenner-Schlumberger, and gradient, which are all geometrically
associated. Of the four examined arrays, dipole-dipole is by its na-
ture most different from the others, and in some situations, it gave
responses that were different than the others. Thus, only results
from dipole-dipole and Wenner-Schlumberger arrays will be pre-
sented.
Certainly, when investigating constant cross sections, i.e., no lat-
eral changes, the differences in the design of the arrays will not
show up fully in the results. Only when examining special cases,
such as cylindrical damages or elongated damage zones with lim-
Figure 1. The modeled cross section geometry. A zoned, rockfill
embankment dam with a central till core and surrounding filter
zones. Electrode layouts and damage zones that are used in the
study are marked out.
Table 1. Dam geometry design parameters (see also
Figure 1).
Dam height 60 m
Crest width 8 m
Upstream and downstream slopes 0.55:1
Distance: Top of core crest 3 m
Distance: Max reservoir level crest 6 m
Core width at top/bottom 4 m/20 m
Filter thickness outside core/top core 4 m/1 m
Table 2. Electrical material properties.
Material Resistivity
m
Core 300
Filter 2000
Upstream fill 4000
Downstream fill 20 000
Reservoir water 550
Damaged core 1500
Table 3. Damage types.
Damage type
Thickness of
damaged layer
Depth from crest to
center of damaged layer
Type 1: Thin seepage
zone layer
2 m 20 m
Type 2: Thin seepage
zone layer
2 m 50 m
2.5D Resistivity modeling of embankment dams G109

ited length, can a full verification of the performance of the differ-
ent arrays be obtained.
RESULTS
3D effects
The 3D effects and their dependency on material parameters
were examined for a dam with the model cross section described in
Figure 1. The effects were estimated by comparing the responses
from two models: a 2.5D model and a 1D model with the proper-
ties of the model midsection, i.e., the section with the electrode
layout extended to horizontal layers. The 2.5D model generated
three to seven times higher responses than the 1D model. Sam-
ple results for the dipole-dipole and the Schlumberger arrays are
shown in Figure 2.
Next, the dependency of input-material parameters was simi-
larly evaluated using a model with constant resistivity for the
whole dam cross section, including the reservoir water. The result-
ing effect, caused by the topography for a homogeneous embank-
ment, gave an increase in resistivity of about 30% 1.30 times for
the 2.5D model Figure 3. It is obvious that most of the huge 3D
effect arises from the contrast between the relatively conductive
core and the high resistivity of the main part of the dam cross sec-
tion. Most of the current flow is concentrated in the core that geo-
metrically constitutes a rather thin sheet Figure 4.
Reservoir-level fluctuations
The effect of lowering the reservoir was examined, using the
dam model in Figure 1. This was done because the reservoir water
Figure 2. 3D effects estimated as relation between 1D and 2.5D models with assumed material properties for the modeled cross section and
reservoir. a Dipole-dipole and b Wenner-Schlumberger arrays with a-spacing of 5–35 m in steps of 5 m and n-factors 1-6. For both ar-
rays, a-spacing is the spacing between potential electrodes, and n-factor is the shortest distance between potential and current electrode di-
vided by the a-spacing.
Figure 3. Purely geometrical 3D effects estimated as relation between 1D and 2.5D models with equal material properties in the whole cross
section and reservoir. a Dipole-dipole and b Wenner-Schlumberger arrays with a-spacing of 5–35 m in steps of 5 m and n-factors 1-6.
G110 Sjödahl et al.

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Cites background from "2.5D resistivity modeling of embank..."

  • ...…studies of resistivity distribution on embankment geometries have shown that 3D effects are significant and that, for typical Swedish designs, the actual measurements with layouts along the dam crest may give readings several times higher than the resistivity of the core (Sjödahl et al., 2006)....

    [...]

  • ...The explanation of this depth distortion is likely to originate from geometrical effects when inverting two-dimensional resistivity data over an embankment geometry (Sjödahl et al., 2006)....

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  • ...Less consideration is given to absolute values as modelling studies of resistivity distribution on embankment geometries have shown that 3D effects are significant and that, for typical Swedish designs, the actual measurements with layouts along the dam crest may give readings several times higher than the resistivity of the core (Sjödahl et al., 2006)....

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Journal ArticleDOI
TL;DR: Crossline resistivity tomography was developed to find out anomalous seepage pathways in an embankment dam as mentioned in this paper, which yields relatively accurate geoelectric structure of the dam when applied to synthetic data.
Abstract: Crossline resistivity tomography was developed to find out anomalous seepage pathways in an embankment dam. By applying crossline tomography to the investigation of embankment dams, leakage pathways can be effectively located because the crossline tomogram presents resistivity distribution in the horizontal plane of an embankment dam. To test the effectiveness of crossline tomography, we applied it to data from an experiment designed to delineate anomalous seepage pathways in the embankment dam. The method yields relatively accurate geoelectric structure of the dam when applied to synthetic data. In the crossline resistivity tomogram, abrupt discontinuities of a low resistivity band corresponding to the core of the dam can be interpreted as leakage pathways. Application to real data obtained from an embankment dam in Korea yields the result which accurately depicts two anomalous seepage pathways. The identified pathways were consistent with low resistivity zones in the dipole-dipole resistivity section obtained on the crest of the dam. One pathway was confirmed by visual inspection of the dam, and afterward, by trenching.

87 citations

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A. Bolève1, André Revil, F. Janod1, J. L. Mattiuzzo, J.-J. Fry 
TL;DR: In this paper, the authors invert self-potential data in order to locate anomalous water flow pathways in dams and embankments and to estimate the seepage velocity.
Abstract: We invert self-potential data in order to locate anomalous water flow pathways in dams and embankments and to estimate the seepage velocity. The inversion of the self-potential data is performed using the modified singular value decomposition for the inverse problem using a linear formulation of the forward problem. The kernel is solved numerically accounting for the topography of the system and the resistivity distribution, which is independently obtained through electrical resistance tomography. A prior constraint based on finite element modelling of ground water flow can also be used to provide a prior source current density model if needed. This self-potential tomography approach is first validated with a synthetic case study showing how the position of a preferential fluid flow pathway can be retrieved from self-potential and resistivity data and how the seepage velocity can be obtained inside one order of magnitude. This methodology is then applied to a test site corresponding to a portion of an embankment dam along the Rhone River in France. Two self-potential maps (with 1169 and 2076 measurements, respectively) and four resistivity tomograms are used to locate a leak. One self-potential profile and one resistivity profile are used together to perform the 2D inversion of the self-potential data to locate the anomalous leakage at depth and to estimate the flow rate. The depth at which the preferential fluid flow pathway is located, according to self-potential tomography, agrees with an independent geotechnical test using the Permeafor. This demonstrates the usefulness of this methodology to detect preferential water channels inside the body of a dam.

82 citations

Journal ArticleDOI
TL;DR: In this article, a 3D electrical resistivity (3D ERT) was used to identify the steepest gradient in first-derivative resistivity profiles, which yields an estimate of bedrock depth (verified by drilling) to a precision better than 0.2m.

79 citations


Cites background from "2.5D resistivity modeling of embank..."

  • ...However, for heterogeneous subsurface conditions, the two-dimensional (2D) assumption is violated because of the influence of 3D features in close proximity to the survey lines, which can cause significant inaccuracies in the resulting 2D resistivity models (Chambers et al., 2002; Sjodahl et al., 2006)....

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  • ...…for heterogeneous subsurface conditions, the two-dimensional (2D) assumption is violated because of the influence of 3D features in close proximity to the survey lines, which can cause significant inaccuracies in the resulting 2D resistivity models (Chambers et al., 2002; Sjodahl et al., 2006)....

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References
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Journal ArticleDOI
TL;DR: In this paper, a finite-element method is used to solve the differential equations which describe electrical and electromagnetic (EM) field behavior, and the results from the resistivity algorithm show the adverse effect of an irregular, conducting, and polarizable overburden on dipole-dipole, induced polarization surveys.
Abstract: The finite-element method can be used to solve the differential equations which describe electrical and electromagnetic (EM) field behavior. The equations are, respectively, Poisson's equation and the vector, damped wave equation. The finite-element equations are derived, in both cases, using the minimum theorem. While both tetrahedral and hexahedral elements may be used for the modeling of the resistivity problem, only hexahedral elements give satisfactory results for the EM problem. A disadvantage of the relatively simple mesh design used in the approach described here is the presence of long thin elements. Such elements have very poor interpolating properties, and they adversely affect the rate of convergence of the overrelaxation technique used in solving the resulting system of linear equations.For the modeling of resistivity data over an earth with one plane of symmetry, the system of equations typically has about 9000 unknowns. About 50,000 unknowns are needed to give a satisfactory solution to an EM problem where the earth has one plane of symmetry. The advantage of solving these problems with a technique such as the finite-element method is that earths with an almost arbitrary distribution of conductivity can be modeled. On the other hand, an integral-equation method can be far more cost effective for small inhomogeneities. The results from the resistivity algorithm show the adverse effect of an irregular, conducting, and polarizable overburden on dipole-dipole, induced polarization surveys. Modeling of a horizontal loop EM survey illustrates the importance of assessing the host rock conductivity before attempting to interpret inhomogeneity responses.

206 citations


"2.5D resistivity modeling of embank..." refers methods in this paper

  • ...Much work has been done on resistivity forward modeling in 2D nd 3D using the finite-difference method Mufti, 1976; Dey and orrison, 1979a, b; Fox et al., 1980 and the finite-element method Pridmore et al., 1981; Queralt et al., 1991; Sasaki, 1994; Zhou and reenhalgh, 2001 ....

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Journal ArticleDOI
TL;DR: In this paper, the authors used electrical resistivity method to delineate zones favorable for seepage, whereas, self-potential (SP) method was used to determine the path of seepages.

205 citations

Journal ArticleDOI
TL;DR: In this paper, the authors investigated the properties and effects of these two kinds of error on 2D resistivity imaging or inversion for practical applications and quantitatively estimated the off-line and in-line electrode spacing errors.
Abstract: Electrode spacing errors and errors correlated with the magnitude of the observed potential are two key factors that affect the data quality for DC resistivity imaging measurements. This paper investigates the properties and effects of these two kinds of error on 2D resistivity imaging or inversion for practical applications. By analytic analysis and numerical simulations, the off-line and in-line electrode spacing errors were quantitatively estimated for all common electrode arrays (pole-pole, pole-dipole, pole-bipole, Wenner, Schlumberger, dipole-dipole, γ-array, Wenner-β) in 2D resistivity imaging surveys. Meanwhile, the spreading patterns of the spacing errors in the pseudosection and the possible artefacts in the imaging (inverted model) are evaluated. We show that the magnitude of the spacing errors are quite different with these arrays, being largest for dipole-dipole, Wenner-β and γ-array surveys, for which a 10% in-line spacing error may cause twice as large an error (>20%) in the observed resistance or apparent resistivity, which in turn will produce some artefacts in the inverted model. The observed potential errors obtained with the reciprocity principle and collected from different sites and with different electrode arrays, were analysed to show the properties of the potential error caused by many aspects in the field. Using logarithmic plots and error pseudosections, we found that with different electrode arrays and at different sites the potential errors demonstrate a general property, which may be regarded as a negative-power function of potential reading. Power net transients, background telluric variation and instrument malfunction are possible sources that may cause the large errors present as outliers deviating from this function. We reaffirm the fact that the outliers are often correlated with high contact resistances for some of the electrodes used in a measurement, but this may also be caused by an unsatisfactory connection between the electrode and the cable due to, for example, dirt or oxide on the connectors. These outliers are often the main part of the errors affecting the imaging results. Furthermore, a robust inversion and a smoothness-constrained inversion were applied to the investigation of the effects of the measurement errors. Using two real data sets, we show that the smoothness-constrained least-squares inversion is much more sensitive to the potential errors than the robust inversion, but the two inversion schemes produce very similar models with a high data quality. Artefacts or indefinite parts in the inverted models correlate with the distribution zones of the outliers in the potential error pseudosection.

186 citations

Journal ArticleDOI
TL;DR: In this paper, a nonlinear inversion technique is proposed to estimate the resistivities of cells in a 2D model of predetermined geometry, based on dipole-dipole resistivity data.
Abstract: Resistivity data on a profile often must be interpreted in terms of a complex two‐dimensional (2-D) model. However, trial‐and‐error modeling for such a case can be very difficult and frustrating. To make interpretation easier and more objective, we have developed a nonlinear inversion technique that estimates the resistivities of cells in a 2-D model of predetermined geometry, based on dipole‐dipole resistivity data. Our numerical solution for the forward problem is based on the transmission‐surface analogy. The partial derivatives of apparent resistivity with respect to model resistivities are equal to a simple function of the currents excited in the transmission surface by transmitters placed at receiver and transmitter sites. Thus, for the dipole‐dipole array the inversion requires only one forward problem per iteration. We use the Box‐Kanemasu method to stabilize the parameter step at each iteration. We have tested our inversion technique on synthetic and field data. In both cases, convergence is rapi...

167 citations

Journal ArticleDOI
TL;DR: In this article, the authors made a systematic study of dipole-dipole apparent resistivity anomalies due to topography and of the effect of irregular terrain on induced polarization (IP) anomalies, using a two-dimensional (2-D), finite-element computer program.
Abstract: We have made a systematic study of dipole‐dipole apparent resistivity anomalies due to topography and of the effect of irregular terrain on induced‐polarization (IP) anomalies, using a two‐dimensional (2-D), finite‐element computer program. A valley produces a central apparent resistivity low in the resistivity pseudosection, flanked by zones of higher apparent resistivity. A ridge produces just the opposite anomaly pattern—a central high flanked by lows. A slope generates an apparent resistivity low at its base and a high at its top. Topographic effects are important for slope angles of 10 degrees or more and for slope lengths of one dipole‐length or greater. The IP response of a homogeneous earth is not affected by topography. However, irregular terrain does affect the observed IP response of a polarizable body due to variations in the distance between the electrodes and the body. These terrain‐induced anomalies can lead to erroneous interpretations unless topography is included in numerical modeling. A...

139 citations

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Q1. What contributions have the authors mentioned in the paper ".5d resistivity modeling of embankment dams to assess nfluence from geometry and material properties" ?

This study is part of a project to improve current longterm monitoring routines and data interpretation and increasing the understanding when interpreting existing data. The study evaluates the influence from 3D effects created by specific dam geometry and effects of water level fluctuations in the reservoir.