ORIGINAL PAPER

Quantitative characterization to construct hard rock lithologicalmodel using dual resistivity borehole logging

Subash Chandra & Alexandre Boisson & Shakeel Ahmed

Received: 14 January 2014 /Accepted: 29 April 2014# Saudi Society for Geosciences 2014

Abstract Borehole logging is a very robust tool to accuratelylocate transitions between weathered layers and fractures inhard rock settings; therefore, it can help substantially in theconstruction of regional and local hydrogeological models. Asimple and low-cost resistivity probe, named dual resistivitylogger (DRL), was experimented to map the formation resis-tivity at two investigation distances by means of three activeelectrodes. Forward response of DRL was analysed on thesynthetic data generated for a conceptual hard rockhydrogeological model as well as tested at two field sites inhard rock aquifers of southern India. The DRL was provenefficient in demarcating the aquifer into successivehydrogeological zones, i.e. the laminated-fissured (L-F), thefissured-semi-fissured (F-SF), and semi-fissured-basement(SF-B) layers. The results were verified by comparison withwell lithologs based on rock cuttings and temperature logging.The DRL has proven its ability to locate the hydraulicallyactive fractures as well as contacts between weathered layers.It offers a simple but efficient way to acquire undergrounddata for building hydrogeological models.

Keywords Borehole geophysics . Dual resistivity logger .

Hard rock aquifer .Weathered . Fractures . Hydrogeologicalmodel

Introduction

The groundwater resources are under stress due to excessivegroundwater abstraction towards irrigation, domestic and in-dustrial needs in semi-arid hard rock terrain. This limits thegroundwater availability for future utilization (e.g. Dewandelet al. 2010; Sonkamble et al. 2013) and causes water salinityincrease that may adversely impact agricultural productionsand human health (e.g. Perrin et al. 2011). Recent studies havefocussed on groundwater resource management tools espe-cially designed for the semi-arid hard rock context. For anexample, a decision support tool (DST) is developed by Indo-French Centre for Groundwater Research to simulate thegroundwater resource in hard rock aquifer (Dewandel et al.2007, 2010). The DST simulates the groundwater resourceevolution for different scenarios, viz. changing cropping pat-terns, artificial recharge, climatic conditions, etc. The simula-tion result is dependent on the accuracy of the requiredhydrogeological inputs such as aquifer thickness and specificyield variations with depth in addition to rainfall, land use,water level time series, etc. In such hard rock aquifers, flow ismainly constrained by discrete fractures or fractured zones(Dewandel et al. 2006). Therefore, a clear knowledge of thefracture network structure and location is of prime importanceto understand hydrodynamics and solute transport (Neuman2005). Although there are a number of non-invasive groundgeophysical techniques, they suffer from uncertainties andinherent ambiguities such as overburden effects, near-surfaceheterogeneities, and principle of equivalence (Keller andFrischknecht 1966; Chandra et al. 2004, 2006; Chandra2006). Borehole geophysics provides more accurate informa-tion as different strata are directly probed and can be applied inthe large number of existing boreholes, particularly in a coun-try like India.

Among the number of geophysical tools, geoelectricalmethod offers the widest range of resistivity variation and

S. Chandra (*) : S. AhmedCSIR-National Geophysical Research Institute, Indo-French Centrefor Groundwater Research, Uppal Road, Hyderabad 500007, Indiae-mail: schandra75@gmail.com

S. Chandrae-mail: chandra_s75@ngri.res.in

A. BoissonBRGM, D3E/NRE, Indo-French Centre for Groundwater Research,Uppal Road, Hyderabad 500007, India

Arab J GeosciDOI 10.1007/s12517-014-1448-1

hence is the most applied tool to define the lithological chang-es, water saturation, salinity, etc. (Krishnamurthy et al. 2007;Chandra et al. 2011) and led to developing various electricaltools such as normal log, lateral log, laterolog, focussed log,and microlog. These tools have their own advantages as wellas limitations due to different sensitivity distributions andhence should be chosen based on the problems. There hasbeen immense advancement in this field by introducing avariety of probes with the latest technology. For example,there are tools that can measure extremely high resistivityenvironment, viz. oil-based mud or gas as the borewell fluid(by induction log), and on the other hand in extremely lowresistive formation such as saline bed by laterolog (Lynch1962; Deng et al. 2013)

Further advancements led to the development of multi/dualloggers such as dual laterolog, which provides measurementsat two depths. Short normal and long normal resistivity logs,where electrode separations between current and potentialelectrodes are respectively 16 and 64 in. can also be used forsuchmeasurements. In hard rock aquifers, the natural geologicsystem and associated weathering/fracturing are normallycomplex. For example, natural fractures either generated bytectonic activity or issued from weathering processes are mostlikely of large to moderate dimensions, whereas the cracksgenerated while drilling are most likely of local dimension. Insuch complex heterogeneous system, additional informationis always advantageous as it reduces the uncertainty in theinterpretation.

This paper demonstrates the concept of dual resistivitylogger with sensitivity distribution, forward simulation andfield experiment in hard rock to characterize quantitativelygeoelectrical parameters and differentiate various litho units.A simple and low-cost probe, called dual resistivity logger(DRL), was fabricated at CSIR-NGRI with PVC pipe andcopper ring obtained from the local market. This was used toacquire the data using Syscal Junior Switch resistivity meter.The field experiments were done at NGRI campus, Hyderabadand the Experimental Hydrogeological Park (SOERE H+network), Choutuppal, Andhra Pradesh, India.

Methodology

Theoretical background

The dual resistivity (DRL) logging tool was conceptualizedfor special application in hard rock granitic terrains, wheregroundwater is contained in the secondary porosity developeddue to weathering, fissuring and fracturing.

Dewandel et al. (2006) described a 3-D geological andhydrogeological model of hard rock aquifers (in southernIndia) constituted by two layers: the saprolite layer on tophaving a lower transmissivity and higher porosity underlain

by the fissured layer of higher transmissivity where fracturedensity decreases with depth. It is commonly accepted that noflow appears below the fissured layer in such terrain. Inaddition, the water wells are normally drilled by down-the-hole (DTH) drilling that results in an additional developmentof the cracks along the walls. These are unequally distributedthroughout the borehole depending on the rock strength. Insuch condition, measuring the resistivity at two different radialdistances of investigations at each horizon in the samemannerwill facilitate an unambiguous log interpretation and allowdifferentiating large fractures from geological developmentfrom small crack from drilling.

Figure 1a presents the electrode setup of DRL, where threeactive electrodes (A, M1 and M2) are fixed in the sondemaintaining 1-m inter-electrode spacing between adjacentelectrodes. Other current (B) and potential (N) electrodes areplaced at the surface theoretically at infinity. The M1 and M2

are alternatively used as active potential electrodes (M) withthe help of a switch. Thus, at a time only, four electrodes areused during the measurement. Since only two (current andpotential each) electrodes attached to the probe are active at atime of measurement, the array is called pole-pole. Two pole-pole resistivity measurements are made at each horizon, andhence, it is termed as dual resistivity logging. Apparent resis-tivity (R) for full space can be calculated as

R ¼ 4πΔV

Ið1Þ

where a, I and ‘ΔV’ are respectively the electrode separation(m), current injection (mA) and potential difference (mV). Themathematical derivation of the equation may be found intextbooks on geophysics, such as Dakhnov (1959), Kellerand Frischknecht (1966), and Telford et al. (1976).

In general, geophysical measurements express an averageof the physical parameters to which it is sensitive over acertain volume (Roy and Apparao 1971; Loke 2000;Christensen 2009). Therefore, sensitivity analysis of DRLwillgive better understanding of its resolution capability. The M1

and M2 are maintaining respectively a and 2a separationsfrom A. One-Dimensional sensitivity (S1D) distribution ofthe DRL array was computed for homogeneous full space as

S1D ¼ 1

πx

a2 þ 4x2½ �32ð2Þ

where, x is the lateral distances representing depth.Figure 1b presents the sensitivity distribution of the DRL

array keeping a and 2a respectively as 1 m (AM1) and 2 m(AM2) in an isotropic and homogeneous formation. The sen-sitivity is zero at the electrode point and rises initially towards

Arab J Geosci

maximum, after which it falls towards zero for x→∞. Sensi-tivity maxima for AM1 and AM2 are found to be 6.12×10

−2 at0.36 m and 1.53×10−2 at 0.7 m respectively. Half of thesensitivity comes from the zone between 0.1 and 0.87 m forAM1 and between 0.22 and 1.73 m for AM2. The sensitivitydistribution indicates that the AM1 has four times better reso-lution than the AM2 up to 0.87-m radius of investigation.However, AM2 presents relatively average response with dou-ble the investigation radius of AM1. Since degree of

disturbance (i.e. drilling-induced cracks in the wall of wells)decreases outward, M1 is affected approximately four times(due to its high resolution in the vicinity) higher than the M2.Fracture zones may vary from sub-metres to metres comprisedof millimetre- to centimetre-thick fractures. Thus, pinpointingthe thin individual fracture can be dealt well by AM1, andhence, the combination of AM1 and AM2 brings unambiguousinvestigations. In other words, M1 can be utilized to pinpointthe changes and the local variability, whereas M2, being less

Switch

AM1

M2

BN

M A

BN

Resistivity meter

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 50

0.01

0.02

0.03

0.04

0.05

0.06

0.07

Depth(m)

Sensi

tivity

One-D Sensitivity Distribution

AM1=1mAM2=2m

(a)

(b)

Fig. 1 a Layout of dualresistivity logger (DRL) array andb 1-D sensitivity distribution withAM1=1 m and AM2=2 m. Thesensitivity maxima are markedwith blue and green arrows forrespectively AM1 and AM2

Arab J Geosci

affected with the noise, can be used to quantify the distant andnatural changes.

Synthetic simulation

To visualize the response of DRL log, forward computationwas carried out over a 10-m-thick and 72-m-deep syntheticmodel as a representative of granite aquifer (Fig. 2). Themodel is made up of four successive layers: (i) a top 20-m-thick layer with 40-Ωm resistivity similar to weathered gran-ite, (ii) an underlying weathered-fissured layer with 191 Ωm(up to 33 m), (iii) a fissured layer of 308Ωm (up to 44 m), and(iv) a 612-Ωm resistive bottom layer (compact zone).

The layer boundaries are marked as B1, B2 and B3. Hardrocks are also known for the occurrences of some productivefractures at deeper levels. Therefore, two productive fracturesF1 and F2 were created respectively at 26- and 38-m depths byassigning 20-Ωm resistivity. Apparent resistivities for 1- and2-m electrode spacing were computed using RES2DMODand inverted to get the true resistivity using RES2DINV(Loke and Barker 1996; Loke 2000).

Field applications and validation

Validation of the method was done through filed measure-ments by comparison with hydrogeological measurementscurrently used for fracture identification. A probe was madeusing a PVC pipe of 4-in diameter and copper rings fixed overthe pipe as electrodes A, M1 and M2 maintaining respectively1-m (AM1) and 1.9-m (AM2) spacing. It is a simple and cost-effective tool as the required material could be obtained easilyfrom the local market and fabricated without much expertise.

Four wells (NB-2, CH1, CH-2 and CH-3) of 6.5-in diameterwere logged at every 0.5 m starting below the casing underwater table. The diameter of the well and water column lyingbetween probe and formation affect the measured apparentresistivity (AR), which were removed using the Schlumbergerchart (Lynch 1962). The resultant resistivity after applying thecorrection factor is mentioned as True Resistivity (TR).

NB-2 well was drilled at NGRI campus in Hyderabad to adepth of 170 m (Chandra et al. 2009), whereas the CH- wellswere drilled on the Experimental Hydrogeological Park ofChoutuppal, part of the SOERE H+ network, 60 km awayfrom NGRI campus to a maximum depth of 73 m (Perrin andMohamed 2008). Both sites are located in the Archean ortho-genesis granite.

Drilling rock cuttings were collected every metre andanalysed in the field for colour changes, weatheringindications on the rock grains, etc. Water flow increasewas also monitored during the drilling. After drilling,samples were washed and spread successively andanalysed in the lab. The geological logs were then drawnbased on the field and lab observations.

DRL data were verified with the borehole camera at NB-2wells and temperature logging in CH- wells using Multi-parameter probe HachHydrolab MS5 allowing logging oftemperature (resolution 0.01 °C, accuracy ±0.1 °C), conduc-tivity, and pH. Logs were achieved under ambient conditionsfor all wells.

Results and discussion

Synthetic data

Apparent resistivities for 1- and 2-m electrode spacing werecomputed using RES2DMOD and inverted to get the trueresistivity using RES2DINV (Loke and Barker 1996; Loke2000). Figure 2 presents the apparent and modelled (i.e.inverted) resistivity responses. The top 40-Ωm resistivity layeris exactly the same in the computed apparent resistivity byboth electrode spacing. However, slightly different responsesof the AM1 and AM2 are achieved at 20-m depth and down-wards. A jump in the apparent resistivity can be seen at eachboundary with its value slightly less than the actual resistivity.Resistivity (AR_1m) obtained with 1-m electrode spacingshows a sharp decrease over the fractures compared toAR_2m. However, after the inversion, even model resistivityfor 2 m (i.e. AM2) turned with sharp low resistivity peak overfracture. The inverted modelled resistivity for AM1 and AM2

is similar to the one assigned in the synthetic model. Thefractures are reflected with low-resistivity anomaly. It is ap-parent that the tip of the fracture location was better resolvedin the modelled resistivity.

The marginal difference in the computed apparent resistiv-ity response below 44 m is due to the different sensitivities ofthe pole-pole measurements with 1- and 2-m spacing. Theprobe crosses the deepest transition boundary at 44-m depth,but the overlying fissured layer influences the measurementswith different degrees of sensitivity. However, moving awayfrom the boundary, AR_1m and AR_2m attain resistivitycloser to the true resistivity in the synthetic model.

Model resistivity for AM1 and AM2 obtained throughinversion brings resistivity values close to the assigned resis-tivity. It also produces spurious resistivity kink over the edgesof the contacts. Two spurious kinks are observed on eithersides of the fracture over contacts and also one at the layerboundaries.

In general, DRL is found responding to the lithologicalchanges and hence capable of bringing valuable informationto build the hydrogeological model. This was an ideal condi-tion, where no lateral and local heterogeneities exist near theelectrodes. However, in the real-field conditions, presence ofvertical and sub-vertical fractures will make the responsemorecomplex. Moreover, heterogeneities exist depending on theadopted drilling technique and the strength of the rock. In such

Arab J Geosci

situation, the apparent resistivity measured by both the poten-tial electrodes(M1 and M2) are most likely not to be of thesame magnitude, and hence, difference in inverted resistivityshould be observed too. Additionally, the presence of waterand its quality in the well affect the measured resistivity withdifferent degrees of sensitivity.

It is clear from the synthetic simulation that the AM1 gotfour times better sensitivity than the AM2 in resolving theshallow signal, and the measured resistivity is quite close tothe assigned true resistivity. But, due to maximum drillingdisturbance in the vicinity, it is also more prone to noisysignals. Thus, AM2 brings more averaged response and canbe utilized to demarcate the broader lithological changes andAM1 to pinpoint the discrete hydrogeological features such ascracks and fractures.

Sometimes, due to a large resistivity difference along thevertical profile, inversion of the apparent resistivity becomesproblematic. However, as underground strata encountered inthe well are directly probed, the measurements are not much

affected by the overburden unlike the surface geophysicalmeasurements. Thus, apparent resistivity measured by AM2 isquite close to the true resistivity. Therefore, it could be useddirectly to characterize the lithology and was exercised whiledoing the interpretation of themeasured litholog in all the wells.The measurements are affected near the layer boundaries byunderlying/overlying strata. For example, while lowering theDRL, apparent resistivity initially rises when it gets close to theboundaries (i.e. B1, B2 andB3), becomes flat over the boundary,and rises afterwards attaining the true resistivity of the layeraway from the boundary (Fig. 2). The invertedmodel resistivitygives high-resistivity gradient over the boundary.

Field applications

NB-2 well

Figure 3 presents lithologs and DRL log sand borehole pho-tographs of the NB-2 well. The litholog broadly presents four

0

10

20

30

40

50

60

70

SyntheticBorehole model

0

10

20

30

40

50

60

70

0 500 1000Resistity (Ωm)

Resistivity

AR_1m

AR_2m

MR_1m

MR_2m

B1

B2

B3

F1

F2

Depth (m

)

Lam

inat

edF

issu

red

Com

pact

Fig. 2 Forward response of thesynthetic layered model, wherewater saturated fractures (F1 andF2) are assigned with low (i.e. 20Ωm) resistivity. Lithologicalboundaries are marked as B1, B2and B3

Arab J Geosci

layers, i.e. top ~3-m sandy regolith followed by successivelylaminated (up to ~20 m), fissured (up to ~156 m), and under-lying basement granite. The DRL data, particularly TrueResistivity for 1.9 m electrode spacing (TR_1.9m), wascalibrated against borehole litholog that revealed the

laminated-fissured (L-F) and fissured-basement (F-B)boundaries that fall at ~300- and ~3,000-Ωm resistivityrespectively. The F-B boundary poses approximately tentimes resistivity of the L-F boundary leaving a large resis-tivity difference as well as the thickness of the fissured layer

20

10

30

40

50

60

70

80

90

100

110

120

130

140

150

160

170

0

Dolerite

Quatzvein

Water

Water

Laminated layer

Sandy Regolith

Fis

sure

d la

yer

Fresh basement

Litholog (NB-2)

Dep

th (

m)

Water

L-F boundary

F-SF boundary

SF-Bboundary

D=20 m

D=50 m

D=110 m

D=140 m

D=160 m

E-Log Photographs

Sandy RegolithLaminated Granite

Fissuredgranite

Fissures granite

Quartz vein

Doerilte dyke Compact granite

Fig. 3 A comparative litholog and DRL plots of 170-m-deep NGRIborewell NB-2. AR_1m is apparent resistivity measured in the field withAM1=1 m. Similarly, AR_1.9m means apparent resistivity for AM2=

1.9 m. TR is termed the corrected resistivity for water present in the well,the dimension of logger and the well diameter. Right side photographs areobtained by borehole camera where D indicates depths.

Arab J Geosci

found to be roughly seven times of the laminated layer. It isa well-established fact that the density of fracture reduceswith depth (Maréchal et al. 2004; Dewandel et al. 2006;Chandra et al. 2008, 2010). That means that the entirefissured zone may not be hydraulically potential. Therefore,the fissured zone could be divided into two zones, i.e. upperpotential and lower non-potential fissured layers. With thisconsideration, an intermediate resistivity band of 1,500 Ωm(i.e. five times of the W-F boundary) was introduced todivide the fissured layer into two halves, i.e. upper fissured(consists of dense fractures)and semi-fissured granite. This

divider is merely taken as an intermediate resistivity band inlack of any other supporting evidence.

Initially, TR_1.9m intersects the 3,000 Ωm at around 60 malso but falls back at around 90-m depth, indicating a 30-m-thick relatively compact fissured granite. In general, small-scale lithological heterogeneities such as biotite granite withfeldspar, chlorite, and quartz intrusive fractures influence theresistivity measurements with small amplitude, but the resis-tivity fluctuation in each respective zone is found around theirrepresentative resistivity divider line. Thus, there are threeresistivity bands marked with dash-dotted straight vertical

Fissured granite

Fissures granite

Quartz vein

Doerilte dyke Compact granite

Sandy RegolithLaminated Granite

-

L-F boundary

F-SF boundary

SF-B boundary

E-Log

0

10

20

30

40

50

60

70

80

30 31 32Temperature °C Litho-log (CH-1)

Fig. 4 Litholog and DRL logs of borewell CH-1 at Choutuppal experimental hydrogeological park

Arab J Geosci

resistivity lines at 300, 1,500 and 3,000Ωm that divide L-F, F-SF and SF-B boundaries.

The first moist fracture was encountered at ~45-m depth,which responded with low resistivity in both TR_1m andTR_1.9m. The second fracture with water was encounteredat ~115-m depth. Two corresponding resistivity low peaks at112 and 118 m can be seen in the DRL log. The third waterstruck is encountered at 150-m depth and produces a corre-sponding low-resistivity anomaly in the DRL log. The third

fracture at 150-m depth is found in the basement granite and isprobably of tectonic origin. Main anomalies observed on theDRL log are verified with fractures observed using the bore-hole camera (Fig. 3).

CH-1 well

The DRL experiment in CH-1 well shows an almost exactcoincidence of L-F layer boundary at 24-m and SF-B layer

Litholog (CH-2)

0

10

20

30

40

50

60

70

80

29.5 30.5 31.5

L-F boundary

S-SF boundary

E-Log T-Log (°C)

Fissuredgranite

Fissures granite

Quartz vein

Doerilte dyke Compact granite

Sandy RegolithLaminated Granite

Fig. 5 Litholog,DRL and temperature logs of borewell CH-2 at Choutuppal experimental hydrogeological park

Arab J Geosci

boundary at 55-m depthswith the litholog (Fig. 4). ThemiddleF-SF layer boundary is found at ~40-m depth. There is noDRL log for the initial two fractures. However, the last threeproductive fractures marked between 33- and 37-m depths inthe litholog were found with a low resistivity peak at ~35-mdepth. DRL indicates a major fracture zone at 35-m depth.Although there are two additional fractures on either side inthe litholog, however, these are reflected as a single fracture inthe DRL log.

In open boreholes, differences in hydraulic heads betweenfractures connected to large-scale flow paths create an ambientvertical flow (Paillet 1998). Those ambient flow disturb am-bient natural temperature gradient, and those anomalies maybe used to assess ambient flow velocity (Anderson 2005;

Klepikova et al. 2011) and to locate productive fractures(Pehme et al. 2009; Chatelier et al. 2011). Therefore, to assessthe productive quality of the fractures observed from the DRLmeasurements, we compare the logs with temperature pro-files. Note that due to the needed presence of flow, only themain productive fractures with different hydraulic head inambient condition may be identified from temperaturemeasurements.

The sharp temperature gradient between the base of thecasing at the end of the laminated layer (24 m) and 34-m depthindicates a vertical flow between two fractures localized atthose depths. Those observations are in accordance with theidentified fractures on the DRL log at 24 and 34 m. Thetemperature profile exhibit a constant gradient between 40-

0

5

10

15

20

25

30

35

40

45

50

30 30.5 31

CH3

Litho-Log (CH-3) E-Log T-Log (°C)

Fissured granite

Fissures granite

Quartz vein

Doerilte dyke Compact granite

Sandy RegolithLaminated Granite

SF-B boundary

Fig. 6 Litholog, DRL and temperature logs of borewell CH-3 at Choutuppal experimental hydrogeological park

Arab J Geosci

and 68-m depths, indicating no ambient flow in this region.This is also in accordance with the DRL log highlighting theabsence of fracture in this zone.

CH-2 well

DRL log revealed L-F boundary at 23-m and F-SF boundaryat ~39-m depth in CH-2 well, which brings almost exactcoincidence with the litholog (Fig. 5). The main fractureobserved from the lithology at 38 m is also clearly observedon DRL data. However, in contrary to the litholog, the base-ment boundary was not picked up in the DRL log. Althoughthe litholog showed small fissures with FeO grains, however,AR_1.9m has shown slowly decreasing resistivity downward.As the fracture density distribution decreases with depth in thegranite (Maréchal et al. 2004), the lower fissured layer be-comes insignificant at deeper levels close to the basement dueto scattered thin fractures. Thus, it is obviously difficult todemarcate the transition boundary precisely while preparinglitholog. It is evident from the temperature log that no flowexists between the fractures at deeper level due to absence oftemperature gradient anomalies. However, electrical conduc-tivity logging shows a sharp change of water chemistry at themain fracture zone (38 m) as observed with lithology andDRL. This highlights the advantage of DRL over temperaturelogging when no ambient flow is present. It is of importancewhen, as often, lithology is not available.

CH-3 well

The CH-3 well demonstrates occurrences of possible mis-takes in preparing well lithologs. The litholog preparedbased on the drill rock cuttings shows six water-producingfractures located at different depths (Fig. 6). However, DRLrevealed only one fracture below 25-m depth. The fractures

at 29-, 33- and 37-m depths in litholog do not produce anyresponse in DRLmeasurement. Constructing litholog basedon the drill rock cuttings has a chance of misleading inter-pretation as fractures due to possibility of falling of angularFeO-coated rock cuttings from the upper horizons to deeperlevels. Whereas, the pressure variation of the injected airinto the well to remove rock cuttings affects change in thewell yield that misleads as water bearing fractures. Resultof in situ DRL measurement is validated by the temperaturelog showing a single variation at 27-m depth. As per theresistivity measured in DRL log, it has investigated SF-Bboundary at 27-m depth (Fig. 6). There are some moreinvestigation needed to resolve the differences betweenbasement depths marked at ~42 m in litholog and ~27 min DRL.

The basement depth at ~62 in litholog of CH-2 wellcould not be marked in the DRL experiment as TR did notattain the value of 3,000 Ωm . To further verify suchcomparative observations, drilling time record was studied.During the drilling of CH-1, CH-2 and CH-3 wells, the timetaken by each 4.6-m-long drilling rod was recorded to havean idea about the compactness of formation (Fig. 7). Asthere is almost exact coincidence of DRL and lithologs atCH-1 well, the drilling time record was calibrated where L-F and F-B boundaries are encountered respectively at 25-and 56-m depths with drilling times of 2 and 10.8 minrespectively. Thus, two lines at 2 and 10.8 min are markedas L-F and F-B time lines. Although the drilling timetouches to the 10.8 min in the middle part of CH-2 well, itreduced to ~9 min at the deeper level until bottom. Thus, itis confirmed that the fresh basement has not been encoun-tered in the CH-2 well, and hence, it validates the DRL logresults. In CH-3 well, drilling time record supports the DRLresults by indicating the basement in seventh rod in thedepth range of 27–32 m.

0

2

4

6

8

10

12

14

drill

ing

time

in

min

ute

s

Depth range (m)

CH-1 (minutes)

CH-2 (minutes)

CH-3 (minutes)

Drilling Time RecordFig. 7 Drilling time records ofwells CH-1, CH-2 and CH-3 atChoutuppal experimentalhydrogeological park

Arab J Geosci

The drilling time record is taken as a qualitative cross check tothe DRL log and litholog interpretations. Although all the possi-ble cares were taken, drilling time records might also be biased tosome extent due to certain uncertainties and happenings such ascollection of the rock cutting samples and number of flushing.Therefore, the time line of 2 and 10.8 min are just indicative.

Contrary to the thickness ratio of fissured and laminatedlayers in CH- wells (i.e. ~1.2), it is found around 6 in NB-2well. NB-2 well is drilled at the contact of quartz reef wheredeepening of the weathering and fracturing front is a commonoccurrence (Chandra et al. 2010; Dewandel et al. 2011).

Thus, from the above observations, it is very clear that theDRL log is capable in pinpointing the fractures and demarcatesthe lithological boundaries in order to construct thehydrogeological model with high accuracy. This is devoid ofmanual error and personal biasness. Even the resistivity canlead further to derive the hydraulic parameters of the differentzones. As in India, a large number of defunct wells are avail-able, and these can be used to construct the hydrogeologicalmodel by probing with the DRL log and used to the DST orother groundwater management schemes as input parameters.

DRL log identification of the hydraulically active/productive fractures was used to sub-divide fissured zone intoupper hydraulically active fissure and lower inactive semi-fissured layers. The F-SF boundary could be treated as thebottom of the productive layer or aquifer base.

Such quantitative subsurface information in terms of resis-tivity can be linked with the hydrological information such ashydraulic conductivity by pumping tests and flow metres totransform resistivity into hydrological parameters (Molz et al.1989; Chandra et al. 2008).

Conclusion

This study concludes that the DRL logging is a low-cost andsimple tool, efficient to construct a realistic hydrogeologicalmodel with the least manual error and personal biasness. Thetool was successfully applied to pinpoint the fractures as wellas demarcate the transition boundaries differentiating variouslitho units such as laminated, fissured, and fresh basementgranite precisely. These were verified with the litholog, dril-ling time records, temperature log and the borehole camera.Although a thick aquifer layer overlies the compact basementgranite, the entire fissured zone is not hydraulically potential.Quantitative interpretations of DRL log helped in sub-dividing the fissured layers into two parts, i.e. upper hydrau-lically potential (i.e. fissured) and lower non-potential (i.e.semi-fissured) layers.

This tool proved to be very useful in hard rock regions ofsouthern India where a large number of abandoned farmerborewells can be used for DRL logging to identify the litho-logical layers. Obtained results on aquifer layer thickness are

essential to the construction of hydrogeological models,groundwater resource estimation, design of groundwater re-source management tools, etc.

Acknowledgments This study has been carried out at the Indo-FrenchCentre for Groundwater Research (IFCGR), a joint centre of NGRI, Indiaand BRGM, France. The authors wish to thank the Ministry of ExternalAffairs of both countries for their kind support and cooperation. We arethankful to the Director, NGRI, Hyderabad for his support, encourage-ment and according permission to publish this paper. We acknowledgeSOERE H+ network for its help on the EHP Choutuppal site develop-ment. Special thanks to Sri RSK Srinivasulu, Engineer and Mr. AnilKumar for fabricating the DRL probe at NGRI. The valuable discussionsand support extended by Dr. Jerome Perrin, Dr. D.V Reddy, Dr. SurendraAtal, Dr. E. Nagaiah, W. Mohamed, Mohd Ahmeduddin, P. Raghvendra,and V. Zaphu are sincerely acknowledged. Finally, we would like toexpress thanks to the anonymous reviewer and editor for their criticalreviews and valuable suggestions, which improved the paper.

References

Anderson MP (2005) Heat as a groundwater tracer. Ground Water 43(6):951–968

Chandra S (2006) Contribution of geophysical properties in estimatinghydrogeological parameters of an aquifer. Unpublished Ph.D. thesis.BHU, Varanasi, pp. 176

Chandra S, Ananda Rao V, Singh VS (2004) A combined approach ofSchlumberger and axial pole-dipole configurations for groundwaterexploration in hard rock areas. Curr Sci 86(10):1437–1443

Chandra S, Rao VA, Krishnamurthy NS, Dutta S, Shakeel A (2006)Integrated studies for characterization of lineaments to locategroundwater potential zones in hard rock region of Karnataka,India. Hydrogeol J 14:767–776

Chandra S, Ahmed S, Ram A, Dewandel B (2008) Estimation of hardrock aquifers hydraulic conductivity from geoelectrical measure-ments: a theoretical development with field application. J Hydrol35:218–227

Chandra S, Atal S, Nagaiah E, Mallesh D, Krishnamraju P, AhmeduddinM, Zaphu V, Seshamma NV, Rao VA, Ahmed S (2009) Electricalresistivity tomography survey to test the performance multi-electrode resistivity systems (Syscals). NGRI-2009-GW-690. p 26

Chandra S, Dewandel B, Dutta S, Ahmed S (2010) Geophysical model ofgeological discontinuities in a granitic aquifer: analyzing small scalevariability of electrical resistivity for groundwater occurrences. JAppl Geophys 71:137–148

Chandra S, Ahmed S, Nagaiah E, Singh SK, Chandra PC (2011)Geophysical exploration for lithological control of arsenic contam-ination in groundwater in Middle Ganga Plains, India. Phys ChemEarth, Elsevier publication (on line published): doi:10.1016/j.pce.2011.05.009

ChatelierM, Ruelleu S, Bour O, Porel Gl, Delay F (2011) Combined fluidtemperature and flow logging for the characterization of hydraulicstructure in a fractured karst aquifer 400(3–4):377–386

Christensen NB (2009) Sensitivity function of EMmethod: a lecture note.Aarhus University, Denmark

Dakhnov VN (1959) Geophysical well logging. Q Colo SchMines 57(2),445 p

Deng R, Guo H, Xiao C (2013) Apply array induction logging to studythe low-resistivity belt zone identification method. Arab J Geosci.doi:10.1007/s12517-013-1049-4

Dewandel B, Lachassagne P, Wyns R, Maréchal JC, Krishnamurthy NS(2006) A generalized 3-D geological and hydrogeological

Arab J Geosci

conceptual model of granite aquifers controlled by single or multi-phase weathering. J Hydrol 330:260–284

Dewandel B, Gandolfi J-M, Zaidi FK, Ahmed S, Subrahmanyam K(2007) A decision support tool with variable agroclimatic scenariosfor sustainable groundwater management in semi-arid hard rockareas. Curr Sci 92(8):1093–1102

Dewandel B, Perrin J, Ahmed S, Aulong S, Hrkal Z, Lachassagne P,Samad M, Massuel S (2010) Development of a tool for managinggroundwater resources in semi-arid hard rock regions. Applicationto a rural watershed in south India. Hydrol Process 24:2784–2797.doi:10.1002/hyp.7696

Dewandel B, Maréchal JC, Ladouche B, Bour O, Ahmed S, Chandra S,Pauwels H (2011) A Conceptual hydrodynamic model of a geolog-ical discontinuity in hard rock aquifers: example of a quartz reef ingranitic terrain in South India. J Hydrol 405:475–487

Keller GV, Frischknecht FC (1966) Electrical methods in geophysicalprospecting First Edition. Pergamon Press, London, 519 pp

Klepikova M, Le Borgne T, Bour O, Davy P (2011) A methodology forusing borehole temperature-depth profiles under ambient, single andcross-borehole pumping conditions to estimate fracture hydraulicproperties. J Hydrol 407:145–152. doi:10.1016/j.jhydrol.2011.07.018

Krishnamurthy NS, Chandra S, Kumar D (2007) Characterization of hardrock aquifer. A chapter in book “Groundwater dynamics in hardrock aquifers”. Capital Publishing Company, pp 64-86

Loke MH (2000) Electrical imaging surveys for environmental andengineering studies: a practical guide to 2-D and 3-D surveys, p 67

Loke MH, Barker RD (1996) Rapid least-squares inversion of apparentresistivity pseudo sections using a quasi-Newton method. GeophysProspect 44:131–152

Lynch EJ (1962) Formation evaluation. Harper’s Gosciences Services,Harper & Row

Maréchal JC, Dewandel B, Subrahmanyam K (2004) Use of Hydraulictest at different scales to characterize fracture network properties intheweathered-fractured layer of hard rock aquifer.Water Resour Res40(W11508):1–17

Molz FJ,Morin RH, Hess AE,Melville JG, Guven O (1989) The impellermeter for measuring aquifer permeability variations: evaluation andcomparison with other tests. Water Resour Res 25(7):1677–1683

Neuman SP (2005) Trends, prospects and challenges in quantifying flowand transport through fractured rocks. Hydrogeol J 13:124–147

Paillet FL (1998) Flow modeling and permeability estimation usingborehole flow logs in heterogeneous fractured formations. WaterResour Res 34(5):997–1010

Pehme PE, Parker BL, Cherry JA, Greenhouse JP (2009) Improvedresolution of ambient flow through fractured rock with temperaturelogs. Ground Water 48(2):191–205

Perrin J, MohamedW (2008) Borewell drilling report of HydrogeologicalPark, Choutuppal. IFCGR-2008, p 20

Perrin J, Mascré C, Pauwels H, Ahmed S (2011) Solute recycling: anemerging threat to groundwater resources in southern India? JHydrol. doi:10.1016/j.jhydrol.2010.12.024

Roy A, Apparao A (1971) Depth of investigation in direct currentmethods. Geophysics 36:943–959

Sonkamble S, Chandra S, Nagaiah E, Dar FA, Somvanshi VK, Ahmed S(2013) Geophysical signatures resolving hydrogeological complex-ities over hard rock terrain—a study from Southern India. Arab JGeosci. doi:10.1007/s12517-013-0931-4

Telford WM, Geldart LP, Sheriff RE, Keys DA (1976) Applied geophys-ics. Cambridge University Press, New York, 860 pp

Arab J Geosci