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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. *[email protected]

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.


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


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,


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


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


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


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


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


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


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


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


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.


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.


2(1) 2017 pp. 215-231

Figure 12: 3 – Dimensional isocores depth map of Amahor field


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.


2(1) 2017 pp. 215-231

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