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Geothermics 65 (2017) 170–179

Contents lists available at ScienceDirect

Geothermics

journa l homepage: www.e lsev ier .com/ locate /geothermics

he conductivity structure of the Gediz Graben geothermal areaxtracted from 2D and 3D magnetotelluric inversion: Synthetic andeld data applications

rhan Erdogan a,b,∗, M. Emin Candansayar b

Enerjeo Kemaliye Enerji Üretim A.S ., Kavacık Meydanı, Energy Plaza Kat: 8, 34805, Beykoz, Istanbul, TurkeyAnkara University, Faculty of Engineering, Department of Geophysical Engineering, Geophysical Modelling Group (GMG), 06830, Gölbas ı, Ankara, Turkey

r t i c l e i n f o

rticle history:eceived 18 July 2016eceived in revised form1 September 2016ccepted 23 September 2016

eywords:agnetotelluricseothermal energyD inversionD inversionediz Graben

a b s t r a c t

In this study, we have created a virtual three-dimensional conductivity model of the Gediz Grabengeothermal area using real topographical variations and geological settings as prelude to the interpre-tation of acquired MT field data. The thicknesses of the geological units were obtained from previouslystudied seismic sections and boreholes drilled inside the study area. A large magnetotelluric grid wascreated using 234 sites with 1 km spacing between each site. The three-dimensional magnetotelluricresponse of the model was calculated at each site and used as an input for two- and three-dimensionalinversion to assess resolving capability for subsurface features. The inversion results were compared tothe virtual graben model, and the efficiency of the inversion methods was examined. Comparisons showthat the three-dimensional inversion of magnetotelluric data has many advantages with respect to thetwo-dimensional inversion results for the interpretation of the three-dimensional geological structure ofthe graben fill. Although the two-dimensional inversion is a rapid tool for exploration of the conductiveanomalies, it is inadequate for interpreting the resistive basement rock structure under the sedimentarycover. We also applied three-dimensional inversion to the field data previously recorded inside the studyarea. The target borehole locations were defined according to the interpretation of the three-dimensionalinversion model. A resistivity cross-section extracted from the three-dimensional model of the field datais presented with the borehole observations. The lithological boundaries of the actual borehole data and

the resistivity transactions of the three-dimensional model show close correlation. The synthetic dataexamples show that the virtual graben model is a practical tool for understanding the advantages anddisadvantages of the magnetotelluric inversion methods on extensional tectonic basins. Additionally, thefield data experiments show that the three-dimensional inversion of magnetotelluric data is an efficienttool for interpreting the geological structure of extensional graben systems.

© 2016 Elsevier Ltd. All rights reserved.

. Introduction

Electrical resistivity is a major physical characteristic of thearth affected by geothermal activities (Gasperikova et al., 2011).igh conductivity anomalies that are caused by geothermal alter-tion and fracture zones filled with geothermal fluids make

lectromagnetic methods (EM) productive tools for geothermalxploration (Munoz, 2014). The magnetotelluric (MT) methods the EM method most often used for determining resistiv-

∗ Corresponding author at: Enerjeo Kemaliye Enerji Üretim A.S ., Kavacık Meydanı,nergy Plaza Kat: 8, 34805, Beykoz, Istanbul, Turkey.

E-mail address: eerdogan@enerjiholding.com.tr (E. Erdogan).

ttp://dx.doi.org/10.1016/j.geothermics.2016.09.007375-6505/© 2016 Elsevier Ltd. All rights reserved.

ity distribution, detecting conductive anomalies, and targetingpotential borehole locations in geothermal areas (Uchida, 1995;Wannamaker et al., 2007, 2016; Maris et al., 2012). Imaging conduc-tive anomalies using the MT method is a useful guide for prioritizinggeothermal areas, but targeting a productive borehole requires anintegrative geological interpretation. Consequently, the geophysi-cal model should represent the major geological characteristics ofthe area and the properties of the conceptual geothermal model.The efficiencies of the MT inversion models on geothermal explo-ration studies have been thoroughly examined in previous papers

(Uchida and Sasaki, 2006; Cumming and Mackie, 2010). Follow-ing the developments in multiprocessor computers and parallelinversion algorithms, three-dimensional (3D) inversion of large MTdata sets has become prevalent for geothermal exploration studies

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E. Erdogan, M.E. Candansayar

Maris et al., 2012; Lindsey and Newman, 2015; Wannamaker et al.,016).

Synthetic model studies are important tools for testing newlyeveloped modeling and inversion codes, configuring field studies,nd analyzing the efficiency of geophysical methods for explo-ation projects. Traditionally, geometric models are used for testingewly developed algorithms (Zhdanov et al., 1997), and concep-ual geological models are used for configuring field parametersBörner et al., 2015) and testing the efficiency of geophysical meth-ds (Candansayar and Tezkan, 2008). Distinct from synthetic modeltudies in the literature, we designed a large graben model simulat-ng the actual topography, site locations, and geological boundariesbtained from previous geophysical observations and borehole

nformation.Gediz Graben is one of the most important geothermal areas in

estern Anatolia, which is also one of the most outstanding exten-ional tectonic region in the world. The tectonic evolution of therea has been studied in detail in several papers (Koc yigit et al.,999; Seyitoglu et al., 2000; Bozkurt and Sozbilir, 2004). Therere also geophysical studies that have investigated the geologi-al structure of Gediz Graben (Eyidogan and Jackson, 1985; Gürert al., 2002). Although many geothermal exploration campaignsave been completed in Gediz Graben, there is no detailed study ofhe geo-electrical structure of the area.

In this study, we designed a large 3D conductivity model of theediz Graben geothermal area. Unlike previous studies, we used thectual topographical variations and layer thicknesses of the geolog-cal settings obtained from seismic sections and previously drilledoreholes. The virtual graben model represents the real character-

stics of the Gediz Graben geothermal area and the calculated MTesponse used as synthetic data for comparing the accuracy of two-imensional (2D) and 3D inversion methods. The inability of theD inversion on 3D structures was investigated. In addition, theffectiveness of the MT method in extensional tectonic geother-al areas was examined. We expect that the virtual conductivityodel will be a useful guide for exploration studies that will be

pplied to Gediz Graben and other extensional graben regions asell. For the purpose of supporting the virtual model studies, we

lso present field data examples surveyed inside the virtual modelrea, at the northern margin of Gediz Graben. The field data exper-ments produced results similar to the synthetic model examples.he inversion results are presented with actual borehole results,nd a new geothermal resource has been explored following thenterpretation of the 3D field data inversion.

. Geological setting

The study area is located in the eastern part of Gediz Graben,hich is one of the largest graben systems in the Western Anato-

ia extensional zone. The graben area is characterized mainly by-W normal faulting and N-S oblique and strike-slip faulting toccommodate the N-S extension (Koc yigit, 1984). The most spec-acular consequence of this extensional system is the exhumationf the Menderes Massif with low-angle normal faulting (detach-ent fault) during the Miocene and high-angle normal faulting

uring the Pliocene–Quaternary. High-angle normal faults play annfluential role on the development of the graben system and theeothermal systems as well. The geological map of Gediz Grabens presented in Fig. 1. The geothermal springs emerge from thentersections of the Quaternary and pre-Quaternary fault systemsYilmazer et al., 2010). The basement of the study area consists

ostly of Menderes Massif metamorphic rocks such as gneiss, mica,chist, phyllite, quartz-schist and marble. The porosity and per-eability of these reservoir basement rocks are highly variable.

he rocks that contain intense amounts of carbonate (marble and

thermics 65 (2017) 170–179 171

dolomitic marble) are highly fractured and act as an efficient reser-voir for both cold ground and thermo-mineral waters. Fracturedgneiss and quartz-schist units of the Menderes Massif also act asaquifer rocks. Miocene-aged terrestrial sediments comprised ofconglomerate and limestone (Hamamdere/Gediz formations) coverthe basement rock and constitute minor aquifers. The Neogenesediments, which are composed of alluvial fan deposits includingpoorly cemented clay-rich horizons, have very low permeabilityand act as a cap rock for the geothermal system (Ozen et al., 2010).We would like to emphasize that the conglomerate/limestone unitunder the cap rock is relatively resistive compared to the clay-like units, generally causing misinterpretations in determining thedepth of the basement rocks.

3. 3D conductivity model

The virtual conductivity model area describes the Eastern partof Gediz Graben between the towns of Alas ehir and Göbekli towns(Fig. 2a). We designed a large 3D conductivity model with realtopographical variations and geological settings. To simulate actualfieldwork, we placed the MT sites at the actual coordinates with1 km of space between them. The MT sites were located on a profiledirection with 25◦ east of north rotation considering the orientationof the graben. The MT grid consists of 18 NE-SW profiles with 13 MTsites on each profile. We discretized the mesh with zero orienta-tion (N-S direction). The distance between the MT sites was equallydivided into 250 m sub-blocks, and to achieve accurate boundaryconditions, 16 blocks were added in x and y directions. A total of70 blocks were used in −z direction including the air layers, whichrepresent the topographical variations. The topographical data ofthe area was acquired from the SRTM (Shuttle Radar TopographyMission, NASA) with 3” resolution and incorporated into the mesh.The minimum and maximum block dimensions in −z direction are8 m and 16.205 m respectively. The entire mesh consists of 829,920blocks.

For simulating a real-world geological model, we benefited from13 profiles of seismic data acquired by the TPIC (Turkish PetroleumInternational Company) for oil and gas exploration. These seismicdata were studied and published by many researchers (Bozkurt andC iftc i, 2008; Turk, 2014). We used the study by C iftc i (2007) todefine the depth of the metamorphic basement and also the litho-logical boundaries of the sedimentary graben fill. The directions ofthe seismic profiles are shown in Fig. 2. The sample-interpretedseismic cross-section S6 (yellow line in Fig. 2) is presented in Fig. 3.In this section, the purple unit represents the metamorphic rocks(Menderes Massif), which are moderately resistive (50–100 ohm-m). The depth of this formation varies from 300 m–3500 m. Thealluvial fill that is covering the Menderes Massif generally con-sists of four layers. The conglomerate/limestone unit, named theAlas ehir Formation (brown), is located above the basement. Thisformation is relatively conductive (20–30 ohm-m) compared tothe basement rocks. Above the Alas ehir Formation, there is asandstone/claystone unit. This unit shows the highest conductiv-ity (1–3 ohm-m) due to the geothermal alteration. Although theseismic section is capable of separating this formation into two dif-ferent layers (pink and orange), there is no conductivity contrastto distinguish these two units. Therefore, this unit was consideredas a single layer. The quaternary alluvial deposits (white) that areplaced at the top of the section also show moderately high resistiv-ity (30–50 ohm-m). All of the seismic sections were sampled using a250 m distance, and the thickness of the formations was measured

in order to design the 3D conductivity model.

In addition to the seismic sections, the lithological informationfor the 18 boreholes previously drilled inside the study area wasutilized. We assigned resistivity values to each of the geological for-

172 E. Erdogan, M.E. Candansayar / Geothermics 65 (2017) 170–179

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Fig. 1. Geology map of th

ations obtained from the seismic sections and borehole data. Wesed 100 ohm-m for the basement rocks, 25 ohm-m for the Alas ehirormation, 3 ohm-m for the conductive sandstone/claystone unit,nd 50 ohm-m for the alluvial deposits. All thickness informationas obtained from seismic sections, and boreholes were gridded

sing 200 m steps for adapting the layer thicknesses to the wholeD conductivity model. The x-y maps of the created conductivityodel are presented in Fig. 4.

3D MT forward modeling was applied to the model pre-ented above using ModEM software (Kelbert et al., 2014). Fouromponents of the impedance tensor and two vertical magnetic

omponents were calculated for 46 frequencies between 10 KHznd 0.001 Hz. The calculation of the MT response data took 208 sn a parallel computer with 128 cores and 256 GB memory; a 5%

iz Graben (C iftc i, 2007).

Gaussian error function was applied to the impedance tensor andthe vertical magnetic component.

4. Inversion of the synthetic data

Synthetic data calculated from the 3D graben model is usedfor evaluating the resolving power of the MT data measured atthe graben structures and also to compare the 2D and 3D inver-sion results. First, we applied 3D inversion to the synthetic datausing ModEM software. The inversion mesh was equally dividedinto 300 m blocks in x and y directions inside the solution area, and

16 blocks were added for the boundary conditions. We would like toemphasize that we used different lateral discretization comparedto the forward mesh we used for calculating the synthetic data.We selected a minimum block thickness of 8 m in the z direction to

E. Erdogan, M.E. Candansayar / Geo

Fig. 2. Aerial (a) and side view (b) of the study area. The blue lines show the seismicprofiles. The dots represent the MT site locations. The red paths are known activefaults. The yellow line shows the S6 seismic profile presented in Fig. 3. (For inter-pt

sumt0dfba3s(mw1

almost the same as the actual graben model section. The conduc-

retation of the references to colour in this figure legend, the reader is referred tohe web version of this article.)

moothly represent the topographical variations; 18 air layers weresed for incorporating the topography in the mesh. The inversionesh consisted of 631,120 blocks. Full impedance tensor and ver-

ical magnetic components for 46 frequencies between 10 KHz and.001 Hz were used as input data. The inversion of the noisy on-iagonal impedance data does not significantly change the model

or geothermal exploration studies carried out for depths accessi-le by drilling (Lindsey and Newman, 2015). Therefore, we applied

30% error floor to the on-diagonal impedance data while using% for off-diagonal and vertical magnetic components. Inversiontarted with a 100 ohm-m homogenous half-space and 14.3 rmsroot mean square) value. After 16 iterations, the rms value was

inimized to 1.5. Each iteration took 50 min, and the inversionorkflow was completed in 812 min using parallel computers with

28 cores and 1024 GB memory.

Fig. 3. Sample seismic sect

thermics 65 (2017) 170–179 173

Horizontal slices of the virtual graben model (on the left) and 3Dinversion results of the synthetic data (on the right) are presented inFig. 5 for different depth values. The figure clearly shows that the3D inversion results represent the general pattern of the grabenfill. The white lines plotted on the inversion results represent theactual model boundaries. The border of the resistive basement rockresolved distinctively for −40 m, and it matches the white line well.Although the pattern of the resistive border only slightly fits thewhite line for −542 m and −661 m, it is not completely overlappingdue to the increasing depth.

The edges of the large shallow conductive anomaly are compa-rable with the model border. The northern border of the shallowconductive anomaly is better resolved when compared to thesouthern border because of the sinuous structure of the conduc-tive anomaly in the southern part. There are two deep conductiveanomalies in the graben model (−452 m and −661 m). These deepconductors represent the deepest part of the graben. The 3D inver-sion has adequately recovered the location and orientation of thesedeep conductors. Although the conductive anomaly outside the MTmeasurement grid exists, it could not be resolved by 3D inversionand appears to be an artifact.

We also applied 2D inversion to the synthetic data and com-pared this to the 3D inversion results and virtual model sections.First, we used the MT sites located on the NE-SW profile, whichis perpendicular to the graben direction. We applied decomposi-tion analysis as described by Groom and Bailey (1989) to determinethe geo-electrical strike direction. After the decomposition analy-sis, all data sets rotated to 25◦E, and Zyx was selected as the TE(Transverse Electric) mode. The inversion algorithm developed byCandansayar (2008) was used for the 2D inversion of the syntheticdata. TE and TM (Transverse Magnetic) modes of apparent resistiv-ity, phase data, and tipper magnitude data were used as inputs. Itis well known that TM mode data is less affected from the three-dimensionality of the underground structure compared to the TEmode data (Wannamaker et al., 1989; Berdichevsky et al., 1998).We applied all single mode and joint inversion methods for 2Dinversion of the synthetic data. Joint inversion results of the TE/TMmodes with tipper data which give better correlation with the realmodel section are presented in this paper. We used the same meshdimensions with the 3D mesh in x and z directions, and a total of4888 cells were used for the 2D inversion. The homogenous half-space with 100 ohm-m resistivity was used as a starting model. Theinversion started with 12.2 rms value and decreased to 2.08 at theend of the inversion scheme. All of the inversion workflow tookonly 6 min on a regular desktop computer.

Fig. 6 shows the comparison of the resistivity cross-sectionsextracted from the virtual graben model (a), the 3D inversion model(b), and the 2D inversion model (c). At first glance, the resis-tivity cross-section extracted from the 3D inversion model looks

tive anomaly is adequately recovered by the 3D inversion. However,when we follow the white line representing the resistive basement-

ion S-6 (C iftc i, 2007).

174 E. Erdogan, M.E. Candansayar / Geothermics 65 (2017) 170–179

sistivi

csgsetw2baftAmb

fids

Fig. 4. X-Y maps of the 3D re

onglomerate/limestone interface, the top of the basement lookshallower at the SW part of the section compared to the virtualraben model (real model). In addition, the deepest part of theection looks like it has shifted slightly to the SW. By contrast,ven if the 2D inversion had detected the conductive anomaly,he shape and the borders of the anomaly would not have alignedith the white line representing the real model. Furthermore, the

D inversion appears to be insufficient for recovering the resistiveasement topography, especially under the deep conductor. In 2Dnd 3D inversion, regularized inversion with smoothing stabilizingunctional was used and in both cases we obtained regulariza-ion parameter by using cooling approximation (e.g. Newman andlumbaugh, 1997; Candansayar, 2008). Therefore, we think thatain differences between 2D and 3D inversion results are caused

y the three dimensionality of the synthetic graben model.

A fundamental assumption of 2D inversion is that the pro-

le direction must be perpendicular to the geo-electrical strikeirection. However, in some cases, the MT profiles parallel to thetrike direction are used for 2D inversion. We selected a sec-

ty model for various depths.

ond synthetic-data example to examine and discuss this issue.Fig. 7a shows the resistivity cross-section extracted from the virtualgraben model. The direction of the profile is selected parallel to thenorthern margin of the graben and also parallel to the geo-electricstrike.

The 2D inversion mesh was designed using similar dimensionsas those used with 3D, and a total of 6392 cells were used for theinversion. The inversion scheme started with a 13.1 rms error andwas finalized with a 2.9 error after 8.2 min. When we compare theinversion results, it is clearly seen that the 2D inversion resultsappear to be unsatisfactory for imaging the conductive anomaly, inparticular for the thin layer located between 500 m and 8000 m. Inaddition, the shape of the anomaly looks quite different comparedto the actual graben section and the 3D inversion results. The resis-tivity of the metamorphic basement could not be recovered at the

SE part of the section in the 2D inversion. The 3D inversion pro-duced comparable results for imaging the conductive anomaly andthe basement topography. Only the sharp undulations on the topof the basement could not be resolved. This synthetic-data study

E. Erdogan, M.E. Candansayar / Geothermics 65 (2017) 170–179 175

F (righti

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ig. 5. A comparison of the virtual graben model (left) and the 3D inversion results

nversion results represents the actual model boundaries.

hows that 2D inversion parallel to the strike direction could easilyause misinterpretations of geological structures.

. 3D inversion of the field data

We used the MT data provided to us by Energy Holding Com-any for our field data study. All recorded MT sites are located insidehe virtual graben area. The study area is located in the northern

argin of Gediz Graben (Fig. 8). The geothermal license borders areot plotted on the map because of the confidentiality rights of the

icensed operator company. The area is completely covered by qua-ernary alluviums and does not provide any geological evidence.

he MT data were recorded at 350 sites in order to understand theeological structures and to determine the locations of the pro-uction and re-injection boreholes. Remote reference processingas applied to the time series data, utilizing the remote site based

) of the synthetic data. In this figure and the following figures, the white line on the

8 km away from the study area on the northern horst. The distancebetween each MT site was selected to be 250 m inside the licensedarea and 1000 m at the outside of the licensed area. The qualityof the MT data was good for most of the sites. Only 3 of the siteswere affected by cultural noise, irrigation activities, and power-lines crossing the area. Those three stations were excluded fromthe inversion.

We applied 3D inversion to all of the MT Data obtained from 350sites using ModEM (Kelbert et al., 2014) software. Discretization ofthe 3D inversion mesh needed to be designed for sufficient accuracywith optimum computational time. Considering the minimum dis-tance between the MT sites (250 m), the solution area was divided

into 80 m blocks in both the x axis and y axis for lateral discretiza-tion. For an accurate model boundary condition, 15 blocks wereappended to the mesh boundaries, and the dimensions of theseboundary blocks were logarithmically increased in all directions.

176 E. Erdogan, M.E. Candansayar / Geothermics 65 (2017) 170–179

F sion rc

Ttimuwnr

wRnwpw

dMdhtpw

ig. 6. Resistivity cross-sections extracted from the virtual model (a), the 3D inverross-section.

he slopes of the topographical variations are less than 4◦ insidehe study area. Therefore, we did not incorporate the topographynto the 3D inversion mesh. We used 70 blocks in z direction with a

inimum block thickness of 10 m. The total number of parameterssed for 3D MT inversion was 1,014,000. A full impedance tensoras used as input for the inversion as well as with the two compo-

ents of the vertical magnetic data. We used the same frequencyange and error floors described in the synthetic data example.

The 3D inversion was started on the same parallel computerith a 100 ohm-m homogenous half-space and 26.8 rms error.egarding the number of frequencies used (46 frequencies), 46odes for each polarization and one node for data transportationere allocated. A total of 93 nodes were used during parallel com-

utation. After 28 iterations, the inversion scheme was completedith a 2.4 rms error.

The final 3D MT model was used for the selection of the pro-uction and re-injection zones. After the interpretations of the 3DT model, the company achieved 100% success on targeting pro-

uctive boreholes. The construction of the geothermal power plant

as already been completed, and the test productions are plannedo start in the following weeks. With the permission of the com-any, we present in this paper only one resistivity cross-sectionith lithological data for 3 completed boreholes.

esult (b), and the 2D inversion result (c); the small map shows the direction of the

Fig. 9 shows the NE-SW resistivity cross-section extracted fromthe 3D MT model. The section represents the major characteristicsof the graben structure. The depth of the resistive metamorphicbasement increases from the NE to the center of the graben fill(SW). We observed two conductive anomalies in the section. Theshallow conductive anomaly is located within 2–3 km. The upperboundary of this anomaly starts at 250 m deep and continues to the750 m range. This shallow conductive anomaly is separated fromthe deep conductor by a high-angle normal fault. The lower bound-ary of the deep conductive anomaly reaches a depth of 1750 m andwas probably formed by higher-temperature geothermal activity.There is also a relatively resistive unit (10–30 ohm-m) between themetamorphic basement and the conductive cap rock. This unit isclearly separated as a conglomerate/limestone layer, representedby the green color. The alluvial deposits also show resistive anomalyon the top of the section.

The fault zone between the deep and shallow conductiveanomalies was selected as a target area for the production wells.A second fault zone was also interpreted on the shallow conduc-

tive anomaly and selected as a re-injection area. Fig. 10 shows thesame resistivity cross-section with the observed borehole geolog-ical data. The distance between production wells PW1 and PW2 is300 m, and the depths of these wells are 3100 m and 3005 m respec-

E. Erdogan, M.E. Candansayar / Geothermics 65 (2017) 170–179 177

Fig. 7. Resistivity cross-sections extracted from the virtual model (a), the 3D inversion rcross-section.

F

tw1tor

part of the graben. This issue was presumably caused by the inver-sion mesh refinement and can be overcome by using more-detailed

ig. 8. Aerial view of Western Gediz Graben; the border shows the field study area.

ively. These two wells produce an average of 350 t/h geothermalater at a temperature of 210 ◦C. The re-injection well RW1 is

300 m deep and produces 400 t/h geothermal water at a tempera-ure of 130 ◦C. Fig. 9b clearly shows that the lithological boundaries

f the observed borehole geological data accurately align with theesistivity transactions of the 3D MT model section.

esult (b), and the 2D inversion result (c); the small map shows the direction of the

6. Conclusions

In this paper, we focused on a comparison of the effectivenessof 2D and 3D MT inversion methods on geothermal explorationusing synthetic and field data examples. A virtual 3D conductiv-ity model of Gediz Graben was created with actual topographicalvariations and geological settings. A 3D MT response of the grabenmodel was calculated and synthetic data used for comparing the 2Dand 3D inversion methods. Comparisons show that 2D inversionis capable of detecting conductive anomalies, but it is less capa-ble compared to 3D for determining the shape of the conductiveanomalies and for imaging the resistive basement rock, especiallyunder the deep conductor. In addition, misinterpretations causedby the 2D inversion applied parallel to the strike direction werepointed out using synthetic data. Resistivity cross-sections thatwere extracted from the 3D inversion model are more compati-ble with the virtual model sections. The orientation and shape ofthe conductive anomalies are accurately recovered by 3D inversion.The major character of the metamorphic basement is resolved by3D inversion, but there are deficiencies for determining the deepest

measurement grid and mesh discretization. The other reason is thatthe MT data is not capable of resolving the deep resistive meta-

178 E. Erdogan, M.E. Candansayar / Geo

Fig. 9. Resistivity cross-section extracted from the 3D inversion model of the MTfield data.

Ffi

mpibpt

ig. 10. Resistivity cross-section extracted from the 3D inversion model of the MTeld data with borehole results.

orphic basement accurately due to the employed regularizationarameter and/or regularized inversion with smoothing stabiliz-

ng functional. The ability of 3D inversion to image the resistiveasement rock shows that 3D inversion is a powerful tool for inter-retation of the geological structures formed by extensional grabenectonics. The efficiency of 3D inversion was also tested on the field

thermics 65 (2017) 170–179

data applications and compared to the borehole results. The con-gruity of the resistivity intersections with lithological boundariesof the borehole data is remarkable. A new geothermal source wasdiscovered using the MT data and the 3D inversion results. The dis-covery was based on the ability of the 3D resistivity model to implystructural offsets in the geological units at depth which proved tobe productive geothermal fault zones.

Acknowledgements

This study is a part of PhD thesis undertaken by the first authorand supported by the Scientific and Technical Research Council ofTurkey, TUBITAK under grant no: 105G145. The authors are gratefulto Energy Holding Company and the MT crew for providing the MTfield data. We also thank Naser Meqbel for his contributions onvirtual graben model. Special thanks to Phil Wannamaker for hisconstructive and versatile comments that improve the paper.

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