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Combined electrical and electromagnetic imaging of hot fluids within fractured rock in rugged Himalayan terrain
Journal of Applied Geophysics 74 (2011) 205–214
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Journal of Applied Geophysics j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / j a p p g e o
Combined electrical and electromagnetic imaging of hot fluids within fractured rock in rugged Himalayan terrain Kumari Sudha a, c,⁎, Bülent Tezkan a, Mohammad Israil b, 1, Jagdish Rai c a b c
Institute of Geophysics and Meteorology, University of Cologne, Germany Department of Earth Sciences, Indian Institute of Technology Roorkee, Roorkee-247667, India Department of Physics, Indian Institute of Technology Roorkee, Roorkee-247667, India
a r t i c l e
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Article history: Received 30 January 2010 Accepted 3 June 2011 Available online 15 June 2011 Keywords: Electrical resistance tomography Transient electromagnetic Sign reversal 2D–3D effects
a b s t r a c t Integrated electrical resistance tomography (ERT) and short-offset transient electromagnetic (TEM) measurements were carried out to investigate a geothermal area in the Main Central Thrust (MCT) zone of Garhwal Himalayan region, India. The study area is located around Helang on either side of Alaknanda River and it is dotted with hot water springs with water temperature of 45°–55 °C emerging at the surface. To assess the geothermal potential and its lateral and vertical extension in and around the hot water springs in the study area, 7 ERT profiles and 21 TEM stations on 7 profiles were established around the hot water spring and at far distant locations. The 2D inversion of ERT data indicates a low resistivity (b 50 Ωm) zone in the vicinity of hot springs, which appears to be associated with an underground water channel through the fractured rock. The bedrock resistivity is very high (N 1000 Ωm) whereas the resistivity of the weathered near surface soil at a far distant location from the hot spring is low (b100 Ωm) again. A common feature of all TEM data is the sign reversal observed at roughly 10 μs. The consistent sign reversal in all TEM data indicates the existence of the multi-dimensionality of the geoelectrical structure. Therefore, the TEM data were treated by using the SLDM (Spectral Lanczos Decomposition Method) 2D/3D forward modeling code based on the finite difference algorithm. The resistivity structure obtained from ERT data was used as an input for the modeling of TEM data. Based on the joint analysis of the ERT and TEM data it can be inferred that geothermal anomalies associated with the hot spring in the MCT zone are a local feature appearing as a low resistivity zone (b 50 Ωm) at shallow depth (b100 m) in the vicinity of the hot spring region. © 2011 Elsevier B.V. All rights reserved.
1. Introduction The rationale for the use of ERT and TEM methods is that a high temperature geothermal zone is manifested as low resistivity anomaly in the geoelectrical model derived from ERT and TEM responses. Many authors have used different geoelectric and electromagnetic (EM) methods to study geothermal resource potentials in various parts of world (Pellerin et al., 1996; Wright et al., 1985). The target for the exploration of convective hydrothermal resources is usually a region composed of faults and fractures filled with thermal fluids and hydrothermal alteration products. The lowresistivity zone produced by the brines and clays capping of a geothermal system provides a feature that should be easily detectable by EM methods (Wright et al., 1985). The size and the low resistivity
⁎ Corresponding author at: Institute of Geophysics and Meteorology, University of Cologne, Albertus-Magnus-Platz, D-50923, Cologne, Germany. Tel.: +49 221 4706127. E-mail addresses: [email protected] (K. Sudha), [email protected] (M. Israil). 1 Tel.: + 91 1332 285078; fax: +91 1332 273560. 0926-9851/$ – see front matter © 2011 Elsevier B.V. All rights reserved. doi:10.1016/j.jappgeo.2011.06.002
of the clay cap associated with a geothermal system create a target well suited for EM methods. Pellerin et al. (1996) numerically evaluated four EM techniques for the use in geothermal exploration: magnetotellurics (MT), controlled source audio magnetotellurics (CSAMT), long-offset transient EM (LOTEM), and short-offset transient EM (SHOTEM). They concluded that a combination of CSAMT and SHOTEM measurements appeared most appropriate for the delineation of the clay cap. The use of electrical and electromagnetic methods in the characterization of a thermal reservoir is well documented in the literature (Caglar and Demirorer, 1999; Majumdar et al., 2000; Rashed et al., 2003; Savin et al., 2001; Yasukawa et al., 2003). Caglar and Demirorer (1999) studied a geothermal area in Kestanbol, Turkey, to investigate the fault zones using self-potential and resistivity surveys. Based on the self-potential map, the fault around Kestanbol showed a large potential associated with the active geothermal area. Rashed et al. (2003) conducted ground penetrating radar (GPR) survey to investigate the shallow geological structures in the vicinity of the fault zones across the Uemachi fault, Osaka, Japan. The interpreted GPR profiles showed the location and geometry of a subsurface fault scarp having a visible expression at the surface as well as several subsurface fault strands. Baranwal and Sharma (2006) used
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vertical electrical sounding (VES), very low frequency (VLF) EM and self-potential (SP) measurements to characterize the geothermal area around a hot spring in the Nayagarh district, Orissa, India that lies in the East Indian geothermal province. With the objective to ascertain the origin and subsurface geometrical configuration of geothermal springs in the MCT zone of Central Himalaya, we conducted ERT and TEM measurements and analyzed the electrical structure of the area. The present paper briefly discusses the geology of the study area followed by a detail description of the data recording, their analysis and interpretation. A possible correlation of the geoelectrical structure with the subsurface geothermal anomalies has also been done.
2. Geology of the study area The study area is located in Central Himalayan region near Main Central Thrust (MCT) zone, closed to Alaknanda River, in Uttarakhand, India. The Himalayan mountain belt is formed as a result of continental collision tectonics and under-thrusting of the Indian plate beneath the Eurasian plate. In this process the leading face of the upper brittle portion of the subducting Indian crust has been sliced and stacked up southwards to form the entire Himalayan Mountain. The various thrusts are the elements of this geodynamical process (Seeber et al., 1981). In general Himalaya, from south to north, can be divided into three major physiographic divisions namely; Outer Himalaya, Lesser Himalaya and Higher Himalaya. The Lesser Himalaya occupying a larger area is divisible into Outer Lesser Himalaya and Inner Lesser Himalaya. The study area is located in Inner Lesser Himalaya near MCT zone, closed to Alaknanda River, in district Chamoli, Uttarakhand, India. Geologically the area is characterized by a number of thrust sheets piled up one over another (GSI, 1991). As a result, local and subregional faults and shear zones are commonly seen in the region. Regionally the rocks of the area have been classified into two broad tectonic units: Central Crystalline in the north and Garhwal in the south separated by a northerly dipping tectonic plane referred as MCT (GSI, 1991). These rocks are mainly calcarenaceous in nature with basic intrusive and magmatic bodies, while around Helang low to medium grade metamorphic rocks are exposed. The rocks of Garhwal group comprise a very thick pile of low grade meta-sedimentary sequence. These are classified into two geological formations: Pipalkoti Formation and Gulabkoti Formation in the study area. Pipalkoti area falls mainly in Garhwal group of rocks (Fig. 1). Helang and Gulabkoti are located in the quartzite, while Langsi in the dolomite (GSI, 1991). The Alaknanda watershed in the study area is part of Inner Lesser Himalaya with minimum and maximum altitudes of 1100 m and 1580 m above sea level. It is a deeply dissected valley resulting steep valley flanks and narrow crested ridges. The valley flanks have a slope of 70° to 90° and the width of the valley floor is limited to the width of a drainage channel. The study area is dotted with both, hot and cold water springs having a water temperature of 45 °–55 ° C at the surface (GSI, 2008). In Garhwal Himalaya, 62 thermal springs are reported (GSI, 1991) and out of these three thermal springs, are located in the study area, fall in the Helang–Pipalkoti section. The springs are located in the deep sections of Alaknanda valley at Helang, Gulabkoti and Langsi. The temperature of the thermal spring water at Helang, Gulabkoti, and Langsi is 47 °C, 51 °C, and 54.6 °C respectively. Profuse sulphurous gas with gas bubbles was observed at Gulabkoti thermal spring, whereas Langsi thermal water was having a feeble sulphurous smell with normal taste.
The study area lying in the Gulabkoti Formation in the north, consists of mainly quartzite with minor chlorite schist and Pipalkoti Formation in the south, and is made up of slates and dolostones (GSI, 1991). The rocks are highly jointed and sheared. 3. ERT data recording and analysis The Himalayan terrain in the study area is tough and hardly accessible. The acquisition of ERT data requires an accessible line along the profile length. Therefore, it was not possible to carry out ERT profiles with equal intervals and with constant inter-electrode spacing. Seven ERT profiles were recorded in the study area. Out of these, 3 ERT profiles were located in and around the hot water spring zone, another 3 profiles were located at a far distant location from the hot spring area. In addition to these, one ERT profile was located somewhere between the above mentioned two locations. The locations of all ERT profiles are shown in Fig. 1. ERT data were recorded using the Wenner–Schlumberger configuration. The ‘IRIS SYSCAL Junior Switch 72’ resistivity meter was used for data recording. The profiles were recorded with an inter-electrode spacing varying between 2 and 10 m. As the area, in general, was highly resistive and electrical contact of electrodes with the ground was the common problem during ERT data recording. To reduce the electrode contact resistance with the ground, clayey soil with water and some salt were used. For convenience, the ERT profiles are designated by serial numbers generally increasing from south to north. The first electrode of each profile was located at the southern end of the profile and the last electrode was located at the northern end. Based on the geological characteristics and surface features, these profiles may be put in four groups: ERT-1 is the only profile located on the right bank (according to the direction of flow of river from north to south) of Alaknanda River in the southern part of the study area near Hat village. ERT-2 and ERT-3 are located on the left bank in Pipalkoti Formation and are kept in the second group. There was no accessible region close to the river between ERT-3 and ERT-5 on either side of the river because of steep cliffs and a deeper valley. Therefore, to fill the gap, we took one profile ERT-4 on a hill slope approximately 600 m away from the riverbank in Pakhi village, which is kept in the third group. ERT-5 to ERT-7, belong to the fourth group and are located in and around the hot water spring region. Geologically, this region is classified as Gulabkoti Formation. The geophysical measurements were carried out in the close vicinity of the river since the hot springs were generally observed along the river in the study area. In order to compare the resistivity distribution of the hot spring region with that of the surroundings where no hot springs were reported, several sites (according to the availability) were investigated from south to north. To delineate the resistivity-depth image along the profile line using the ERT data, we used the 2D inversion algorithm developed by Günther (2004). The algorithm was implemented for a global regularization scheme using the first order smoothness constraint. Homogeneous half-spaces as starting model were calculated from the mean value of the data. The regularization parameter (λ) is a weight to the model smoothness constraints against the data misfit. In order to determine the optimal λ value, the data misfit functional is plotted versus the model smoothness functional for a wide-ranging λ. The resultant function is called the L-curve (Hansen and O'Leary, 1993). The optimum value of λ, which is used for the present ERT data inversion, is the point where the curvature of the L-curve is maximized. The 2D resistivity-depth images along the profile lines obtained by the inversion of the observed data are shown in Fig. 2 (a, b, c & d). The quality of data fit, for selected profiles (ERT-6 and ERT-7) located in
Fig. 1. Geological map (Valdiya, 1980) of the study area showing the locations of ERT and TEM profiles. The locations of TEM profiles are assigned by the first letter of the site name, whereas ERT profiles are numbered as ERT-1 to ERT-7 from south to north.
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Fig. 2. 2D interpreted resistivity depth sections along the ERT profile lines (a) ERT-1 to 3, (b) ERT-4 and 5, (c) ERT-6 and 7; the label on the y-axis for measured and calculated apparent resistivity pseudosection (Fig. 2(c)) defines the separation factor of the electrodes. The borehole is located at 500 m along the horizontal scale (ERT-1). (d) 2D interpreted resistivity depth section along ERT-5 profile line including topography. For Fig. 2(d), the elevation does not show the altitude above mean sea level, however, it indicates the relative change in topography along the profile line.
the hot spring zone is shown in Fig. 2 (c) in the form of pseudosections. Relative high RMS errors, which are observed along ERT profiles, are most likely due to measurement errors caused by contact resistance problems and hard topography. The profile ERT-1 was recorded in the southern part of the study area on the right bank of Alaknanda River with an inter-electrode spacing of 10 m and a profile length of 710 m. The resistivity of the near surface layer varies within the range of 150–1000 Ωm. Underneath this layer, the resistivity is very high in the range of
1000–3000 Ωm, indicating the presence of the basement rock in the middle part of the profile from 300 to 450 m on the horizontal scale (Fig. 2a). Relatively low resistivity zones on either side of the basement rock are apparently fractured zones (100 to 300 m and 450 to 550 m). These zones appear to be partially water saturated as also seen on the surface as traces of seasonal water channels. The resistivity of these zones varies between 200 and 500 Ωm. For the geological interpretation, the resistivity values are calibrated with the known lithology from the available borehole
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Fig. 2 (continued).
data. The borehole location is shown by a vertical line in Fig. 2(a) at 500 m along the horizontal scale of profile line (ERT-1). The lithological correlation of the resistivity values, extracted from the 2D resistivity-depth model from Fig. 2(a) at the borehole location is shown in Fig. 3. At the borehole location, resistivity values indicate that the overburden was consists of clay with rock fragments of dolomite at top and extended up to 4 m depth. From 4 to 16.5 m depth, river borne material consisting of medium to coarse grained sand, pebbles and cobbles of gneiss, base rock quartzite and dolomite, is present. Lithological correlation can be further generalized along
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the entire ERT-1 section, accordingly, the overburden (up to 16.5 m depth) exhibits the resistivity of more than 500 Ωm (Fig. 2(a)). Below the overburden, weathered grayish black, thinly foliated splintery shale/slate is present up to 41.5 m depth with the resistivity value of 100–300 Ωm. Underneath this layer a dark gray compact shale/slate (calcareous) containing veins and specks of pyrite continues up to the depth of 116 m with a resistivity of 300–500 Ωm. Two profiles (ERT-2 and ERT-3) belonging to the second group are located in Pipalkoti Formation on the left bank of Alaknanda river in an agricultural field at Mayapur and Pipalkoti, respectively. The 2D resistivity-depth models obtained after the inversion of the data at these profiles are shown in Fig. 2(a). Due to the non-availability of a sufficient length, the profile length was reduced to 355 m, interelectrode spacing for these profiles was selected at 5 m. The geoelectrical section along ERT-2 shows approximately layered structure. The top layer is highly resistive with a resistivity of more than 3000 Ωm (Fig. 2(a)) which extends up to the depth of 10–12 m below the ground level. Beneath this layer, the resistivity decreases to some 300–700 Ωm. This relatively low resistivity zone indicates the presence of river borne material in a partially saturated condition. Below this zone, the resistivity increases to 1000–1500 Ωm and indicates the presence of a compact zone. The resistivity-depth section along ERT-3 looks fairly different. It shows a low resistivity layer (20–60 Ωm) at the top of the electrical section extending to the depth of approximately 8 m (Fig. 2(a)). The low resistivity near surface layer most likely is due to the partially saturated fractured zone with fine material. In depth (approximately up to 30 m), these fractures become more compact (less porous) exhibiting the increase in resistivity to 200–700 Ωm within a narrow zone between approximately 120 and 150 m along the profile. The highly resistive
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(2000–5000 Ωm) structures on both sides of the fracture zones are most likely undisturbed bedrock zones. Line ERT-4 belonging to the third group, is located on the left side of Alaknanda River in an agricultural field on a hill slope near Pakhi village. The surface conditions along the profile are characterized by a hard topography and by the existence of large loose boulders and rocks. The latter are reflected in geoelectrical sections by near surface local high resistivity zones at 70 m, 210 m, 240 m and 320 m along the surface (Fig. 2(b)). The resistivity-depth section along the ERT-4 line infers the presence of a near surface low resistivity layer with a resistivity in the range of 100–350 Ωm up to the depth of 20 m. However, at some places, the resistivity is very high (more than 1500 Ωm) that exhibits the presence of boulders and rock mass also exposed on the surface. At greater depths the resistivity generally increases and reaches a range of 400–2500 Ωm. This increase is apparently related to the increase in compactness of material with depth. The fourth group of ERTs (ERT-5 to ERT-7) is located in and around the hot spring region at Tangni, Langsi and Gulabkoti, respectively, where hot springs were reported. The lengths of the profiles were restricted to 142 m with an inter-electrode spacing of 2 m, to 355 m with an inter-electrode spacing of 5 m, and to 210 m with that of 3 m for ERT-5, 6, and 7, respectively. A hot water spring was observed at about 1 km north of the last electrode at Langsi (ERT-6). Another hot spring was observed at Gulabkoti, but due to a tough topography, it was not possible to pass the profile line through the hot water spring. The interpreted models along these profile lines show that the near surface resistivity varies due to the presence of joints and fractures partially saturated with water. For example a low resistivity (~100 Ωm) zone extending up to 6 m depth is observed in ERT-5, along the surface from approximately 75 to 120 m, whereas the rest of the section is highly resistive. The low resistivity structure is associated with the water seepage through fractured zone also observed on the surface. The low resistivity structure at ERT-5 is associated with the shallow water channel. In ERT-6, the low resistivity zone (13–50 Ωm) is observed between approximately 200 m and 250 m (Fig. 2(c)), which appears till the end of the profile with slightly higher resistivities. Further north of ERT-6, a low resistivity zone in the southern end of the profile ERT-7 at Gulabkoti is also observed (Fig. 2(c)). This low electrical resistivity zone is terminating toward the northern end of the profile. It appears that the southern low resistivity zone at ERT-7 is in the continuation of the same low resistivity layer observed at the northern end of the profile ERT-6. The low resistivity structure, observed in ERT-6 and ERT-7, can be related to the hot water channel through fractured rock in the area. The effect of topography on the ERT interpreted sections can be studied by inverting the ERT apparent resistivity sections including topography. In order to observe the effect of topography, ERT-5 to ERT-7 are re-inverted using the Res2dInv code (Loke, 2007) including topography in the inversion. ERT-1 to ERT-4 are carried out on a relatively flat area and therefore, the inclusion of topography in the inversion is not necessary. Fig. 2(d) shows ERT-5 as a representative example for the possible topography effect on the ERT inversion. As can be seen the structure observed along the ERT-5 profile line (Fig. 2 (b)) remains nearly the same in the model including topography (Fig. 2(d)). Note that the color scales are not the same for the Fig. 2(b) and (d). The resistivity distribution derived by the 2D ERT inversion is used in the modeling of TEM data.
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Field data were recorded using the in-loop configuration with approximately 3 A current passing through a transmitter loop (20 × 20 m 2) and a receiver loop (5 × 5 m 2) was placed at the center of the transmitter loop. The data were recorded at 21 stations distributed along 7 profiles in the study area. The locations of these profiles are shown in Fig. 1. The distance between two adjacent stations on a profile was 20 m and the maximum length of the profile was limited to 40–100 m. Due to the rugged terrain and a hardly accessible topography, it was not possible to record a large number of stations on a single profile. Fig. 4 shows the general character of raw data from the study area. It is interesting to note that a sign reversal in TEM data is consistently observed at all sites. In the geophysical literature, the sign reversal in TEM data is explained either as an IP (Induced Polarization) effect or by a 2D/3D electrical structure (Newman, 1989; Smith and West, 1988; Weidelt, 1982). In coincident-loop measurements, the response of a ground whose properties are linear and independent of frequency is purely positive (Weidelt, 1982). Very small negative transients observed in coincidentloop measurements have been explained by polarization currents (Spies, 1980). However, to model these negative transients successfully with either half-space or with buried conductors, the polarizability should be exceptionally large (Flis, 1987; Lee, 1975; Lee and Lewis, 1974; Morrison et al., 1969). Another approach, to explain the sign reversal in LOTEM (longoffset transient electromagnetic) data is to consider the 2D/3D electrical structure. Newman (1989) investigated the effects of near surface conductors beneath and remote from a grounded-wire transmitter. It was observed that the conductor is detectable only at early times when it is close to a receiver. During these times the conductor can produce responses with sign reversals. Hördt et al. (1992) explained the observed sign reversal in LOTEM data by considering the laterally inhomogeneous subsurface. Hördt and Müller (2000) and Commer et al. (2006) used topography to model the observed sign-reversals in the field data. Recently a sign reversal has been observed in the SHOTEM measurements by Goldman et al. (2009). Sign reversal in IP effect starts at late times, generally later than 100 μs (Tezkan, 1999). However, the sign reversals observed in all our measurements occur at 10–20 μs. In addition, the study area is characterized by hard rock terrain, in which the presence of polarizable body is not expected. Therefore, the IP effect is not considered as a cause of sign reversals in our TEM data. Thus, sign reversal in our TEM responses may either be due to 2D/3D inductive effects or by the surface topographic features.
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4. TEM data recording and analysis TEM data were collected using the NanoTEM (Zonge Engineering and Research Organization Inc., 2000) system. It is a time-domain electromagnetic data acquisition system, which facilitates TEM data acquisition for different transmitter-receiver loop configurations.
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To explain sign reversal in our data we first modeled topographic details by computing 2D TEM responses for a base model consisting of topographic features. The finite-difference code by Druskin and Knizhnermann (1988) based on the Spectral Lanczos Decomposition Method (SLDM) was used for modeling. 4.1. 2D TEM modeling A generalized 2D model with topography was constructed by taking into account the geomorphological details (Fig. 5). Subsequently, a numerical experiment was conducted for grid validation by comparing the responses of homogeneous half-space and 1D layered model, computed using SLDM and 1D codes. For an optimum grid size both responses (computed from 1D code and SLDM code) are closely matching in the time range recorded in our data set. After the grid validation experiment, an initial model (Fig. 5) was used for 2D TEM response computations. It has been observed that the model is capable of generating the response with sign reversal by incorporating topographical features in the vicinity of transmitter loop. Further, the effect of resistivity in and around the transmitter loop has been studied. It has also been noticed that the time at which the sign reversal is observed is shifting to earlier times with the increase in the resistivity of the homogeneous medium in and around the transmitter loop. Fig. 6 shows the comparison of the computed and observed responses from the study area. Synthetic responses were computed for background resistivity of 300 Ωm for Mayapur, 500 Ωm for Tangni, and 600 Ωm for Gulabkoti village. Fig. 6(a, b & c) shows the comparison of the 2D modeling result with the field data from Mayapur, Langsi, and Gulabkoti sites, respectively. One can see that in the present work we are successful in reproducing the general behavior and the time location of sign reversals in the observed data at all sites. However, at this stage we could not achieve the best fitted model for the data. From the numerical experimentation, we have reached to the conclusion that the best model can only be obtained by increasing more data density and by an extensive 3D modeling, which is outside the scope of the present paper. 5. Discussion of geophysical results and laboratory analyses ERT and TEM data are used in the present investigation to study the electrical structure of the near surface (b200 m) in the MCT zone of Himalayan region. The electrical resistivity of the geological formation in the area is controlled by the amount of fracturing, water content, temperature, and weathered zones saturation. The
southern part of the study area (Pipalkoti) is characterized by top weathered layer in partial or complete water saturation. Thickness of this zone varies between 10 and 20 m and is characterized by a resistivity of about 100 Ωm. This zone extends up to Pakhi (ERT-4), where the resistivity of the weathered layer increases up to 400 Ωm. This is due to the presence of large size boulder molasse which can also be seen on the surface. Further, north to Pakhi at the investigated sites: Tangni, Langsi, Gulabkoti and Helang weathering is generally absent and the formation is characterized by Gulabkoti formation composed of quartzite with inner chlorite schist (GSI, 1991) and dolomite at Langsi. The rocks are highly fractured and hot water springs emerge at Gulabkoti and Helang around the observation sites. The compact rock mass is resistive (N1000 Ωm) at Tangni (ERT-5). Local small scale fractured saturated zones are characterized by low resistivity (b200 Ωm). A very low resistivity (b50 m) is also observed in the zones where hot/cold water springs emerge (ERT-5, 6, 7). These zones are the characteristics of the underground water channels through the minor/major fracturing. A limited success has also been obtained in the TEM modeling of the data. General character and sign reversal in TEM data have been successfully reproduced by topographic modeling. TEM modeling results infer that the background resistivity of the rock mass in the southern part is lower than that in the northern part and this is also consistent with the ERT results. The measured electrical conductivity of the water samples collected from the hot springs in the Helang area varies between 628 μmho/cm and 648 μmho/cm on the right and left bank of Alaknanda river. This value is 382 μmho/cm measured for the normal nearby river water. The electrical conductivity of precipitation water (rainwater) collected from the Pipalkoti area is 46 μmho/cm. The water of the hot water spring, which has a higher electrical conductivity (628–648 μmho/cm) than fresh meteoric and river water, is rich in bicarbonates and sulphate, indicating a meteoric source. After its percolation the water has mixed with ionic solid from the earth rock mass during its transit and residence in the localized fracture zones saturated with the hot fluid. The MCT zone falls in a high heat flow area, a majority of hot springs are concentrated around this zone. Israil et al. (2008) reported high heat flow (130 ± 30 mW/m 2) and high temperature gradient (60 ° ± 20 ° C/km) in the MCT zone, whereas the foot hill Himalayan belts show low heat flow (41 ± 10 mW/m 2) and low temperature gradient (17 ° ± 5 ° C/km) as published in GSI (1991). This suggests that the subsurface temperature is elevated in the MCT zone. The hot water oozing out from the subsurface must be either of deeper hot
Fig. 5. 2D model used for the interpretation of TEM data.
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source origin or of meteoric origin passing through relatively shallow subsurface hot zones. The low resistivity (~ 50 Ωm) zones at shallow depths are associated with the hot water bearing zones. The resistive formation above the low resistivity zone is acting as cap rock in the entire region. Hence, except through fracture, there appears no direct hydraulic connection between the low resistivity hot water zones and near surface formations. The zone is extended laterally around MCT region.
6. Conclusions The subsurface electrical structure at shallow depth (b200 m) is delineated by ERT and TEM profiles in the Central Himalaya region. Electrical models derived from these data are interpreted in terms of rock fracture and their water saturation based on the general geological inputs available for the area. The compact rock mass is exhibited by high resistivity (N1000 Ωm); fractured and partially
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fractured zones are indicated by low resistivity formations (b50 to 100 Ωm). A very low resistivity (b50 Ωm) zone at shallow depth is interpreted as water bearing fractured zone from which water emerges as normal water spring at surface. The electrical models derived from ERT indicate that the area is intensively fractured. These fractures are generally shallow in nature, except for some places like at the Helang area where fractures might have gone deeper and meteoric water flowing through these fractures from the ground surface reaches deeper levels and becomes hot water due to the elevated temperature. Such zones have become the source of the hot water springs in the area namely: Gulabkoti and Langsi, which is one possible interpretation of the hot water springs in the area. In the study area it has been observed that in addition to this deep hot water bearing fractured zones, there exists a number of shallow water bearing fractured zones. These zones are reflected in the ERT results as low resistivity (~50 Ωm) zones in the upper part of the otherwise high resistivity (N1000 Ωm) rock mass (Tangni). These conclusions are based on the limited geophysical data recorded, available information and geological inputs for the study area. The outcome of the present investigations may be further updated or revised by adding more geophysical/geological data and by incorporating 3D modeling and inversion in future. References Baranwal, V.C., Sharma, S.P., 2006. Integrated geophysical studies in the East-Indian geothermal province. Pure and Applied Geophysics 163, 209–227. Caglar, I., Demirorer, M., 1999. Geothermal exploration using geoelectric methods in Kestanbol, Turkey. Geothermics 28, 803–819. Commer, M., Helwig, S.L., Hördt, A., Scholl, C., Tezkan, B., 2006. New results on the resistivity structure of Merapi Volcano (Indonesia), derived from three-dimensional restricted inversion of long-offset transient electromagnetic data. Geophysical Journal International 167, 1172–1187. Druskin, V.L., Knizhnermann, L.A., 1988. A spectral semi-discrete method for the numerical solution of 3 d nonstationary problems in electrical prospecting. Physics of the Solid Earth 24, 641–648. Flis, M., 1987. IP effects in 3-D TEM data — theory and case histories. Proceeding of the 5th Australian SEG Conference, pp. 55–58. Goldman, M., Levi, E., Kafri, U., Herut, B., Tibor, G., Tezkan, B., Gurk, M., Bergers, R., Yogeshwar, P., 2009. Detection of fresh groundwater bodies within the Mediterranean sub-marine coastal aquifers offshore Israel using marine geoelectromagnetic methods: http://www.marelec.co.uk/conference/MarelecAbstracts.pdf. GSI, 1991. Geothermal Atlas of India, Geological Survey of India. Special Publication 19 143 pp. GSI, 2008. Geological Survey of India, Northern Region. Günther, T., 2004. Inversion methods and resolution analysis for the 2D/3D reconstruction of resistivity structures from DC measurements. Ph. D. Thesis, Technische Universität Bergakademie Freiberg, Germany.
Hansen, P.C., O'Leary, D.P., 1993. The use of the L-curve in the regularization of discrete ill posed problems. SIAM Journal on Scientific Computing 14, 1487–1503. Hördt, A., Müller, M., 2000. Understanding LOTEM data from mountainous terrain. Geophysics 65 (4), 1113–1123. Hördt, A., Druskin, V.L., Knizhnerman, L.A., Strack, K.M., 1992. Interpretation of 3-D effects on longoffset transient electromagnetic (LOTEM) soundings in the Münsterland area/Germany. Geophysics 57, 1127–1137. Israil, M., Tyagi, D.K., Gupta, P.K., Sri Niwas, 2008. Magnetotelluric investigations for imaging electrical structure of Garhwal Himalayan corridor, Uttarakhand, India. Journal of Earth System Science 117 (3), 189–200. Lee, T., 1975. Sign reversals in the transient method of electrical prospecting (one-loop version). Geophysical Prospecting 23, 653–662. Lee, T., Lewis, R., 1974. Transient EM response of a large loop on a layered ground. Geophysical Prospecting 22, 430–444. Loke, M.H., 2007. RES2DINV ver. 3.56 for Windows 98/Me/2000/NT/XP; Rapid 2-D Resistivity & IP inversion using the least-squares method. Geoelectrical Imaging 2D & 3D. Geotomo Software, Malaysia. July 2007, http://www.geoelectrical.com. Majumdar, R.K., Majumdar, N., Mukherjee, A.L., 2000. Geoelectric investigations in Bakreswar geothermal area, West Bengal, India. Journal of Applied Geophysics 45 (3), 187–202. Morrison, H.F., Phillips, R.J., O'brien, D.P., 1969. Quantitative interpretation of transient electromagnetic fields over a layered half space. Geophysical Prospecting 17, 82–101. Newman, G.A., 1989. Deep transient electromagnetic soundings with a grounded source over near-surface conductors. Geophysical Journal International 98, 587–601. Pellerin, L., Johnston, J.M., Hohmann, G.W., 1996. A numerical evaluation of electromagnetic methods in geothermal exploration. Geophysics 61 (1), 121–130. Rashed, M., Kawamura, R., Nemoto, H., Miyata, T., Nakagawa, K., 2003. Ground penetrating radar investigations across the Uemachi fault, Osaka, Japan. Journal of Applied Geophysics 53, 63–75. Savin, C., Ritz, M., Join, J., Bachelery, P., 2001. Hydrothermal system mapped by CSAMT on Karthala volcano, Grande Comore Island, Indian Ocean. Journal of Applied Geophysics 48, 143–152. Seeber, L., Armbruster, J., Quittmeyer, R.C., 1981. Seismicity and continental subduction in the Himalayan arc. In: Gupta, H., Delany, F. (Eds.), Zagros-Hindukush-Himalaya geodynamic evolution. Geodynamics Series, 3. American Geophysical Union, p. 215. Smith, R.S., West, G.E., 1988. Inductive interaction between polarizable conductors: an explanation of a negative coincident loop transient electromagnetic response. Geophysics 53, 677–690. Spies, B.R., 1980. A field occurrence of sign reversals with the transient electromagnetic method. Geophysical Prospecting 28, 620–632. Tezkan, B., 1999. A review of environmental applications of quasi-stationary electromagnetic techniques. Surveys in Geophysics 20, 279–308. Valdiya, K.S., 1980. Geology of Kumaun Lesser Himalaya, Dehra Dun, India: Wadia Institute of Himalayan Geology. pp. 291. Weidelt, P., 1982. Response characteristics of coincident loop transient electromagnetic systems. Geophysics 47 (9), 1325–1330. Wright, P.M., Ward, S.H., Ross, H.P., West, R.C., 1985. State-of-the-art geophysical exploration for geothermal resources. Geophysics 50 (12), 2666–2699. Yasukawa, K., Mogi, T., Widarto, D., Ehara, S., 2003. Numerical modeling of a hydrothermal system around Waita volcano, Kyushu, Japan, based on resistivity and self-potential survey results. Geothermics 32, 21–46. Zonge Engineering, Research Organization Inc., 2000. Zonge GDP32II Multifunction Receiver Operation Manual. Zonge Engineering and Research Organization Inc., Tucson, Arizona.
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Journal of Applied Geophysics j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / j a p p g e o
Combined electrical and electromagnetic imaging of hot fluids within fractured rock in rugged Himalayan terrain Kumari Sudha a, c,⁎, Bülent Tezkan a, Mohammad Israil b, 1, Jagdish Rai c a b c
Institute of Geophysics and Meteorology, University of Cologne, Germany Department of Earth Sciences, Indian Institute of Technology Roorkee, Roorkee-247667, India Department of Physics, Indian Institute of Technology Roorkee, Roorkee-247667, India
a r t i c l e
i n f o
Article history: Received 30 January 2010 Accepted 3 June 2011 Available online 15 June 2011 Keywords: Electrical resistance tomography Transient electromagnetic Sign reversal 2D–3D effects
a b s t r a c t Integrated electrical resistance tomography (ERT) and short-offset transient electromagnetic (TEM) measurements were carried out to investigate a geothermal area in the Main Central Thrust (MCT) zone of Garhwal Himalayan region, India. The study area is located around Helang on either side of Alaknanda River and it is dotted with hot water springs with water temperature of 45°–55 °C emerging at the surface. To assess the geothermal potential and its lateral and vertical extension in and around the hot water springs in the study area, 7 ERT profiles and 21 TEM stations on 7 profiles were established around the hot water spring and at far distant locations. The 2D inversion of ERT data indicates a low resistivity (b 50 Ωm) zone in the vicinity of hot springs, which appears to be associated with an underground water channel through the fractured rock. The bedrock resistivity is very high (N 1000 Ωm) whereas the resistivity of the weathered near surface soil at a far distant location from the hot spring is low (b100 Ωm) again. A common feature of all TEM data is the sign reversal observed at roughly 10 μs. The consistent sign reversal in all TEM data indicates the existence of the multi-dimensionality of the geoelectrical structure. Therefore, the TEM data were treated by using the SLDM (Spectral Lanczos Decomposition Method) 2D/3D forward modeling code based on the finite difference algorithm. The resistivity structure obtained from ERT data was used as an input for the modeling of TEM data. Based on the joint analysis of the ERT and TEM data it can be inferred that geothermal anomalies associated with the hot spring in the MCT zone are a local feature appearing as a low resistivity zone (b 50 Ωm) at shallow depth (b100 m) in the vicinity of the hot spring region. © 2011 Elsevier B.V. All rights reserved.
1. Introduction The rationale for the use of ERT and TEM methods is that a high temperature geothermal zone is manifested as low resistivity anomaly in the geoelectrical model derived from ERT and TEM responses. Many authors have used different geoelectric and electromagnetic (EM) methods to study geothermal resource potentials in various parts of world (Pellerin et al., 1996; Wright et al., 1985). The target for the exploration of convective hydrothermal resources is usually a region composed of faults and fractures filled with thermal fluids and hydrothermal alteration products. The lowresistivity zone produced by the brines and clays capping of a geothermal system provides a feature that should be easily detectable by EM methods (Wright et al., 1985). The size and the low resistivity
⁎ Corresponding author at: Institute of Geophysics and Meteorology, University of Cologne, Albertus-Magnus-Platz, D-50923, Cologne, Germany. Tel.: +49 221 4706127. E-mail addresses: [email protected] (K. Sudha), [email protected] (M. Israil). 1 Tel.: + 91 1332 285078; fax: +91 1332 273560. 0926-9851/$ – see front matter © 2011 Elsevier B.V. All rights reserved. doi:10.1016/j.jappgeo.2011.06.002
of the clay cap associated with a geothermal system create a target well suited for EM methods. Pellerin et al. (1996) numerically evaluated four EM techniques for the use in geothermal exploration: magnetotellurics (MT), controlled source audio magnetotellurics (CSAMT), long-offset transient EM (LOTEM), and short-offset transient EM (SHOTEM). They concluded that a combination of CSAMT and SHOTEM measurements appeared most appropriate for the delineation of the clay cap. The use of electrical and electromagnetic methods in the characterization of a thermal reservoir is well documented in the literature (Caglar and Demirorer, 1999; Majumdar et al., 2000; Rashed et al., 2003; Savin et al., 2001; Yasukawa et al., 2003). Caglar and Demirorer (1999) studied a geothermal area in Kestanbol, Turkey, to investigate the fault zones using self-potential and resistivity surveys. Based on the self-potential map, the fault around Kestanbol showed a large potential associated with the active geothermal area. Rashed et al. (2003) conducted ground penetrating radar (GPR) survey to investigate the shallow geological structures in the vicinity of the fault zones across the Uemachi fault, Osaka, Japan. The interpreted GPR profiles showed the location and geometry of a subsurface fault scarp having a visible expression at the surface as well as several subsurface fault strands. Baranwal and Sharma (2006) used
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vertical electrical sounding (VES), very low frequency (VLF) EM and self-potential (SP) measurements to characterize the geothermal area around a hot spring in the Nayagarh district, Orissa, India that lies in the East Indian geothermal province. With the objective to ascertain the origin and subsurface geometrical configuration of geothermal springs in the MCT zone of Central Himalaya, we conducted ERT and TEM measurements and analyzed the electrical structure of the area. The present paper briefly discusses the geology of the study area followed by a detail description of the data recording, their analysis and interpretation. A possible correlation of the geoelectrical structure with the subsurface geothermal anomalies has also been done.
2. Geology of the study area The study area is located in Central Himalayan region near Main Central Thrust (MCT) zone, closed to Alaknanda River, in Uttarakhand, India. The Himalayan mountain belt is formed as a result of continental collision tectonics and under-thrusting of the Indian plate beneath the Eurasian plate. In this process the leading face of the upper brittle portion of the subducting Indian crust has been sliced and stacked up southwards to form the entire Himalayan Mountain. The various thrusts are the elements of this geodynamical process (Seeber et al., 1981). In general Himalaya, from south to north, can be divided into three major physiographic divisions namely; Outer Himalaya, Lesser Himalaya and Higher Himalaya. The Lesser Himalaya occupying a larger area is divisible into Outer Lesser Himalaya and Inner Lesser Himalaya. The study area is located in Inner Lesser Himalaya near MCT zone, closed to Alaknanda River, in district Chamoli, Uttarakhand, India. Geologically the area is characterized by a number of thrust sheets piled up one over another (GSI, 1991). As a result, local and subregional faults and shear zones are commonly seen in the region. Regionally the rocks of the area have been classified into two broad tectonic units: Central Crystalline in the north and Garhwal in the south separated by a northerly dipping tectonic plane referred as MCT (GSI, 1991). These rocks are mainly calcarenaceous in nature with basic intrusive and magmatic bodies, while around Helang low to medium grade metamorphic rocks are exposed. The rocks of Garhwal group comprise a very thick pile of low grade meta-sedimentary sequence. These are classified into two geological formations: Pipalkoti Formation and Gulabkoti Formation in the study area. Pipalkoti area falls mainly in Garhwal group of rocks (Fig. 1). Helang and Gulabkoti are located in the quartzite, while Langsi in the dolomite (GSI, 1991). The Alaknanda watershed in the study area is part of Inner Lesser Himalaya with minimum and maximum altitudes of 1100 m and 1580 m above sea level. It is a deeply dissected valley resulting steep valley flanks and narrow crested ridges. The valley flanks have a slope of 70° to 90° and the width of the valley floor is limited to the width of a drainage channel. The study area is dotted with both, hot and cold water springs having a water temperature of 45 °–55 ° C at the surface (GSI, 2008). In Garhwal Himalaya, 62 thermal springs are reported (GSI, 1991) and out of these three thermal springs, are located in the study area, fall in the Helang–Pipalkoti section. The springs are located in the deep sections of Alaknanda valley at Helang, Gulabkoti and Langsi. The temperature of the thermal spring water at Helang, Gulabkoti, and Langsi is 47 °C, 51 °C, and 54.6 °C respectively. Profuse sulphurous gas with gas bubbles was observed at Gulabkoti thermal spring, whereas Langsi thermal water was having a feeble sulphurous smell with normal taste.
The study area lying in the Gulabkoti Formation in the north, consists of mainly quartzite with minor chlorite schist and Pipalkoti Formation in the south, and is made up of slates and dolostones (GSI, 1991). The rocks are highly jointed and sheared. 3. ERT data recording and analysis The Himalayan terrain in the study area is tough and hardly accessible. The acquisition of ERT data requires an accessible line along the profile length. Therefore, it was not possible to carry out ERT profiles with equal intervals and with constant inter-electrode spacing. Seven ERT profiles were recorded in the study area. Out of these, 3 ERT profiles were located in and around the hot water spring zone, another 3 profiles were located at a far distant location from the hot spring area. In addition to these, one ERT profile was located somewhere between the above mentioned two locations. The locations of all ERT profiles are shown in Fig. 1. ERT data were recorded using the Wenner–Schlumberger configuration. The ‘IRIS SYSCAL Junior Switch 72’ resistivity meter was used for data recording. The profiles were recorded with an inter-electrode spacing varying between 2 and 10 m. As the area, in general, was highly resistive and electrical contact of electrodes with the ground was the common problem during ERT data recording. To reduce the electrode contact resistance with the ground, clayey soil with water and some salt were used. For convenience, the ERT profiles are designated by serial numbers generally increasing from south to north. The first electrode of each profile was located at the southern end of the profile and the last electrode was located at the northern end. Based on the geological characteristics and surface features, these profiles may be put in four groups: ERT-1 is the only profile located on the right bank (according to the direction of flow of river from north to south) of Alaknanda River in the southern part of the study area near Hat village. ERT-2 and ERT-3 are located on the left bank in Pipalkoti Formation and are kept in the second group. There was no accessible region close to the river between ERT-3 and ERT-5 on either side of the river because of steep cliffs and a deeper valley. Therefore, to fill the gap, we took one profile ERT-4 on a hill slope approximately 600 m away from the riverbank in Pakhi village, which is kept in the third group. ERT-5 to ERT-7, belong to the fourth group and are located in and around the hot water spring region. Geologically, this region is classified as Gulabkoti Formation. The geophysical measurements were carried out in the close vicinity of the river since the hot springs were generally observed along the river in the study area. In order to compare the resistivity distribution of the hot spring region with that of the surroundings where no hot springs were reported, several sites (according to the availability) were investigated from south to north. To delineate the resistivity-depth image along the profile line using the ERT data, we used the 2D inversion algorithm developed by Günther (2004). The algorithm was implemented for a global regularization scheme using the first order smoothness constraint. Homogeneous half-spaces as starting model were calculated from the mean value of the data. The regularization parameter (λ) is a weight to the model smoothness constraints against the data misfit. In order to determine the optimal λ value, the data misfit functional is plotted versus the model smoothness functional for a wide-ranging λ. The resultant function is called the L-curve (Hansen and O'Leary, 1993). The optimum value of λ, which is used for the present ERT data inversion, is the point where the curvature of the L-curve is maximized. The 2D resistivity-depth images along the profile lines obtained by the inversion of the observed data are shown in Fig. 2 (a, b, c & d). The quality of data fit, for selected profiles (ERT-6 and ERT-7) located in
Fig. 1. Geological map (Valdiya, 1980) of the study area showing the locations of ERT and TEM profiles. The locations of TEM profiles are assigned by the first letter of the site name, whereas ERT profiles are numbered as ERT-1 to ERT-7 from south to north.
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Fig. 2. 2D interpreted resistivity depth sections along the ERT profile lines (a) ERT-1 to 3, (b) ERT-4 and 5, (c) ERT-6 and 7; the label on the y-axis for measured and calculated apparent resistivity pseudosection (Fig. 2(c)) defines the separation factor of the electrodes. The borehole is located at 500 m along the horizontal scale (ERT-1). (d) 2D interpreted resistivity depth section along ERT-5 profile line including topography. For Fig. 2(d), the elevation does not show the altitude above mean sea level, however, it indicates the relative change in topography along the profile line.
the hot spring zone is shown in Fig. 2 (c) in the form of pseudosections. Relative high RMS errors, which are observed along ERT profiles, are most likely due to measurement errors caused by contact resistance problems and hard topography. The profile ERT-1 was recorded in the southern part of the study area on the right bank of Alaknanda River with an inter-electrode spacing of 10 m and a profile length of 710 m. The resistivity of the near surface layer varies within the range of 150–1000 Ωm. Underneath this layer, the resistivity is very high in the range of
1000–3000 Ωm, indicating the presence of the basement rock in the middle part of the profile from 300 to 450 m on the horizontal scale (Fig. 2a). Relatively low resistivity zones on either side of the basement rock are apparently fractured zones (100 to 300 m and 450 to 550 m). These zones appear to be partially water saturated as also seen on the surface as traces of seasonal water channels. The resistivity of these zones varies between 200 and 500 Ωm. For the geological interpretation, the resistivity values are calibrated with the known lithology from the available borehole
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Fig. 2 (continued).
data. The borehole location is shown by a vertical line in Fig. 2(a) at 500 m along the horizontal scale of profile line (ERT-1). The lithological correlation of the resistivity values, extracted from the 2D resistivity-depth model from Fig. 2(a) at the borehole location is shown in Fig. 3. At the borehole location, resistivity values indicate that the overburden was consists of clay with rock fragments of dolomite at top and extended up to 4 m depth. From 4 to 16.5 m depth, river borne material consisting of medium to coarse grained sand, pebbles and cobbles of gneiss, base rock quartzite and dolomite, is present. Lithological correlation can be further generalized along
101 100
102
103
104
101
102
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104 Fig. 3. Correlation of borehole lithology with the interpreted resistivity values derived from 2D model in Fig. 2(a) at borehole location i.e. along ERT-1.
the entire ERT-1 section, accordingly, the overburden (up to 16.5 m depth) exhibits the resistivity of more than 500 Ωm (Fig. 2(a)). Below the overburden, weathered grayish black, thinly foliated splintery shale/slate is present up to 41.5 m depth with the resistivity value of 100–300 Ωm. Underneath this layer a dark gray compact shale/slate (calcareous) containing veins and specks of pyrite continues up to the depth of 116 m with a resistivity of 300–500 Ωm. Two profiles (ERT-2 and ERT-3) belonging to the second group are located in Pipalkoti Formation on the left bank of Alaknanda river in an agricultural field at Mayapur and Pipalkoti, respectively. The 2D resistivity-depth models obtained after the inversion of the data at these profiles are shown in Fig. 2(a). Due to the non-availability of a sufficient length, the profile length was reduced to 355 m, interelectrode spacing for these profiles was selected at 5 m. The geoelectrical section along ERT-2 shows approximately layered structure. The top layer is highly resistive with a resistivity of more than 3000 Ωm (Fig. 2(a)) which extends up to the depth of 10–12 m below the ground level. Beneath this layer, the resistivity decreases to some 300–700 Ωm. This relatively low resistivity zone indicates the presence of river borne material in a partially saturated condition. Below this zone, the resistivity increases to 1000–1500 Ωm and indicates the presence of a compact zone. The resistivity-depth section along ERT-3 looks fairly different. It shows a low resistivity layer (20–60 Ωm) at the top of the electrical section extending to the depth of approximately 8 m (Fig. 2(a)). The low resistivity near surface layer most likely is due to the partially saturated fractured zone with fine material. In depth (approximately up to 30 m), these fractures become more compact (less porous) exhibiting the increase in resistivity to 200–700 Ωm within a narrow zone between approximately 120 and 150 m along the profile. The highly resistive
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(2000–5000 Ωm) structures on both sides of the fracture zones are most likely undisturbed bedrock zones. Line ERT-4 belonging to the third group, is located on the left side of Alaknanda River in an agricultural field on a hill slope near Pakhi village. The surface conditions along the profile are characterized by a hard topography and by the existence of large loose boulders and rocks. The latter are reflected in geoelectrical sections by near surface local high resistivity zones at 70 m, 210 m, 240 m and 320 m along the surface (Fig. 2(b)). The resistivity-depth section along the ERT-4 line infers the presence of a near surface low resistivity layer with a resistivity in the range of 100–350 Ωm up to the depth of 20 m. However, at some places, the resistivity is very high (more than 1500 Ωm) that exhibits the presence of boulders and rock mass also exposed on the surface. At greater depths the resistivity generally increases and reaches a range of 400–2500 Ωm. This increase is apparently related to the increase in compactness of material with depth. The fourth group of ERTs (ERT-5 to ERT-7) is located in and around the hot spring region at Tangni, Langsi and Gulabkoti, respectively, where hot springs were reported. The lengths of the profiles were restricted to 142 m with an inter-electrode spacing of 2 m, to 355 m with an inter-electrode spacing of 5 m, and to 210 m with that of 3 m for ERT-5, 6, and 7, respectively. A hot water spring was observed at about 1 km north of the last electrode at Langsi (ERT-6). Another hot spring was observed at Gulabkoti, but due to a tough topography, it was not possible to pass the profile line through the hot water spring. The interpreted models along these profile lines show that the near surface resistivity varies due to the presence of joints and fractures partially saturated with water. For example a low resistivity (~100 Ωm) zone extending up to 6 m depth is observed in ERT-5, along the surface from approximately 75 to 120 m, whereas the rest of the section is highly resistive. The low resistivity structure is associated with the water seepage through fractured zone also observed on the surface. The low resistivity structure at ERT-5 is associated with the shallow water channel. In ERT-6, the low resistivity zone (13–50 Ωm) is observed between approximately 200 m and 250 m (Fig. 2(c)), which appears till the end of the profile with slightly higher resistivities. Further north of ERT-6, a low resistivity zone in the southern end of the profile ERT-7 at Gulabkoti is also observed (Fig. 2(c)). This low electrical resistivity zone is terminating toward the northern end of the profile. It appears that the southern low resistivity zone at ERT-7 is in the continuation of the same low resistivity layer observed at the northern end of the profile ERT-6. The low resistivity structure, observed in ERT-6 and ERT-7, can be related to the hot water channel through fractured rock in the area. The effect of topography on the ERT interpreted sections can be studied by inverting the ERT apparent resistivity sections including topography. In order to observe the effect of topography, ERT-5 to ERT-7 are re-inverted using the Res2dInv code (Loke, 2007) including topography in the inversion. ERT-1 to ERT-4 are carried out on a relatively flat area and therefore, the inclusion of topography in the inversion is not necessary. Fig. 2(d) shows ERT-5 as a representative example for the possible topography effect on the ERT inversion. As can be seen the structure observed along the ERT-5 profile line (Fig. 2 (b)) remains nearly the same in the model including topography (Fig. 2(d)). Note that the color scales are not the same for the Fig. 2(b) and (d). The resistivity distribution derived by the 2D ERT inversion is used in the modeling of TEM data.
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Field data were recorded using the in-loop configuration with approximately 3 A current passing through a transmitter loop (20 × 20 m 2) and a receiver loop (5 × 5 m 2) was placed at the center of the transmitter loop. The data were recorded at 21 stations distributed along 7 profiles in the study area. The locations of these profiles are shown in Fig. 1. The distance between two adjacent stations on a profile was 20 m and the maximum length of the profile was limited to 40–100 m. Due to the rugged terrain and a hardly accessible topography, it was not possible to record a large number of stations on a single profile. Fig. 4 shows the general character of raw data from the study area. It is interesting to note that a sign reversal in TEM data is consistently observed at all sites. In the geophysical literature, the sign reversal in TEM data is explained either as an IP (Induced Polarization) effect or by a 2D/3D electrical structure (Newman, 1989; Smith and West, 1988; Weidelt, 1982). In coincident-loop measurements, the response of a ground whose properties are linear and independent of frequency is purely positive (Weidelt, 1982). Very small negative transients observed in coincidentloop measurements have been explained by polarization currents (Spies, 1980). However, to model these negative transients successfully with either half-space or with buried conductors, the polarizability should be exceptionally large (Flis, 1987; Lee, 1975; Lee and Lewis, 1974; Morrison et al., 1969). Another approach, to explain the sign reversal in LOTEM (longoffset transient electromagnetic) data is to consider the 2D/3D electrical structure. Newman (1989) investigated the effects of near surface conductors beneath and remote from a grounded-wire transmitter. It was observed that the conductor is detectable only at early times when it is close to a receiver. During these times the conductor can produce responses with sign reversals. Hördt et al. (1992) explained the observed sign reversal in LOTEM data by considering the laterally inhomogeneous subsurface. Hördt and Müller (2000) and Commer et al. (2006) used topography to model the observed sign-reversals in the field data. Recently a sign reversal has been observed in the SHOTEM measurements by Goldman et al. (2009). Sign reversal in IP effect starts at late times, generally later than 100 μs (Tezkan, 1999). However, the sign reversals observed in all our measurements occur at 10–20 μs. In addition, the study area is characterized by hard rock terrain, in which the presence of polarizable body is not expected. Therefore, the IP effect is not considered as a cause of sign reversals in our TEM data. Thus, sign reversal in our TEM responses may either be due to 2D/3D inductive effects or by the surface topographic features.
10-4 10-5 10-6 10-7 10-8 10-9
4. TEM data recording and analysis TEM data were collected using the NanoTEM (Zonge Engineering and Research Organization Inc., 2000) system. It is a time-domain electromagnetic data acquisition system, which facilitates TEM data acquisition for different transmitter-receiver loop configurations.
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Fig. 4. The raw data from different zones of the study area (extreme south part: Mayapur site, central part: Tangni, Gulabkoti and extreme north part: Helang). These transients are showing the similar nature of data in different zones.
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To explain sign reversal in our data we first modeled topographic details by computing 2D TEM responses for a base model consisting of topographic features. The finite-difference code by Druskin and Knizhnermann (1988) based on the Spectral Lanczos Decomposition Method (SLDM) was used for modeling. 4.1. 2D TEM modeling A generalized 2D model with topography was constructed by taking into account the geomorphological details (Fig. 5). Subsequently, a numerical experiment was conducted for grid validation by comparing the responses of homogeneous half-space and 1D layered model, computed using SLDM and 1D codes. For an optimum grid size both responses (computed from 1D code and SLDM code) are closely matching in the time range recorded in our data set. After the grid validation experiment, an initial model (Fig. 5) was used for 2D TEM response computations. It has been observed that the model is capable of generating the response with sign reversal by incorporating topographical features in the vicinity of transmitter loop. Further, the effect of resistivity in and around the transmitter loop has been studied. It has also been noticed that the time at which the sign reversal is observed is shifting to earlier times with the increase in the resistivity of the homogeneous medium in and around the transmitter loop. Fig. 6 shows the comparison of the computed and observed responses from the study area. Synthetic responses were computed for background resistivity of 300 Ωm for Mayapur, 500 Ωm for Tangni, and 600 Ωm for Gulabkoti village. Fig. 6(a, b & c) shows the comparison of the 2D modeling result with the field data from Mayapur, Langsi, and Gulabkoti sites, respectively. One can see that in the present work we are successful in reproducing the general behavior and the time location of sign reversals in the observed data at all sites. However, at this stage we could not achieve the best fitted model for the data. From the numerical experimentation, we have reached to the conclusion that the best model can only be obtained by increasing more data density and by an extensive 3D modeling, which is outside the scope of the present paper. 5. Discussion of geophysical results and laboratory analyses ERT and TEM data are used in the present investigation to study the electrical structure of the near surface (b200 m) in the MCT zone of Himalayan region. The electrical resistivity of the geological formation in the area is controlled by the amount of fracturing, water content, temperature, and weathered zones saturation. The
southern part of the study area (Pipalkoti) is characterized by top weathered layer in partial or complete water saturation. Thickness of this zone varies between 10 and 20 m and is characterized by a resistivity of about 100 Ωm. This zone extends up to Pakhi (ERT-4), where the resistivity of the weathered layer increases up to 400 Ωm. This is due to the presence of large size boulder molasse which can also be seen on the surface. Further, north to Pakhi at the investigated sites: Tangni, Langsi, Gulabkoti and Helang weathering is generally absent and the formation is characterized by Gulabkoti formation composed of quartzite with inner chlorite schist (GSI, 1991) and dolomite at Langsi. The rocks are highly fractured and hot water springs emerge at Gulabkoti and Helang around the observation sites. The compact rock mass is resistive (N1000 Ωm) at Tangni (ERT-5). Local small scale fractured saturated zones are characterized by low resistivity (b200 Ωm). A very low resistivity (b50 m) is also observed in the zones where hot/cold water springs emerge (ERT-5, 6, 7). These zones are the characteristics of the underground water channels through the minor/major fracturing. A limited success has also been obtained in the TEM modeling of the data. General character and sign reversal in TEM data have been successfully reproduced by topographic modeling. TEM modeling results infer that the background resistivity of the rock mass in the southern part is lower than that in the northern part and this is also consistent with the ERT results. The measured electrical conductivity of the water samples collected from the hot springs in the Helang area varies between 628 μmho/cm and 648 μmho/cm on the right and left bank of Alaknanda river. This value is 382 μmho/cm measured for the normal nearby river water. The electrical conductivity of precipitation water (rainwater) collected from the Pipalkoti area is 46 μmho/cm. The water of the hot water spring, which has a higher electrical conductivity (628–648 μmho/cm) than fresh meteoric and river water, is rich in bicarbonates and sulphate, indicating a meteoric source. After its percolation the water has mixed with ionic solid from the earth rock mass during its transit and residence in the localized fracture zones saturated with the hot fluid. The MCT zone falls in a high heat flow area, a majority of hot springs are concentrated around this zone. Israil et al. (2008) reported high heat flow (130 ± 30 mW/m 2) and high temperature gradient (60 ° ± 20 ° C/km) in the MCT zone, whereas the foot hill Himalayan belts show low heat flow (41 ± 10 mW/m 2) and low temperature gradient (17 ° ± 5 ° C/km) as published in GSI (1991). This suggests that the subsurface temperature is elevated in the MCT zone. The hot water oozing out from the subsurface must be either of deeper hot
Fig. 5. 2D model used for the interpretation of TEM data.
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source origin or of meteoric origin passing through relatively shallow subsurface hot zones. The low resistivity (~ 50 Ωm) zones at shallow depths are associated with the hot water bearing zones. The resistive formation above the low resistivity zone is acting as cap rock in the entire region. Hence, except through fracture, there appears no direct hydraulic connection between the low resistivity hot water zones and near surface formations. The zone is extended laterally around MCT region.
6. Conclusions The subsurface electrical structure at shallow depth (b200 m) is delineated by ERT and TEM profiles in the Central Himalaya region. Electrical models derived from these data are interpreted in terms of rock fracture and their water saturation based on the general geological inputs available for the area. The compact rock mass is exhibited by high resistivity (N1000 Ωm); fractured and partially
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fractured zones are indicated by low resistivity formations (b50 to 100 Ωm). A very low resistivity (b50 Ωm) zone at shallow depth is interpreted as water bearing fractured zone from which water emerges as normal water spring at surface. The electrical models derived from ERT indicate that the area is intensively fractured. These fractures are generally shallow in nature, except for some places like at the Helang area where fractures might have gone deeper and meteoric water flowing through these fractures from the ground surface reaches deeper levels and becomes hot water due to the elevated temperature. Such zones have become the source of the hot water springs in the area namely: Gulabkoti and Langsi, which is one possible interpretation of the hot water springs in the area. In the study area it has been observed that in addition to this deep hot water bearing fractured zones, there exists a number of shallow water bearing fractured zones. These zones are reflected in the ERT results as low resistivity (~50 Ωm) zones in the upper part of the otherwise high resistivity (N1000 Ωm) rock mass (Tangni). These conclusions are based on the limited geophysical data recorded, available information and geological inputs for the study area. The outcome of the present investigations may be further updated or revised by adding more geophysical/geological data and by incorporating 3D modeling and inversion in future. References Baranwal, V.C., Sharma, S.P., 2006. Integrated geophysical studies in the East-Indian geothermal province. Pure and Applied Geophysics 163, 209–227. Caglar, I., Demirorer, M., 1999. Geothermal exploration using geoelectric methods in Kestanbol, Turkey. Geothermics 28, 803–819. Commer, M., Helwig, S.L., Hördt, A., Scholl, C., Tezkan, B., 2006. New results on the resistivity structure of Merapi Volcano (Indonesia), derived from three-dimensional restricted inversion of long-offset transient electromagnetic data. Geophysical Journal International 167, 1172–1187. Druskin, V.L., Knizhnermann, L.A., 1988. A spectral semi-discrete method for the numerical solution of 3 d nonstationary problems in electrical prospecting. Physics of the Solid Earth 24, 641–648. Flis, M., 1987. IP effects in 3-D TEM data — theory and case histories. Proceeding of the 5th Australian SEG Conference, pp. 55–58. Goldman, M., Levi, E., Kafri, U., Herut, B., Tibor, G., Tezkan, B., Gurk, M., Bergers, R., Yogeshwar, P., 2009. Detection of fresh groundwater bodies within the Mediterranean sub-marine coastal aquifers offshore Israel using marine geoelectromagnetic methods: http://www.marelec.co.uk/conference/MarelecAbstracts.pdf. GSI, 1991. Geothermal Atlas of India, Geological Survey of India. Special Publication 19 143 pp. GSI, 2008. Geological Survey of India, Northern Region. Günther, T., 2004. Inversion methods and resolution analysis for the 2D/3D reconstruction of resistivity structures from DC measurements. Ph. D. Thesis, Technische Universität Bergakademie Freiberg, Germany.
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