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215
Nigerian Research Journal of Engineering and Environmental Sciences 2(1) 2017 pp. 215-231
Original Research Article
2D and 3D ELECTRICAL RESISTIVITY TOMOGRAPHY (ERT)
INVESTIGATION OF MINERAL DEPOSITS IN AMAHOR, EDO
STATE, NIGERIA
*1Alile, O.M., 1Aigbogun C.O., 2Enoma, N., 3Abraham, E.M. and 1Ighodalo, J.E.
1Department of Physics, Faculty of Physical Sciences, University of Benin, Benin City, Edo State, Nigeria 2Department of Physics, Usen Polytechnic, Usen, Edo State, Nigeria. 3Department of Geophysics, Federal University Ndufu Alike Ikwo, Abakaliki, Ebonyi State, Nigeria. *monday.alile@uniben.edu
ARTICLE INFORMATION ABSTRACT
Article history:
Received 08 May 2017
Revised 11 May 2017
Accepted 12 May 2017
Available online 01 June 2017
A three – dimensional (3D) geoelectrical resistivity imaging study
was carried out on different locations (Eguare primary school field
and Amahor Secondary School Field) in Amahor, Edo State, Nigeria
for solid mineral investigations. A series of 2D apparent resistivity
data were generated in parallel and perpendicular directions using
dipole-dipole electrode configuration with electrode separations of
2.5 m and 5 m respectively. The 2D data sets were collated and
inverted separately to produce 2D models for each line. These
models were then collated into 3D data sets and inverted using 3D
inversion codes with smoothness constrain inversion. The images
were presented as horizontal depth slices of a block model of both
locations in the parallel and orthogonal directions. The total depth
attained for the first and second locations were 7.66 m and 15.3 m
respectively. Results obtained also showed that the two locations
considered were composed of lateritic soil, sand, sandstone, shale,
limestone, clay, dolomite with resistivity ranging from 259 Ωm to
2159 Ωm for both units electrode spacing. Results from this study
would be useful in furthering mineral exploration in the region.
© 2017 RJEES. All rights reserved.
Keywords:
Geoelectrical
Resistivity
Imaging
Inversion
Minerals
1. INTRODUCTION
Geological structures and spectral distribution of subsurface physical properties are
inherently three-dimensional (3D) in nature. Subsurface rocks are generally made up of a
variety of minerals. In 3D geoelectrical resistivity surveys, electrodes are commonly arranged
in square or rectangular grids with constant electrode spacing in both the x and y directions.
216 O.M. Alile et al. / Nigerian Research Journal of Engineering and Environmental Sciences
2(1) 2017 pp. 215-231
Aigbogun and Egbai (2012) investigated the subsurface geologic parameters of the aquifer
layers at Uhunmwode local government area, Edo State, Nigeria. Their investigation showed
that the study area is composed of 5 - 8 earth layers with various thicknesses in the range 13.7
- 181.6m, depths, in the range, 38.9 - 198.6m and resistivity in the range, 115.0 - 18111.8
Ωm. They observed that most of the curves were the ascending A-type and concluded that
this was an indication of a horizontally stratified homogenous earth. Alile and Abraham
(2015) inverted the 2D apparent resistivity data they collected in Benin City, Edo State, into
3D dataset and subsequently applied the 3D dataset in their geoelectrical resistivity imaging
to determine the effectiveness of using parallel or orthogonal sets of 2D profiles to generate
3D dataset for resistivity imaging. Their result demonstrated that the resolution of the
inverted images can be enhanced by using closely spaced 2D profiles or orthogonal 2D
profiles. Additionally, unrealistic artifacts and spurious features due to 3D effects commonly
associated with 2D inversion images were minimized or completely eliminated in the 3D
inversion images. They concluded that the grid orientation effect could be eliminated by
collating orthogonal 2D profiles to 3D data set.
A major limitation of the 2D geoelectrical resistivity imaging is that measurements made
with large electrode spacing are affected by deeper sections of the subsurface as well as
structures at a larger horizontal distance from the survey line. This is most pronounced when
the survey line is placed near a steep contact with the line parallel to the contact (Loke,
2001). Geological structures and spatial distribution of subsurface physical properties and/or
contaminants often encountered in environmental, hydrogeological and mining engineering
investigations could be three dimensional (3D) in nature. Thus the assumption of the 2D
model of interpretation is commonly violated in such cases. Images resulting from 2D
geoelectrical resistivity surveys would contain spurious features due to the 3D effects. This
usually leads to misinterpretation and/or misrepresentation of the observed anomalies in
terms of magnitude and location. Due to out-of-plane resistivity anomalies and violation of
the 2D assumption the 2D resistivity imaging will produce misleading images (Bentley and
Gharibi, 2004).
In addition, the 2D images produced are only along the survey lines and not the entire
investigation site. Therefore, geometrically complex heterogeneities cannot be adequately
characterized with vertical electrical sounding (VES), profiling or 2D electrical resistivity
imaging. Hence, a 3D geoelectrical resistivity survey with a 3D interpretation, where the
resistivity values are allowed to vary in all the three directions (vertical, lateral and
perpendicular) should in theory give a more accurate and reliable result. 3D interpretation
models are also needed in subtle heterogeneous subsurface investigations associated with
environmental and engineering investigation sites. This research aims to produce 3D
geological slices of the subsurface at Amahor area, Edo State for mineral deposit
investigations using the Electrical Resistivity Tomography (ERT) method. The technique of
collating parallel or orthogonal 2D profiles to build 3D data set has additional advantage of
producing stand alone 2D inversion images which can be very useful in the interpretation of
3D images commonly presented as horizontal depth slices.
217 O.M. Alile et al. / Nigerian Research Journal of Engineering and Environmental Sciences
2(1) 2017 pp. 215-231
2. METHODOLOGY
2.1. Study Area
The survey area is located within longitudes 5° 32' 59" E and 6° 30' 0" E, latitudes 6° 10' 40"
N and 6° 45' 45" N as shown in Figure 1. It has a minimal elevation of 8 m and maximum
elevation of 457m. The area occupies the north-central part of Edo State which is a
sedimentary terrain and is underlain by sedimentary rocks of Paleocene to recent age. The
sedimentary rock contains about 90% of sand stone and shale intercalations (Alile et al.,
2011). Edo State is situated in South-western part of Nigeria. It is an important sedimentary
basin in Nigeria due to her closeness to the oil fields within the Niger-Delta region. The
geological setting consists of the coastal plain sands sometimes referred to as Benin sands of
the Benin Formation in Nigeria. The Benin sands are partly marine, partly deltaic and partly
lagoonal (Ogunsanwo, 1989), all indications of a shallow water environment of deposition.
The formation is made up of top reddish clayey sand capping highly porous fresh water
bearing loose pebbly sands, and sandstone with local thin clays and shale interbeds which are
considered to be of braided stream origin.
The formation is covered with loose brownish sand (quaternary drift) varying in thickness
and is about 800 m thick; almost all of which is water bearing with water level varying from
about 20 m to 52 m (Kogbe, 1989). The coastal plain sands in the study area is bounded by
Alluvium and Mangrove swamps before it, and afterwards by the Bende Ameki Formation
and Imo clay-shale group (Alile and Abraham, 2015).
Figure 1: Location of Amahor community on the sedimentary basin of southern Nigeria (Map modified from
Abraham et al., 2014)
KEY
CRETACEOUS RECENT
SEDIMNTS
PRECAMBRIAN BASEMENT
COMPLEX
AMAHOR (STUDY AREA)NIGERIA
150 0 300KM
NKADUNA
JOS
IBADAN
4O
6O
8O
12O
10O
14 NO
2 EO 4O 6O
8O10
O 12O
14O16
O
BENIN CITY
LAGOS
R. BENUE
R. NIGER
LAKE
CHAD
AFRICA
AMAHOR
218 O.M. Alile et al. / Nigerian Research Journal of Engineering and Environmental Sciences
2(1) 2017 pp. 215-231
The first and second survey grids at Eguare primary school (EPS) and Amahor secondary
school (ASS) premises are shown in Tables 1 and 2. These two locations were selected after a
reconnaissance visit to the study area. Figure 2 show the base map for the two locations.
Table 1: Location 1 (Eguare primary school premises)
Point Latitude Longitude Elevation (m)
1 6o 28’14.9” N 6o 12’22.0” E 188
2 6o 28’15.7” N 6o 12’21.6” E 188
3 6o 28’15.5” N 6o 12’22.8” E 187
4 6o 28’16.3” N 6o 12’22.3” E 186
Table 2. Location 2 (Amahor secondary school premises)
Point Latitude Longitude Elevation(m)
1 6o 28’6.5” N 6o 11’51.6” E 188
2 6o 28’4.0” N 6o 11’51.8” E 188
3 6o 28’6.0” N 6o 11’53.5” E 187
4 6o 28’4.4” N 6o 11’51.8” E 186
Figure 2: Amahor location and topographical map (points marked red are locations of the 3d electrical
resistivity tomography survey)
There are two major climatic seasons in Amahor area, the wet and the dry season. The wet
season is characterized by heavy rainfall which occurs from April to October. Annual average
rainfall in this area is over 2000 mm (Okhakhu, 2014). Temperature during the rainy season
is between 20oC – 27oC. The dry season is characterized by intense sunshine, and dry wind.
Temperatures could be as low as 20 in the morning and as high as 31 in the afternoon.
The vegetation of the area is that of the guinea savannah which comprises of various species
of shrubs and high forest plants along the streams and depressions in the area.
2.2. Research Method
Dipole-dipole array is widely used in resistivity/induced polarization (I.P) surveys because of
the low electromagnetic (EM) coupling between the current and potential circuits. The choice
of a particular method is governed by the nature of the terrain and cost considerations (Alile,
219 O.M. Alile et al. / Nigerian Research Journal of Engineering and Environmental Sciences
2(1) 2017 pp. 215-231
2008). The arrangement of the electrodes is shown in (Figure 3). The spacing between the
current electrodes pair, C2 – C1 is given as “a” which is the same as the distance between the
potential electrodes pair P1 – P2. This array has another factor marked as “n”. This is the ratio
of the distance between the C1 and P1 electrodes to the C2 – C1 (or P1 P2) dipole separation
“a”. For surveys with this array, the “a” spacing is initially kept fixed and the “n” factor is
increased from 1 to 2 to 3 until up to about 6 in order to increase the depth of investigation.
Figure 3: Two different arrangements of a dipole-dipole array measurement with the same array length but with
different “a” and “n” factors resulting in very different signal strengths. (Loke, 1999)
The first and second survey grids were laid at Eguare Primary School and Amahor Secondary
School compounds as shown in Figure 4.
Figure 4: 3D electrical resistivity survey grid format used at Amahor secondary school and Eguare primary
school locations
Dipole-dipole electrode array was used (Figure 5) with a 13 x 13 square electrode grids
making a total of 169 electrodes. On the first and second survey area, electrodes were
arranged at a distance, a = 2.5m, factor n, increasing from 1 to 8. Readings were taken on
both grids in X-direction with 13 electrodes and Y-direction with 13 electrodes in succession
in a 2-D format. As measurements progressed, factor a, was kept constant while n increased
from 1 8 to increase the depth of investigation. Measurements were displayed in ohms Ω
0 10 20 30 40 50 60
X(m)
AMAHOR SECONDARY SCHOOL 3D ELECTRICAL IMAGING SURVEY GRID
0
10
20
30
40
50
60
Y(m
)
0 10 20 30 40
Scale
m
LY1
LY2
LY3
LY4
LY5
LY6
LY7
LX1 LX2 LX3
LX4
LX5LX4 LX6 LX7
O A
BC
220 O.M. Alile et al. / Nigerian Research Journal of Engineering and Environmental Sciences
2(1) 2017 pp. 215-231
and milli-ohms mΩ and were converted to resistivity in ohms-meter Ωm by evaluating
with the geometric factor k of the array used.
Figure 5: Dipole-dipole electrode array used for this study and its geometric factor
The 3-D data set consists of a number of parallel 2-D lines in the X and Y directions. The
data from each 2-D survey line was initially inverted independently to give 2-D cross-
sections. Finally the whole data set was combined into a 3-D data set and inverted using RES
3D INV software to produce a 3-D picture. The inversion routine used was based on the
smoothness constrained least squares method (DeGroot-Hedlin and Constable, 1990; Sasaki,
1992). The optimization method then adjusts the resistivity of the model blocks and tries to
reduce the difference between the measured and calculated apparent resistivity values using
iterative procedure.
3. RESULTS AND DISCUSSION
Figures 6 and 7 show outputs from Eguare and Amahor lines 2D smoothness constrained
inversion model resistivity sections of this study.
Figure 6(a): Eguare line Lx1
Figure 6 (b): Eguare line Lx2
Figure 6 (c): Eguare line Lx3
Figure 6 (d): Eguare line Lx4
221 O.M. Alile et al. / Nigerian Research Journal of Engineering and Environmental Sciences
2(1) 2017 pp. 215-231
Figure 6 (e): Eguare line Lx5
Figure 6 (f): Eguare line Lx6
Figure 6 (g): Eguare line Lx7
Figure 6 (h): Eguare line Ly1
Figure 6 (i): Eguare line Ly2 Figure 6 (j): Eguare line Ly3
Figure 6 (k): Eguare line Ly4 Figure 6 (l): Eguare line Ly5
222 O.M. Alile et al. / Nigerian Research Journal of Engineering and Environmental Sciences
2(1) 2017 pp. 215-231
Figure 6 (m): Eguare line Ly6 Figure 6 (n): Eguare line Ly7
Figure 6: Eguare lines of 2D smoothness constrained inversion model resistivity sections. Lines Lx and Ly are
displayed for all subscripts of x and y
Figure 7 (a): Amahor line Lx1 Figure 7 (b): Amahor line Lx2
Figure 7 (c): Amahor line Lx3 Figure 7 (d): Amahor line Lx4
Figure 7 (e): Amahor line Lx5 Figure 7 (f): Amahor line Lx6
223 O.M. Alile et al. / Nigerian Research Journal of Engineering and Environmental Sciences
2(1) 2017 pp. 215-231
Figure 7(g): Amahor line Lx7 Figure 7 (h): Amahor line Ly1
Figure 7 (i): Amahor line Ly2 Figure 7 (j): Amahor line Ly3
Figure 7(k): Amahor line Ly4 Figure 7 (l): Amahor line Ly5
Figure 7 (m). Amahor line Ly6 Figure 7 (n): Amahor line Ly7
Figure 7: Amahor lines of 2D smoothness constrained inversion model resistivity sections. Lines Lx and Ly are
displayed for all subscripts of x and y
224 O.M. Alile et al. / Nigerian Research Journal of Engineering and Environmental Sciences
2(1) 2017 pp. 215-231
The 3D inverse models obtained from the inversion of 2D data sets collated from the parallel
2D profiles in x and y directions that is, in-line and cross-line profiles for both survey grids
are presented as horizontal depth slices (Figures 8 and 9) for smoothness constrained
inversion models. The smoothness constrained inversion method produce smoother model
than the robust constrained method. The collated 3D data sets were inverted according to the
method of Li and Oldenburg (1994) and (White et al., 2001). The Pole-Pole array commonly
used for the square or rectangular grid method has limitation of finding suitable locations for
the two electrodes at infinity. Figures 8 (a) and (b), show that the geoelectric layers are
divided into six with a total depth of 7.66m. The detail of the interpretation at EPS can be
seen on Table 3. The first, second, third, fourth, fifth and sixth layers have thicknesses of 0.88
m, 1.00 m, 1.16 m, 1.33 m, 1.53 m and 1.76 m respectively. The first, second and third layers
having a lower resistivity range of between 259 - 503 Ωm for unit electrode spacing of 2.5 m
suggests that these layers compose of lateritic soil, sand sandstone, sand clay, limestone, and
shale (Loke, 2001). The fourth, fifth and sixth layer having a higher resistivity range of
between 403-1217 Ωm for the same unit electrode spacing suggests the composition of these
layers to include sand, sandstone, shale, limestone, clay and dolomite.
Table 3: Interpretation table for EPS site
Name of survey site: eguare primary school (eps) premises
Electrode spacing: 2.5 m
Total depth attained: 7.66 m
Layer no In-line(m) Cross-line(m) Resistivity range Interpretation
1 0.88 0.88
259-503 Ωm
Iateritic soil,
Sand,
Sandstone,
Sandclay,
Limestone,
Shale.
2 1.0 1.0
3 1.16 1.16
4 1.33 1.33
503-1217 Ωm
Sand,
Sandstone,
Shale,
Limestone,
Clay,
Dolomite.
5 1.53 1.53
6 1.76 1.76
225 O.M. Alile et al. / Nigerian Research Journal of Engineering and Environmental Sciences
2(1) 2017 pp. 215-231
Figure 8(a): Eguare parallel Lx in-lines horizontal depth slices of smoothness constrained inverse model
Figure 8(b): Eguare Perpendicular Ly cross-line horizontal depth slices of smoothness constrained inverse
model
Horizontal depth slices displayed after the collation of 2D data set in Amahor in-line (x-
direction) and cross-line (y-direction) into 3D data set is shown in Figures 9 (a) and (b) and a
summary explanation on Table 4. It was observed that the geoelectric layers are divided into
six, with total depth range of 15.3 m. The first, second, third, fourth, fifth and sixth layers had
thicknesses of 1.75 m, 2.01 m, 2.32 m, 2.66 m 3.06 m and 3.5 m respectively. The first 3
layers had lower resistivities of 377- 1021 Ωm for a unit electrode spacing of 5.0 m indicating
lateritic soil, sand sandstone, sand clay, limestone, clay, shale compositions. The last 3 layers
226 O.M. Alile et al. / Nigerian Research Journal of Engineering and Environmental Sciences
2(1) 2017 pp. 215-231
had resistivity range of 796 -2159 Ωm from same unit electrode spacing also indicating sand,
sandstone, sand clay, limestone, clay, shale, dolomite composition in the region. Alile and
Abraham (2015) made comparable observations within the Benin Formation, on which parts
of the current study sites also resides. They noted that although the extracted 2D model
images reveal evidence of some features in the investigation site, the 3D resistivity
imaging/inversion was more suitable in this region due to the heterogeneous nature of its
subsurface. It was hypothesized that results obtained in this study should be similar to results
from a multi-channel 3D equipment, if it were to be used on the study area. The survey
technique used in this study allows the use of more flexible arrays such as Dipole-Dipole,
Pole-Dipole and Wenner –Schlumberger, which are not easily adapted into conventional
square or rectangular grid methods for 3D resistivity survey.
Table 4: Interpretation Table for ASS Site
Name of survey site: Amahor secondary school (ass) premises
Electrode spacing: 5.0 m
Total depth attained: 15.3 m
Layer no In-line(m) Cross-line(m) Resistivity range Interpretation
1 1.75 1.75
377-1021 Ωm
Iateritic soil,
Sand,
Sandstone,
Sandclay,
Limestone,
Shale.
2 2.01 2.01
3 2.32 2.32
4 2.66 2.66
796-2159 Ωm
Sand,
Sandstone,
Shale,
Limestone,
Clay,
Dolomite.
5 3.06 3.06
6 3.50 3.50
Figure 9(a): Amahor parallel Lx in-line horizontal depth slices of smoothness constrained inverse model
227 O.M. Alile et al. / Nigerian Research Journal of Engineering and Environmental Sciences
2(1) 2017 pp. 215-231
Figure 9(b): Amahor Perpendicular Ly cross-line horizontal depth slices of smoothness constrained inverse
model
Figure 10: Colour legend explaining Aggregate/Mineral distribution in the subsurface of study area.
Figure 10 explains the subsurface aggregate/mineral distribution in the study area. A
summary presentation of the 2D results from Amahor area is shown in Figures 11 (a) and (b).
Positions depicting high resistivity values could be spotted on the maps (Figure 11 (a)). These
regions with high resistivity are seen clearly on the XY slice view (Figure 11 (b)). The
regions with high resistivity is consistent with earlier inference that these could be pointers to
the existence of dolomite, clay or shale minerals in the region.
228 O.M. Alile et al. / Nigerian Research Journal of Engineering and Environmental Sciences
2(1) 2017 pp. 215-231
Figure 11(a): Amahor Field linear contour interval view
Figure 11(b): Amahor Field XY View
The 3D model isocore depth map from Amahor Field is shown in Figure 12 while Figure 13
presents various subsurface slices of the isocore depth map. Mineral intrusions of equal
resistivity values are identified as possible intrusions in Figure 12. It was deduced from the
resistivity range of the structures (800 – 1200 Ωm), that the structures could represent
dolomite mineral intrusions in the shaly environment. This deduction is also in line with the
geology of the region. It is also possible that given the revealing nature of the high and equal
resistivity structures identified in Figures 12 and 13, some of the structures (especially the
linear structures) could be associated to fractures (Chávez et al., 2014). The Isochore map
could be used to predetermine the drilling depths of wells and locate the mineral structures
buried in the region.
229 O.M. Alile et al. / Nigerian Research Journal of Engineering and Environmental Sciences
2(1) 2017 pp. 215-231
Figure 12: 3 – Dimensional isocores depth map of Amahor field
230 O.M. Alile et al. / Nigerian Research Journal of Engineering and Environmental Sciences
2(1) 2017 pp. 215-231
Figure 13: Subsurface slices of isochors depth and subsurface volume map from Amahor field
4. CONCLUSION
3 – Dimensional geoelectrical resistivity imaging study was successfully carried out at Eguare
primary school and Amahor Secondary School premises, both in Amahor, Edo State, Nigeria,
for solid mineral investigations. The study showed that 3D geoelectrical resistivity survey can
be effectively and efficiently conducted by collating apparent resistivity data from parallel and
orthogonal 2D profiles. The generation of 3D data set by collating orthogonal or parallel set of
2D lines speeds up field procedure and considerably reduced the effort and cost involved in
collecting 3D data set using square or rectangular grid method. The technique of collating
parallel or orthogonal 2D profiles to build 3D data set has an additional advantage of
producing stand alone 2D inversion images which can be very useful in the interpretation of
3D images commonly presented as horizontal depth slices. 3 – Dimensional Isocores depth
and the subsurface volume were realized in the study. Results obtained showed that the two
locations considered were composed of lateritic soil, sand, sandstone, shale, limestone, clay,
dolomite with resistivity ranging from 259 Ωm to 2159 Ωm for both units electrode spacing.
Results from this study would be useful in furthering mineral exploration in the region.
5. ACKNOWLEDGMENT
The authors wish to acknowledge the assistance and contributions of the technical staff during
the field work toward the success of this work. The authors are also grateful to all the
anonymous reviewers and editors whose comments improved the quality of this manuscript
6. CONFLICT OF INTEREST
There is no conflict of interest associated with this work.
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2(1) 2017 pp. 215-231
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