application of geoelectrical resistivity imaging and vlf-em

ORIGINAL PAPER

Application of geoelectrical resistivity imaging and VLF-EMfor subsurface characterization in a sedimentary terrain,Southwestern Nigeria

Ahzegbobor P. Aizebeokhai & Kehinde D. Oyeyemi

Received: 29 January 2014 /Accepted: 19 May 2014# Saudi Society for Geosciences 2014

Abstract Geoelectrical resistivity imaging and very-low fre-quency electromagnetic (VLF-EM) geophysical techniqueswere integrated to characterize the subsurface as part of pre-liminary investigations for groundwater resource assessment,development, and management in a sedimentary terrain,southwestern Nigeria. Six parallel 2D geoelectrical resistivityfield data were collected using Wenner array; the VLF-EMdata were equally collected along the same traverses. In addi-tion, four vertical electrical soundings (VES) were conductedon the site using Schlumberger array to provide layeringinformation. The plots of filtered in-phase and quadraturecomponents of the VLF-EM data as well as their correspond-ing Fraser and Karous-Hjelt pseudo-sections are presented.The observed apparent resistivity data for the 2D traverseswere inverted to produce 2D inverse model resistivity andthen collated to 3D data set, which was inverted to obtain 3Dinverse model resistivity of the subsurface. Iso-resistivity sur-faces for 750, 1,000, and 1,500 m extracted from the 3Dinverse model show the 3D distribution of these resistivities.High-resistivity layer at depth range of 10.216.4 m andthickness ranging from 11.0 to 21.0, which overly the aquiferunit, delineated in the VES and 2D/3D resistivity modelscould not be distinctly discriminated in the Fraser andKarous-Hjelt pseudo-sections of the VLF-EM data. However,some conductive linear anomalies thought to be fissures orjoints, which could serve as the main conduit path for ground-water recharge, were delineated in the Fraser and Karous-Hjeltpseudo sections. Thus, the use of geoelectrical resistivity orVLF-EM technique alone is inadequate to characterize the

subsurface features in the study site; consequently, the inte-gration of 2D and 3D resistivity imaging with VLF-EMtechnique enhanced the degree of reliability of the subsurfacecharacterization in the study site.

Keywords Resistivity imaging . VLF-EM . 3D inversion .

Parallel 2D profiles . Near-surface characterization

Introduction

Geoelectrical resistivity and electromagnetic methods areeffective geophysical techniques that are increasingly be-ing used in addressing a wide variety of mineral explora-tion, hydrogeological, environmental, and geotechnicalproblems by determining the spatial and/or temporal var-iability of subsurface electrical properties (resistivity/con-ductivity and dielectric constant). Two-dimensional (2D)geoelectrical resistivity imaging is often used to charac-terized the subsurface for such applications (e.g., Griffithsand Barker 1993; Dahlin and Loke 1998; Olayinka andYaramanci 1999; Daily and Ramirez 2000; Amidu andOlayinka 2006; Aizebeokhai et al. 2010b; Aizebeokhaiand Singh 2013). However, the spatial distributions ofsubsurface properties are inherently three-dimensional(3D), and the 2D resistivity measurements, usually con-ducted along the survey line, can be affected by structuresat great depths and at larger horizontal distances from thesurvey line. Thus, the inversion of 2D resistivity dataoften yields resistivity images that contain spurious fea-tures resulting from 3D effects as well as the effects ofstructures at great depths or at larger horizontal distancesfrom the survey lines. Consequently, 2D inversion modelscould be misinterpreted or misrepresented in terms ofmagnitude and location of the observed resistivity anom-alies (Bentley and Gharibi 2004; Gharibi and Bentley

A. P. Aizebeokhai (*) :K. D. OyeyemiDepartment of Physics, College of Science and Technology,Covenant University, P. M. B. 1023, Ota, Ogun State, Nigeriae-mail: [email protected]

A. P. Aizebeokhaie-mail: [email protected]

Arab J GeosciDOI 10.1007/s12517-014-1482-z

2005; Aizebeokhai et al. 2009, 2010b). Hence, 3Dgeoelectrical resistivity imaging should give more accu-rate and reliable characterization of geometrically com-plex and subtle heterogeneities subsurface.

3D electrical resistivity imaging technique has a wide rangeof applications; it has been used to study fluid migration in thevadose zone (e.g., Park 1998), delineate contaminant plume,and characterize complex heterogeneity subsurface systems inmineral and groundwater prospecting (e.g., Eso andOldenburg 2006; Aizebeokhai et al. 2010b; Aizebeokhai andSingh 2013). The 3D geoelectrical resistivity imaging allowsfor a better understanding of groundwater systems. Conse-quently, the imaging technique can be used tomonitor ground-water seepage and flow in and around sites of more focusedstudies such as dams, nuclear installations, landfill sites, and

waste disposal sites, which often requires 3D definition of theaquifer geometry and characterization.

Similarly, very-low frequency electromagnetic (VLF-EM)technique is one of the most useful electromagnetic methodsoften used for quick delineation of steeply dipping geologicstructures, which are (or may be) related to mineralization,weathered zone in crystalline basement complex, groundwaterfilled fractures, or faults and buried wastes. VLF-EM systemsmake use of energy of distant powerful radio transmitters inthe frequency range of 1525 kHz that operates in differentcountries. The VLF-EM signals may be broadcast by marineor air navigation systems. The amplitudes of the electromag-netic anomalies are significantly influenced by the conductiv-ity of the near-surface lithology rather than the thickness.Geoelectrical resistivity and VLF-EM can be jointly

Fig. 1 Geological sketch map of Nigeria showing the major geological components: basement, younger granites, and sedimentary basins(after Obaje 2009)

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employed for optimal subsurface characterization (e.g.,Benson et al. 1997; Karlik and Kaya 2001; Sharma andBaranwal 2005; Ofomola et al. 2009; Tijani et al. 2009).

The goal of the present work is to characterize the near-subsurface conditions by integrating geoelectrical resistivityimaging and VLF-EM as part of the preliminary investiga-tions for groundwater resource assessment, development, andmanagement in a sedimentary area (Ota), Southwestern Nige-ria. The survey consists of six parallel 2D traverses of electri-cal resistivity, which were collated and inverted to obtain 3Dinverse model of the subsurface resistivity distribution. The2D resistivity data were integrated with four verticalc electri-cal soundings (VES) which provide one-dimensional (1D)layering information about the subsurface and six traversesof VLF-EM data collected along the same traverses. The plotsof filtered in-phase and quadrature components of the VLF-EM data as well as their corresponding Fraser and Karous-Hjelt pseudo-sections, which discriminate between the con-ductive and resistive subsurface features, are presented. 2Dand 3D inverse resistivity models of the subsurface togetherwith iso-resistivity surfaces for 750, 1,000, and 1,500 mextracted from the 3D inverse model, which shows the vari-ability and distribution of the subsurface resistivity, arepresented.

Geological setting of the study area

The study area (Figs. 1 and 2) is within Covenant Universitycampus, Ota, southwestern Nigeria; it is a sedimentary terrainin the eastern part of the Dahomey Basin. Dahomey basin isan extensive basin that stretches along the continental marginof the Gulf of Guinea from southern Ghana through Togo andBenin Republic on the west side. The basin is separated fromthe Niger Delta in the Eastern section by the Benin Hinge Lineand Okitipupa Ridge and marks the continental extension ofthe chain fracture zone (Wilson and Williams 1979; Onuoha1999). The rocks are generally Late Cretaceous to EarlyTertiary in age (Jones and Hockey 1964; Adegoke 1969;Ogbe 1970; Omatsola and Adegoke 1981; Okosun 1990;Billman 1992; Olabode 2006). The stratigraphy of the basinhas been grouped into six lithostratigraphic formations name-ly, from oldest to youngest, Abeokuta, Ewekoro, Akinbo,Oshosun, Ilaro, and Benin Formations. Some workers havedescribed the Cretaceous Abeokuta Formation as a groupconsisting of Ise, Afowo, and Araromi Formations.

The Cretaceous Abeokuta Formation mainly composed ofpoorly sorted sequence of continental grits and pebbly sandsover the entire basin with occasional siltstones, mudstones,and shale-clay with thin limestone beds due to marine

Ota

Fig. 2 Geological map of the Nigerian part of the Dahomey embayment (modified after Gebhardt et al. 2010)

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transgression. Overlying the Abeokuta Formation is theEwekoro Formation, which is predominantly composed ofshallow marine limestone due to the contamination of themarine transgression. The Ewekoro limestones are Palaeocenein age. Overlying the Ewekoro Formation is the shale-dominated Akinbo Formation of Late Palaeocene to EarlyEocene (Ogbe 1970; Okosun 1990). The Akinbo Formationis overlain by the Oshosun Formation which composed ofEocene shale and then Ilaro Formation, which is predominant-ly a sequence of coarse sandy estuarine, deltaic, and continen-tal beds; the Ilaro Formation displays rapid lateral facieschanges. Overlying the Ilaro Formation is the Benin Forma-tion, which is predominantly coastal plain sands and Tertiaryalluvium deposits.

The study area, which lies between latitude 0640.141N 0640.306N and Longitude 00309.665E00309.735E (Fig. 3) with elevation between 52 and54 m above mean sea level, is generally a gentle slopinglow-lying area in the tropical humid region. Ota area ischaracterized by two major climatic seasons, namely, thedry season spanning from November to March and raining

(or wet) season between April and October. Occasionalrainfalls are often witnessed within the dry season, partic-ularly along the region adjoining the coast. Mean annualrainfall, which forms the major source of groundwaterrecharge in the area, is >2000 mm. The local geology ispredominantly coastal plain sands underlain by a sequenceof coarse sandy estuarine, deltaic, and continental bedslargely characterized by rapid changes in facies.

Methodology

Data acquisition and field procedures

Six parallel 2D geoelectrical resistivity traverses in the south-eastnorthwest direction were conducted in a study site(Fig. 3) within Covenant University campus, Ota, southwest-ern Nigeria. The data were collected manually using Omegaresistivity meter. The 2D traverses, separated from each otherwith interline spacing of 15 m, were 230 m in length. Wennerelectrode configuration with minimum electrode spacing of

VES2

VES1

VES3

VES4

T1T3

T5

1

25

41

9

17

33

E566.09003 E0 E573.09003 E0

N630.4006 N4

N114.4006 N4

N

1 9 : Electrode Positions

: VES Positions

T : Traverse

Fig. 3 Survey plan showing thelocations of VES points and 2D(geoelectrical resistivity andVLF-EM) traverses

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Fig. 4 Sounding curves and geo-electric parameters for a VES 1, bVES 3, and c VES 4

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5.0 m was used for the data measurements, and a data level of8 (maximum electrode spacing of 40.0 m) was achieved ineach of the profiles. This results to a total of 47 electrodepositions in each of the traverses; consequently, 268 data points

were obtained for each traverse. The resistivity meter was set toresistancemode, and the geometric factor was calculated for eachdata level and multiplied by the observed resistance to obtain theapparent resistivity for each data point. Special care was taken to

Table 1 Geoelectric layered parameters from interpretation of VES

Layer VES 1 VES 2 VES 3 VES 4 Lithology

1 Resistivity (m) 418.7 214.5 502.0 234.1 Top soil (unconsolidated clayey sand)Thickness (m) 0.6 0.7 0.8 0.6

Bottom Depth (m) 0.6 0.7 0.8 0.6

2 Resistivity (m) 814.9 231.3 835.0 909.2 Mud/mudstoneThickness (m) 5.4 4.1 3.2 3.3

Bottom depth (m) 6.0 4.8 4.0 3.9

3 Resistivity (m) 156.8 291.2 Lateritic clayThickness (m) 6.1 4.9

Bottom depth (m) 12.1 8.8

4 Resistivity (m) 288.9 571 711.1 Clayey sand (aquitard)Thickness (m) 4.3 6.2 7.2

Bottom depth (m) 16.4 10.2 16.0

5 Resistivity (m) 4,221.5 2,115.4 2,165.0 2,150.2 Mud stone (confining bed)Thickness (m) 11.0 16.5 21.0 18.2

Bottom depth (m) 27.4 21.3 31.2 34.2

6 Resistivity (m) 346.0 981.4 350.0 345.3 Sand (low yielding aquifer)Thickness (m) 11.3 9.3 12.0 11.6

Bottom depth (m) 38.7 30.6 43.2 45.8

7 Resistivity (m) 48.2 49.6 120.0 103.2 Coarse sand (high yielding aquifer)

Italicized data Depth-to-bottom of geo-electric layersallow quick assesment of lateral thickening of the delineated layers

VLF measurement (Real component) TR1 VLF measurements (Imaginarycomponent) TR1

Karous-Hjelt filtering (Real component) TR1 Karous-Hjelt filtering (Imaginarycomponent) TR1

Real component, unnormalised Imaginary component, unnormalised

Distance (m) Distance (m)


a

b

c

d

Fig. 5 VLF-EM Fraser and Karous-Hjelt filtering for traverse 1: a filtered real plot, b filtered real pseudo-section, c filtered quadrature plot, and dfiltered quadrature pseudo-section

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minimize electrode positioning error in the data measurements,as the survey was conductedmanually. A cycle of 4 was used forthe data stacking during the field measurements; the root-mean-squared error in the measurements was generally

associated noise and consequently produce 2D pseudo-sections for the traverses (Pirttijarvi 2004).

Similarly, the observed apparent resistivity data for the 2Dprofiles were processed and inverted using RES2DINV inver-sion code (Loke and Barker 1996). The RES2DINV computerprogram uses a nonlinear optimization technique, which au-tomatically determines 2D resistivity inverse model of thesubsurface for the observed apparent resistivity data(Griffiths and Barker 1993; Loke and Barker 1996). Theprogram subdivides the subsurface into a number of rectan-gular blocks in accordance to the spread of the observed dataas determined by the survey parameters (electrode configura-tion, electrode separations and positions, and data level) used.Least-squares inversion technique with standard least-squaresconstraint, which minimizes the square of the difference be-tween the observed and the computed apparent resistivityvalues, was used to invert the 2D data. The least-squaresequation was solved using the standard GaussNewton tech-nique. Smoothness constraint was applied to the model per-turbation vector only and appropriate damping factors wereselected using trial and error methods.

The observed apparent resistivity data for the six parallel2D traverses were then collated to 3D data set. The 2D datasets were collated on a 3D grid of 476 electrodes with adensity of 1608 data points. The resulting 3D grid corresponds

to a separation of 5 m on the x-axis (traverse direction) and15 m on the y-axis (separation between the 2D traverses).Thus, the inter-line spacing between the 2D traverses is thricethe minimum electrode spacing used for the survey. Theinversion of the 3D data set collated was carried out usingRES3DINV, which automatically determines a 3D inversemodel of resistivity distribution using apparent resistivity dataobtained from a 3D resistivity imaging survey (Li andOldenburg 1994). The inversion process involves consideringthe subsurface layers as number of small rectangular prismswith resistivity values determined such that the differencebetween computed and observed apparent resistivity valuesis minimized. As in RES2DINV, the inversion routine used isbased on the smoothness constrained least-squares method (deGroot-Hedlin and Constable 1990; Sasaki 1992). The pro-gram allows users to adjust the damping factor and the flatnessfilters to suit the data set being inverted.

The smoothness constrained least-squares inversion meth-od implementing the finite element technique was used toinvert the data. Initial damping factor of 0.15 and minimumdamping factor of 0.011 with standard GaussNewton opti-mization technique were used for the 3D data inversion. Aftereach iterating process, the inversion subroutine generally re-duced the damping factor used; a minimum limit (one tenth ofthe value of the initial damping factor used) was set to stabilize

Karous-Hjelt filtering (Real component) TR3 Karous-Hjelt filtering (Imaginary component) TR3

VLF measurement (Real component) TR3 VLF measurement (Imaginary component) TR3




a

b

c

d

Fig. 7 VLF-EM Fraser filtering for traverse 3: a filtered real plot, b filtered real pseudo-section, c filtered quadrature plot, and d filtered quadraturepseudo-section

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the inversion process. The damping factor was increased by afactor of 1.050 for each deeper layer and optimized so as toreduce the number of iterations the inversion code required forconvergence. In order to determine the 3D distribution of themodel resistivity values from the distribution of apparentresistivity values, the subsurface was subdivided into a num-ber of small rectangular blocks. The program default for thefirst layer thickness based on the maximum depth of investi-gation of the array was used, and this was increased by 1.15(115 %) for subsequent layers since the resolution ofgeoelectrical resistivity imaging generally decreases withdepth. Homogeneous earth model was used as the initialmodel for the inversion with four nodes between adjacentelectrodes in the finite element so as to significantly improvethe accuracy of the 3D inversion model. The potential valueswere normalized during the inversion.

Results and discussions

The geo-electrical parameters obtained from the computeriteration of the resistivity soundings are presented inFig. 4 and Table 1. Six to seven geo-electric layers weredelineated from the iterated sounding curves. The geo-

electrical parameters of the layers are largely consistenceamong the sounding curves. Based on the local geolgy ofthe study area and available information from boreholesand hand-dung wells, these layers are characterized as:top soil (uncosolidated clayey sand) with model resistivityrange of 214.5502.0 m and thickness of 0.60.8 m;mud/mudstone unit with model resistivity ranging be-tween 814.9 and 909.2 m and thickness range of 3.35.4 m; lateritic clay unit with model resistivity rangingbetween 156.8 and 291.2 m and thickness range of 4.96.1 m; clayey sand unit with model resistivity rangingfrom 288.9 to 711.1 m and thickness ranging from 4.3to 7.2 m, which is often an aquiclude; a very resistivemudstone unit with model resistivity range of 2,115.44,221.5 m and thickness of 11.021.0 m, which servesas a confining bed to the underlying aquifer unit; uncon-solidated medium to coarse grain sand with resistivityranging between 345.3 and 350.0 m and thickness rang-ing between 11.3 and 12.0 m, which is thought to beaquifer unit; and a low resistivity unit with model resis-tivity ranging from 48.2 to 120.0 m.

Similarly, the plots of filtered in-phase (real) and out-of-phase (quadrature) components of the observed VLF-EM data with their corresponding Fraser and Karous-

VLF measurement (Real component) TR4

Karous-Hjelt filtering (Real component) TR4 Karous-Hjelt filtering (Imaginary component) TR4

VLF measurement (Imaginary component) TR4




a

b

c

d


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Hjelt pseudo-sections are presented in Figs. 5, 6, 7, 8,9, and 10. The interpretation of the VLF-EM plots andpseudo-sections are largely qualitative. The subsurfacelayered information could not be determined from eitherthe plots or the pseudo-sections. The pseudo-section islargely a measure of the subsurface conductivity as afunction of depth and qualitatively discriminates betweenconductive and resistive subsurface features. The visualinspection of the Fraser and Karous-Hjelt pseudo-sections allow the determination of depth to anomalousbodies as well as the width and trend of the anomaly.The varying amplitude of the plots is essentially a mea-sure of the changes in the VLF-EM anomaly of thesubsurface, which indicates the variability of the subsur-face conductivity. The positive peaks (crests) observed inthe filtered real plots correspond to high positive anom-alies in the pseudo-sections; similarly, the negative peaks(troughs) in the filtered real plots correspond to highnegative anomalies observed in the pseudo-sections.High positive anomalies are known to correspond toconductive structures while low negative anomalies rep-resent resistive features. However, it is often difficult toqualitatively discriminate between deep and shallow

sources; this may be largely due to the effect of ground-water saturation at depths (Sharma and Baranwal 2005).Some linear high conductive anomalies that are thoughtto represent fissures or joints are delineated in Figs. 5, 7,8, and 9 with dotted lines. These fissures may be themain conduit paths for groundwater recharge in the studysite. Similar linear anomalous trends of relatively lowconductivity are also observed in the pseudo-sections. The-se low conductivity anomalies are also thought to be frac-tures and fissures which have been filled with materials ofhigh resistivity; hence, they are not effective conduit pathsfor groundwater recharge. Similar trends are observed inthe out-of-phase plots and their corresponding Karous-Hjelt pseudo-sections.

The 2D inverse models of the subsurface resistivitydistribution obtained from the smoothness constrainedinversion are presented in Figs. 11, 12, and 13. The 2Dinverse model resistivity values range from about 3505,500 m, 2002,500 m, 4001,700 m, 4001,750 m, 4201,450 m, and 3201,250 m for tra-verses 16, respectively. Similarly, the 3D inverse resistiv-ity models are presented as horizontal depth slices inFig. 14a. The 3D resistivity inverse model presented, with

Karous-Hjelt filtering (Imaginary component) TR5Karous-Hjelt filtering (Real component) TR5

VLF measurement (Real component) TR5 VLF measurement (Imaginary component) TR5



Distance (m)Distance (m)

a

b

c

d


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model resistivity ranging between 80 and 1,550 m, wasobtained after the sixth iteration with a corresponding root-mean-square error of 7.60 %. 2D resistivity images extract-ed from the 3D resistivity model are presented in Fig. 14b.In addition, iso-resistivity surfaces for 750, 1,000, and1,500 m extracted from the 3D resistivity model arepresented in Fig. 15.

The 2D inverse model resistivity values together with theirthicknessess agree reasonably with the geoelectric model pa-rameters obtained from the soundings. The maximum modelresistivity value observed in traverse 1 appears to be relativelymuch higher than that observed in all other traverses. Thishigh inverse model resistivity value observed in traverse 1(5,500 m) corresponds to that observed in the fith layer ofVES 1 (4,221.5 m), which is also much higher those of thecorresponding layers in the other soundings. From Table 1,this high resistive layer generally thickens from the southwestend towards the northeast of the site with minimum layerthickness of 11.0 m observed in VES 1 and maximum layerthickness of 21.0 m in VES 3. Thus, the variability of theresistivity of this geoelectric unit is attributed to variability inthe degree of compaction.

The inter-line spacing used for the 2D resistivity sur-vey ensures high quality and good resolution 3D inver-sion images. The range of resistivity values for the 3Dinverse model is largely consistence with that observed in

the 2D model sections. This is because the resistivitylayers are laterally continuous, as observed in the resis-tivity soundings, though the resistivity of a unit may varydepending largely on the lithology, degree of compaction,and saturation. However, anomalously low resistivityvalues are observed in the 3D model sections and are attrib-uted to side effect in the 3D models; also, the very highresistivity observed in Traverse 1 and VES 1 has been aver-aged out in the 3D inverse model. The iso-resistivity maps inFig. 15 shows the spatial variability and distribution of the750, 1,000, and 1,500 m resistivity units.

The top soil consists of unconsolidated clayey sandwith relatively low inverse model resistivity value thatrange between 214.5 and 502.0 m and an average thick-ness of about 0.7 m. This clayey sand is underlain by aweakly consolidated and relatively impermeable mud-stone unit with a relatively high inverse model resistivityvalue ranging from about 814.9 to 909.2 m with anaverage thickness of about 4.0 m. Most part of the studyarea and its environment are often flooded for severaldays after rainfall due to the low rate of infiltrationthrough this substratum (Aizebeokhai et al. 2010a). Out-crops of this mudstone are observed in serveral part ofOta and its thickness can be sufficiently greater than thatrevealed by the geoelectric sections in this study. Itsresistivity could also vary widely depending on its degree

Karous-Hjelt filtering (Imaginary component) TR6Karous-Hjelt filtering (Real component) TR6

VLF measurement (Imaginary component) TR6VLF measurement (Real component) TR6




a

b

c

d


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of consolidation, water saturation and other intercalatedmaterials.

Envidence from local pitting and hand-dug-wellsshows that underlying the mudstone unit is a weakly

Fig. 11 Observed pseudo-section, calculated pseudo-section, and 2D inverse resistivity model for a traverse 1 and b traverse 2

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consolidated clay unit which becomes intercalated withsand and unconsolidated carbonates with depth. Thegeoelectric parameters (Fig. 4 and Table 1) and 2D/3D

resistivity images show that the model resistivity of thisclayey unit ranges between 156.8 and 291.2 m and itsthickness ranges from 4.9 6.1 m. The sand and


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carbonate intercalations with depth make the porosity andpermeability of this unit to increase with depth. Thus, thisunit possesses a widely varying resistivity which de-creases with depth. The lower part of this unit is saturatedand often forms aquiclude.

Underlying the clayey unit is a very resistivity layer withmodel resistivity ranging from 2,115.4 m to about4,221.5 m at a depth range of 10.216.4 m and thicknessranging between 11.0 and 21.0m as observed in the soundingsresult (Table 1). This high resistivity unit is observed in the2D inverse models from an average depth of about14 m. The unit overlies unconsolidated sand unit with

model resistivity ranging between 345.3 and 350.0 mand thickness between 11.3 and 12.0 m. In anotherpreliminary study carried out earlier, this unconsolidatedsand unit was thought to be the main aquifer unit andthe overlying resitive unit serves as a confining bed tothe underlying aquifer unit (Aizebeokhai and Oyebanjo2013). The depth to this aquifer unit ranges from about2734 m with an average thickness of about 11.5 m.The depth of investigation covered by the 2D and 3Dresistivity images did not extend to this aquifer unitsince the effective depth of investigation of the 2Dand 3D resistivity images is about 26 m.

Fig. 14 3D inverse model resistivity sections: a horizontal depth slices and b extracted 2D models

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Underlying this aquiferous unit is a relatively conductiveunit with model resistivity ranging from 48.2 to 120.0 m.The thickness of this unit could not be assertained as the depthof investigation of the soundings did not extend beyond thisunit. This relatively conductivie unit was earlier interpreted tobe a clayey/shaley formation in the preliminary investigation(Aizebeokhai and Oyebanjo 2013). However, available evi-dence from boreholes around the study area suggests that thislow resistivity unit is more porous coarse sand and a highyielding aquifer unit. Thus, this unit and the overlying unitdelineated from the geoelectric sections are essentially thesame with porosity increasing with depth possibly due tosorting and grading. Further studies that incorporate the useof other geophysical methods such as induced polarization arerecommended to confirm the lithology and depth of this unit.

The pseudo-depth of investigation of the VLF-EM re-sponses as revealed by the Fraser and Karous-Hjelt pseudo-section is about 35 m. This indicates that the low yieldingaquifer (Table 1) was slightly penetrated by the VLF-EMresponses. Although the underlying high yielding aquiferwas not imaged by the VLF-EM data, its effect can signifi-cantly influence the observed responses. The high resistivityanomaly observed in the 2D and 3D geoelectrical resistivityinverse models are not distinctly discriminated in the Fraser

and Karous-Hjelt pseudo-sections. This may be partly due tothe masking effect of the overlying conductive layers and theeffect of the conductive saturated formations at depths.

Conclusions

Integrated geophysical techniques, comprising of verticalelectrical soundings (VES), 2D and 3D geoelectrical re-sistivity imaging, and VLF-EM methods have been usedfor subsurface characterization within the campus of Cov-enant University, southwestern Nigeria. The interpretationof the VLF-EM data was largely qualitative with highpositive anomalies in the Fraser and Karous-Hjeltpseudo-sections produced representing conductive subsur-face features and low negative anomalies reflecting resis-tive structures. Some linear anomalies interpreted as fis-sures and joints thought to be the main conduit paths forgroundwater recharge are delineated in the VLF-EMFraser and Karous-Hjelt pseudo-sections. The subsurfacelayered media and their average electrical resistivities andthicknesses were obtained from the resistivity soundings.The lateral variability and distribution of the geo-electricalparameters are revealed in the 2D and 3D geoelectrical

Fig. 15 Iso-resistivity surfaces extracted from the 3D inverse model section: a 750 m, b 1,000 m and c 1,500 m surfaces

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resistivity images. The high resistivity layer delineated in thevertical electrical soundings as well as the 2D and 3Dgeoelectrical resistivity imaging could not be discriminated inthe VLF-EM Fraser and Karous-Hjelt pseudo-sections. Hence,the use of VLF-EM technique alone was not sufficient tocharacterize the subsurface features in the study site. The 2Dand 3D geoelectrical resistivity images enhanced the degree ofreliability of the subsurface characterization. Consequently,VLF-EM survey is only recommended for reconnaissancestudies in such geological environment and should be integrat-ed with other geophysical techniques for detail studies.

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Arab J Geosci

Application...AbstractIntroductionGeological setting of the study areaMethodologyData acquisition and field proceduresData processing and inversion

Results and discussionsConclusionsReferences

application of geoelectrical resistivity imaging and vlf-em

Documents

d resistivity imaging

d resistivity measurements

keywords resistivity

dinverse model resistivity

vlfem data

d distribution

d traverseswere

d inversion