Geoelectric assessment as an aid to geotechnical investigation at a proposed residential development...

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ORIGINAL PAPER

Geoelectric assessment as an aid to geotechnical investigationat a proposed residential development site in Ilubirin, Lagos,

Southwestern Nigeria

L. Adeoti1 & A. O. Ojo1 & R. B. Adegbola2 & O. O. Fasakin1

Received: 18 November 2014 /Accepted: 20 January 2016# Saudi Society for Geosciences 2016

Abstract The study focuses on the application of electrical

resistivity methods as a guide for a detailed geotechnical in-vestigation due to the inhomogeneity of the soil materials cum

inability of the drilling beyond 38 m from the three initially

drilled geotechnical boreholes which did not allow for proper

foundation decisions and thus necessitated the research. Two-

dimensional (2D) electrical resistivity data were acquired

using the Wenner array along ten (10) traverses of about

500 m long, and forty-four (44) vertical electrical sounding

(VES) data were acquired along the various traverses using

the Schlumberger array with a maximum spread of 620 m.

The VES data were interpreted using partial curve matching

technique and one-dimensional (1D) computer iteration using

WinRESIST software. The 2D dataset were processed using

DIPROWin software. The inversion of the 2D resistivity data

was constraint by the VES results and available borehole data.

The results of the interpretation of the electrical resistivity data

reveal that the lithological units underlying the study area

compose of clay/peat, clayey sand, sandy clay, and sand.

The results of the interpretation of the electrical resistivity data

guided by the range of resistivity (ρ) values and knowledge of

the geology of the area reveal that the lithological units under-

lying the study area are composed of peat (ρ < 10 Ωm), clay

(10 > ρ < 100 Ωm), clayey sand (100 > ρ < 200 Ωm), sandy

clay (200 > ρ < 300 Ωm), and sand (ρ > 300 Ωm). The various

layers are intercalated with each other, and thickness values

vary from one location to another up to a maximum depth of

70 m. The VES results show that the clayey material underliesthe sand-filled topsoil and there are indications of competent

sand layers at depth beneath these clayey layers in the study

area. The 2D pseudosections reflect that the different litholog-

ical units are intercalated with varying thicknesses across the

study area. Thus, the study reveals that the subsoil within the

study area is quite inhomogeneous and great care and exper-

tise is required for developing the site. Anonymously low-

resistivity areas delineated along each of the traverses are lo-

cations recommended for targeted geotechnical investigation

prior to construction.

Keywords Geotechnical . Geoelectric . Electrical resistivity .

Wenner . Schlumberger . Lithological . Pseudosections

Introduction

In the last decade, the use of geophysics in civil and environ-

mental engineering has become a promising approach. Before

then, much money has been wasted by covering sites with

regular grids of boreholes and expensive programs of routine

tests rather than targeting the investigation towards anomalous

areas where information is required (McDowell et al. 2002).

Because every geotechnical in situ survey gives discontinuous

one-dimensional (1D) information of the subsurface condi-

tion, the variability of the near-surface ground may complicate

such site investigations and budgetary constraints may also

limit the number of boreholes that will be drilled. Hence, at

an early stage of site investigation, it may be beneficial to

undertake a reconnaissance geophysical survey which can

provide either a 2D or 3D image of the subsurface that can

be used to identify areas of the site which should be investi-

gated by drilling (i.e., those where anomalous results are

* L. Adeoti

[email protected]

1 Department of Geosciences, University of Lagos, Akoka,

Lagos, Nigeria

2 Department of Physics, Lagos State University, Lagos, Nigeria

Arab J Geosci (2016) 9:338

DOI 10.1007/s12517-016-2334-9

http://crossmark.crossref.org/dialog/?doi=10.1007/s12517-016-2334-9&domain=pdf


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obtained) so as to further investigate areas with potentially

dangerous subsurface conditions and make correlation be-

tween boreholes.

Geophysics is non-destructive, and it often serves as a re-

liable and cost-effective means of imaging the subsurface be-

tween and below boreholes and for determining the in situ

bulk properties of soil and rock (Neil et al. 2008). The use of

geophysical methods confers advantages as they generally

speed up the process of investigation. They provide continu-

ous streams of information not otherwise available in discrete

sampling or invasive procedures and give advance informa-

tion on what to expect for a given locality. This information

can be used to guide a more detailed soil exploration, thereby

offering considerable savings in both time and money. The

application of geophysical investigations can enhance the re-

liability and speed of geotechnical investigations and reduce

Fig. 1 Geological map of Lagos state showing the study area (modified after Jones and Hockey 1964)

Fig. 2 Geophysical data acquisition map

338 Page 2 of 10 Arab J Geosci (2016) 9:338


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the cost of the investigation as the number of boreholes re-

quired for adequate definition of subsurface conditions can be

greatly reduced if geophysics is used as a basis for selecting

borehole locations in order to optimize the layout of excava-

tions. This will make the borehole data being technically more

representative of ground conditions than they might have been

otherwise.

Several geophysical methods can be applied in engineering

investigation, but the use of the electrical resistivity method

has been favored and successfully applied to solve a wide

variety of engineering problems (Olorunfemi and Meshida

1987; Barker 1997; Adepelumi and Olorunfemi 2000;

Olorunfemi et al. 2004; Soupios et al. 2007; Omoloyole et

al. 2008; Adepelumi et al. 2009; Adeoti et al. 2009; Fatoba

et al. 2010; Ayolabi et al. 2010; Fatoba et al. 2013) particularly

in aiding geotechnical investigation (Akintorinwa and Adelusi

2009; Akintorinwa and Adesoji 2009; Adeyemo and

Omosuyi 2012; Salami et al. 2012). This is because of the

wide range of resistivity values found in nature and the fact

that it is one of the simplest and less costly geophysical

methods available. The method is best suited to the determi-

nation of depths to the bedrock and detecting the presence of

structural features in the bedrock or potentially dangerous

subsurface conditions before the erection of any engineering

structure (Soupios et al. 2007).

Due to urbanization and geometrically increasing popula-

tion in Lagos, Southwestern part of Nigeria, a section of

Ilubirin in Lagos Island Local Government Area was

Fig. 3 Correlation between VES

1, 41, and 42 and boreholes 1, 2,

and 3, respectively

Arab J Geosci (2016) 9:338 Page 3 of 10 338


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reclaimed by sand filling in order to provide further land for

housing projects/development purposes. In this study area,

three randomly geotechnical boreholes were initially drilled

to reveal the nature of the subsurface information, but the in-

homogeneity of the soil materials cum inability to drill beyond

38 m did not allow for proper foundation decisions. Thus,

these limitations informed the application of vertical electrical

sounding (VES) and 2D resistivity survey with a view to properly revealing laterally and vertically the subsurface ge-

ology as a guide for a detailed geotechnical investigation prior

to construction.

Geological setting of the study area

The study area (Ilubirin) located between latitudes 60 27′ 40″

N and 60 27′ 58″ N and longitudes 30 23′ 45″ E and 30 24′ 10″

E lies within Lagos State in the Southwestern part of Nigeria.

The state overlies the Dahomey Basin, which extends almost

from Accra in Ghana through the Republic of Togo and Beninto Nigeria where it is separated from the Niger Delta basin by

the Okitipupa Rigde at the Benin hinge flank. According to

Jones and Hockey (1964), the geology of Southwestern

Nigeria reveals a sedimentary basin which is classified under

five major formations according to their geological formation

age, namely the Littoral and the Lagoon deposits, Coastal

Plain sands, the Ilaro Formation, the Ewekoro Formation,

and the Abeokuta formation overlying the crystalline base-

ment complex with their ages ranging from Recent to

Cretaceous (Fig. 1).

As part of the Nigerian sector of the Benin Basin, the

Quaternary geology of the study area comprises the Benin

Formation (Miocene to Recent), recent littoral alluvium, and

lagoon/coastal plain sand deposits (Pugh 1954; Durotoye

1975; Longe et al. 1987; Jones and Hockey 1964). The allu-

vial deposits consist mainly of sands (Jones 1960; Halstead

1971), littoral and, lagoon sediments formed between two

barrier beaches (Adeyemi 1972) and coastal plain sands.

Topographically, the land on the northern fringe of the state

has soils that do not rise very much above sea level.

Material and methods

The electrical resistivity method adopted for the geophysical

survey uses artificial source of current ( I ) introduced into the

ground through a set of metallic rods referred to as the current

electrodes while a measurement of the potentials generated

was made using another set of metallic rods referred to as

the potential electrodes. The PASI-16GL resistivity meter

was used to measure the potential difference (ΔV) from which

the resistance ( R) is computed ( R = ΔV/ I ) and converted into

apparent resistivity (ρa ) (Geometric factor * Resistance). The

true resistivity of the subsurface was subsequently estimated

by inversion using a computer program. For the purpose of

this research, the Schlumberger array was used for the acqui-

sition of vertical electrical sounding (VES) because of its com-

parable depth of inve stigation, speed, and convenie nce.

Likewise, the plethora of interpretation material for the

Schlumberger array also makes it attractive for depth sound-

ing. The Wenner array was used for the acquisition of the 2D

resistivity dataset. Wenner array is relatively sensitive to ver-

tical changes in the subsurface resistivity (Loke 2004); there-

fore, it is good in resolving vertical changes (i.e., horizontal

structures) which can effectively help to delineate the lateral

extent of different lithologies in the study area. Compared to

other arrays, the Wenner array has a moderate depth of inves-

tigation and the strongest signal strength which is an important

factor because the survey was carried out in Ilubirin area

which has high background noise. A constant spacing be-

tween adjacent electrodes was used along each profile and

increased to deeper depth.

The data acquisition layout for the survey is shown in Fig.

2, and the orientations of our traverses were roughly perpen-

dicular to NE-SW which is the general strike of geological

features in the study area. This was done to achieve optimum

resolution of the subsurface structures. Ten (10) traverses of

about 500 m along the NW-SE direction were established, and

the 2D resistivity datasets were acquired along these traverses

(a)

(b)

Fig. 4 Typical VES curves in the study area: a KQH-type curve, b QH-

type curve



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in two segments of 0 – 250 m and 250 – 500 m. In addition, a

total of forty-four (44) VES points were occupied along the

ten traverses. Three of the VES data were acquired beside

three boreholes located within the study area as shown in

Fig. 2. The spread length of the Schlumberger current elec-

trode varied from 2 to 620 m while for Wenner profiling, the

Table 1 VES interpretation results and lithological description

VES no. Type curve Resistivity (ρ1….ρn)Ωm//thickness (h1…..hn)m Lithological description

1 KQ 34.7208.6,27.5,8.8//0.5,2.4,3.3 Clayey topsoil, clayey sand, clay, clay/peat

2 QQH 2603.5150.8,87,6.1207.3//1,9.6,25.5,18.6 Sandy topsoil, sandy clay, clay, clay/peat, sandy clay

3 KH 84.3270.2,16.6152.3//0.7,0.6,21 Clayey topsoil, clayey sand, clay/peat, sandy clay

4 KQH 306.1409.8,89,8.1//0.6,1.7,2.7,9.2 Sandy topsoil, sand, clay, clay/peat, clay

5 QQH 732.6585.1,83.53.8,26.3//0.7,2.8,13.4,14.2 Sandy topsoil, sand, clay, clay/peat, clay

6 QH 1668.1152.5,16.7,98//0.9,2.4,20.8 Sandy topsoil, clayey sand, clay, clay

7 KQH 59.4124.7,12.2,1.4,25//0.6,1.7,6.5,8.2 Clayey topsoil, sandy clay, clay/peat, clay/peat, clay

8 KQH 437.2,1628.2123.8,15.9128.3//0.5,2.1,1.7,54 Sandy topsoil, sand, sandy clay, clay, sandy clay

9 QH 2567.6208.5,37.9258.4//0.8,2.2,21.8 Sandy topsoil, clayey sand, clay, clayey sand

10 QH 2467.8139.5,14.4129.1//0.5,1.5,27.8 Sandy topsoil, sandy clay, clay/peat, sandy clay

11 KHA 375.2740.3,27.4,72.9626.7//0.5,1.9,1.8,44 Sandy topsoil, sand, clay, clay, sand

12 QH 745.4,66.6,12,160.1//0.8,4.3,48 Sandy topsoil, clay, clay/peat, sandy clay

13 QH 3909.2473.1,28.4115.7//0.7,1.8,16.1 Sandy topsoil, sand, clay sandy clay

14 KH 26.7156.9,7.8,1900.6//0.6,1.5,16.4 Clayey topsoil, sandy clay, clay/peat, sand

15 KQH 27.6153,11.9,7224.9//0.4,1.6,2.6,29.2 Clayey topsoil, sandy clay, clay/peat, clay/peat, clayey sand

16 QHK 1217.8152.9,7.5,57.6,7.8//0.6,2.9,10.3,55.3 Sandy topsoil, sandy clay, clay/peat, clay, clay/peat

17 KQH 464,2588.2183,20,441.5//0.3,1.5,6.6,25.7 Sandy topsoil, sand, sandy clay, clay, sand

18 KH 87.7201,14.8168.9//0.4,3,15.1 Clayey topsoil, sandy clay, clay, sandy clay

19 KH 121.4193.8,19.9222.2//0.5,1.6,22.8 Sandy topsoil, clayey sand, clay, clayey sand

20 KQH 38.7143.1,32.1,3.2,47.6//0.5,3.3,14.8,27.6 Clayey topsoil, sandy clay, clay, clay/peat, clay

21 QQ 2987.8428.7,34.3,13.6//0.9,1.5,4.2 Sandy topsoil, sand, clay, clay

22 KQH 2341.6,2544.1,92.9,32.8252.9//0.6,0.8,7.4,42 Sandy topsoil, sand, clay, clay, clayey sand

23 QQH 2065.1463,64.1,46.9611.3//0.8,1.2,3.5,68.8 Sandy topsoil, sand, clay, clay, sand

24 QQH 1137.3157.4,36.6,14.2207.7//1,2.9,3.7,57 Sandy topsoil, sandy clay, clay, clay, clayey sand

25 KQ 276.4372.8155.6,13.6//0.5,3.4,36.8 Sandy topsoil, sand, sandy clay, clay

26 KHK 257.3319.4,14.2418.8,45.6//0.6,2.4,2.9,37.5 Sandy topsoil, sand, clay, sand, clay

27 KQQ 319.6896.6,36,35.1878.6//0.5,1.3,0.4,71.7 Sandy topsoil, sand, clay, clay, sand

28 QH 1760.8792.9187.5696.5//0.8,2.2,18 Sandy topsoil, sand, sandy clay, sand29 QHK 1226.1563.3,37.9423.8,23.4//0.8,2.1,8.7,22.6 Sandy topsoil, sand, clay, sand, clay

30 QHK 8439.9390.6,41.3300.8,66.3//0.6,2.7,2.4,75.4 Sandy topsoil, sand, clay, sand, clay

31 QQH 3445.5305.2,40.2,5,54.2//1.2,2.2,7.2,10.9 Sandy topsoil, sand, clay, clay/peat, clay

32 KQH 635.7,1750.2,44.1,10.7136.2//0.5,1.8,11,57.4 Sandy topsoil, sand, clay, clay/peat, sandy clay

33 QH 3247.9201.7,29.5270//0.8,3.1,42.5 Sandy topsoil, clayey sand, clay, clayey sand

34 QH 3592.7675.3,34.7397.5//0.6,1.8,36.1 Sandy topsoil, sand, clay, sand

35 QH 559.6170.7,41.2,4080//0.9,4,65.9 Sandy topsoil, sandy clay, clay, sand

36 QQH 1210.8758.7,53,4.8,61.1//0.6,3.3,13.2,16.5 Sandy topsoil, sand, clay, clay/peat, clay

37 QHA 5350.5,1496.4,99.6110.1841.8//0.8,2,1,67.7 Sandy topsoil, sand, clay, sandy clay, sand

38 QHA 8405.3499.7,37.2273,80.4//0.7,2.2,3104.4 Sandy topsoil, sand, clay, clayey sand, clay

39 KQH 711,2295.8163.2,12.3177.8//0.4,1.8,5.5,11.8 Sandy topsoil, sand, sandy clay, clay/peat, sandy clay

40 KQQ 776.1,1710.1414.8,38.7,12.4//0.5,1.5,0.5,5.8 Sandy topsoil, sand, sand, clay, clay/peat

41 QHA 374.3129.5,30.6113.4,1550//0.7,2,7.2,49.9 Sandy topsoil, sandy clay, clay, sandy clay, sand

42 K 351.3,1188.1,20.4//0.7,1.8 Sandy topsoil, sand, clay

43 KH 34.6106.9,16.8,1098.5//0.6,3.3,10.2 Clayey topsoil, clay/sandy clay, clay/peat, sand

44 KHA 128.8735.3,14.8,69.1175.6//0.5,0.9,5.9,15 Clayey topsoil, sand, clay/peat, clay, sandy clay



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electrode spacing varied from 10 to 80 m. The Garmin Etrexmodel Global Positioning System (GPS) handset was used to

record geographical coordinates (in degrees) of the VES sta-

tions and the traverse lines.

In order to obtain a good final model, the data must be

of very good quality. As a rule of thumb, prior to inver-

sion, we plotted the resistivity data from the 2-D survey

using the pseudosection contouring method as well as a

profile plot. From the pseudosection plot, we manually

picked out bad apparent resistivity measurements from

the dataset. Such bad measurements stood out as points

with unusually high or low values which might be caused

by some sort of failure during the survey. Since we ac-quired our data manually, we had the privilege of cross-

checking and verifying our readings; therefore, the per-

centage of bad data points is negligible in our case. In

addition, our resistivity meter was usually checked for

possible wire leakages, poor electrode contact, and current

injection issues before taking several measurements which

are averaged to suppress random noise.

The VES curves were interpreted using the conventional

partial curv e matching tech nique (Orella na and Mooney

1966; Bhattacharya and Patra 1968) to obtain an initial

model as input into an inversion procedure using a modified

Marquardt-Levenberg inversion algorithm involving the

WinResist Software (Vander Velpen and Sporry 1993).

The acquired 2D resistivity dataset were inverted to obtain

a 2D image of the subsurface using DIPROfWin software.

The 2.5-D inversion code solves the forward problem of

electrical resistivity using finite difference modeling

(FDM) or finite element modeling (FEM) approximations.

For our study, we used the FDM component of the software

to generate theoretical dataset for several models. In the

inversion step, the theoretical dataset was compared to the

observed resistivity data and an attempt to fit both data wasachieved using a smoothness-constrained least-squares in-

version algorithm and an active constraint balancing (ACB)

to achieve stable results. The ACB method was used to

determine the spatially varying Lagrangian multiplier at

each of the parameterized blocks of the model during the

inversion process to enhance both resolution and stability

(Yi et al. 2003). As the inversion proceeded, the method

aimed to iteratively minimize the difference between the

synthetic and observed resistivity fields by updating the

model until a reasonable fit was achieved. The quality of

the data fit was expressed in terms of the RMS error, and

once the misfit is less than 5 %, the iteration was stoppedand the observed field pseudosection, the computed theo-

retical data pseudosection, and the inverted subsurface 2D

resistivity structure were outputted. As a constraint to the

inversion process, we supplied a priori information in terms

of the number of layers from the VES interpretation results

and available borehole information.

Results and discussion

Correlation between borehole and VES model

For optimum interpretation of geophysical survey data, it is

important that adequate direct control is available; such con-

trol can be provided by boreholes or trial pits. Hence, para-

metric soundings at VES 1, 41, and 44 were carried out beside

three boreholes, which had been dug prior to the geophysical

investigation. This has assisted in correlating the results of

both methods and also to probe deeper where necessary.

This is also to help constrain and aid the interpretation of the

geophysical results. The lithological information of boreholes

Fig. 5 Frequency chart for

different VES-type curves

obtained in the study area.

Borehole data (Fig. 3) in thestudy

area form a basis for interpreting

the 2D resistivity images. The

inverted 2D resistivity structure

beneath traverses one (1) to five

(5) andtraverses six(6 ) toten(10)

are shown (Fig. 6 (1a – 5b) andFig. 7 (6a – 10b)). Segment a of

each traverse covers a lateral

distance of 0 – 250 m while

segment b covers a lateral

distance of 250 – 500 m making

each traverse 500 m long



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1 – 3 in correlation with the results of the parametric VES

sounding is presented (Fig. 3). The results obtained from the

correlation informed the use of different ranges of resistivity

values to classify the different lithology in the study area.

RMS error = 0.060 RMS error = 0.059

RMS error = 0.053 RMS error=0.056

RMS error = 0.062RMS error = 0.057

RMS error = 0.059 RMS error = 0.056

RMS error = 0.052RMS error = 0.054

Fig. 6 2D Resistivity structure beneath traverses 1 – 5. Segment (a) is from 0 to 250 m while segment (b) is from 250 to 500 m



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Fig. 7 2D resistivity structure beneath traverses 6 – 10. Segment (a) is from 0 to 250 m while segment (b) is from 250 to 500 m



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Vertical electrical sounding results

Samples of the resistivity curves are presented (Fig. 4). The

summary of interpreted VES results and lithological descrip-

tion is also presented (Table 1). The resistivity curves obtained

from the survey are the KQ-, QQH-, KH-, KQH-, QH-, KHA-,

QHK-, QQ-, KHK-, KQQ-, QHA-, and K-type curves with

the KQH- and QH types being dominant (Fig. 5). The litho-logical interpretation of the VES subsurface models reveals

that the study area is underlain by topsoil (mostly sandy),

sandy clay/clayey sand, clay/peat, and sand layers.

The dominant-type curve (Fig. 5) shows that resistivity

generally decreases with an increase in depth and later in-

creases. This indicates that beneath the sand-filled topsoil,

there is a strong indication of clayey material and subsequent-

ly a competent sandy material at depth.

For construction purposes in the study area, appropriate

foundation such as piling is recommended since the clayey

material lying beneath the sand-filled layer is inimical to

building construction due to differential settlement resultingfrom poor load-bearing capacity.

2D electrical resistivity imaging results

The inversion of the 2D resistivity data was constraint using the

VES results as shown (Table 1) and discussed in a previous

section. The number of layers, which is an input into the inver-

sion process, was determined from the VES results. Likewise, the

understanding of the relationship between resistivity values and

lithology obtained from the borehole data (Fig. 3) in the study

area formed a basis for interpreting the 2D resistivity images.

The 2D subsurface images obtained from the inversion of the

Wenner resistivity data show both the lateral and vertical varia-

tions in subsurface resistivity across the different traverses. The

2D images reveal four major subsurface lithology which are peat

(generally in blue color band with resistivity values less than

10 Ωm), clay (generally in lime/ light orange/ yellow color band

with resistivity values less than 100Ωm), sandy clay/clayey sand

(generally in deep orange/ red color band with resistivity values

ranging from 101 to 199 Ωm for sandy clay and 200 – 299 Ωm

for clayey sand), and sand (generally in purple color band with

resistivity values greater than 300 Ωm). A description of the

lithology is denoted on the subsurface image obtained across

each traverses as presented (Fig. 6 (1a – 5b) and Fig. 7 (6a – 10b)).

For further geotechnical investigation, boreholes should be

targeted at anomalously low resistivity areas that are generally

in blue/lime color band across the different traverses.

Conclusions

From the results of the geophysical investigation, it can be

concluded that the subsurface lithology underlying the sand-

filled area is generally clayey. However, there are patches of

sand unit along the different traverses at different depths.

Since clayey layers are inimical to the development of engi-

neering structures due to differential settlement resulting from

poor load-bearing capacity, it is recommended that a suitable

foundation such as pilling is constructed.

As a guide to further geotechnical investigation, boreholes

are recommended to be drilled at anomalous areas (areas withvery low resistivity


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Geoelectric assessment as an aid to geotechnical investigation at a proposed residential development...

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