The conductivity structure of the Gediz Graben geothermal area extracted from 2D and 3D magnetotelluric inversion: Synthetic and field data applications
•Interpretation of MT data on extensional tectonic geothermal areas is examined using synthetic and field data.
•Three dimensional conductivity model of Gediz Graben geothermal area is created using seismic sections and used for producing synthetic magnetotelluric data.
•The resolving power of the two and three-dimensional inversion methods is discussed.
•Three dimensional inversion is applied to the field data and presented with real borehole results.
•New geothermal source was discovered using the MT data and three-dimensional inversion results.
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The conductivity structure of the Gediz Graben geothermal area extracted from 2D and 3D magnetotelluric inversion: Synthetic and field data applications
2. E. Erdo˘gan, M.E. Candansayar / Geothermics 65 (2017) 170–179 171
(Maris et al., 2012; Lindsey and Newman, 2015; Wannamaker et al.,
2016).
Synthetic model studies are important tools for testing newly
developed modeling and inversion codes, configuring field studies,
and analyzing the efficiency of geophysical methods for explo-
ration projects. Traditionally, geometric models are used for testing
newly developed algorithms (Zhdanov et al., 1997), and concep-
tual geological models are used for configuring field parameters
(Börner et al., 2015) and testing the efficiency of geophysical meth-
ods (Candansayar and Tezkan, 2008). Distinct from synthetic model
studies in the literature, we designed a large graben model simulat-
ing the actual topography, site locations, and geological boundaries
obtained from previous geophysical observations and borehole
information.
Gediz Graben is one of the most important geothermal areas in
Western Anatolia, which is also one of the most outstanding exten-
sional tectonic region in the world. The tectonic evolution of the
area has been studied in detail in several papers (Koc¸ yi˘git et al.,
1999; Seyitoglu et al., 2000; Bozkurt and Sozbilir, 2004). There
are also geophysical studies that have investigated the geologi-
cal structure of Gediz Graben (Eyidogan and Jackson, 1985; Gürer
et al., 2002). Although many geothermal exploration campaigns
have been completed in Gediz Graben, there is no detailed study of
the geo-electrical structure of the area.
In this study, we designed a large 3D conductivity model of the
Gediz Graben geothermal area. Unlike previous studies, we used the
actual topographical variations and layer thicknesses of the geolog-
ical settings obtained from seismic sections and previously drilled
boreholes. The virtual graben model represents the real character-
istics of the Gediz Graben geothermal area and the calculated MT
response used as synthetic data for comparing the accuracy of two-
dimensional (2D) and 3D inversion methods. The inability of the
2D inversion on 3D structures was investigated. In addition, the
effectiveness of the MT method in extensional tectonic geother-
mal areas was examined. We expect that the virtual conductivity
model will be a useful guide for exploration studies that will be
applied to Gediz Graben and other extensional graben regions as
well. For the purpose of supporting the virtual model studies, we
also present field data examples surveyed inside the virtual model
area, at the northern margin of Gediz Graben. The field data exper-
iments produced results similar to the synthetic model examples.
The inversion results are presented with actual borehole results,
and a new geothermal resource has been explored following the
interpretation of the 3D field data inversion.
2. Geological setting
The study area is located in the eastern part of Gediz Graben,
which is one of the largest graben systems in the Western Anato-
lia extensional zone. The graben area is characterized mainly by
E-W normal faulting and N-S oblique and strike-slip faulting to
accommodate the N-S extension (Koc¸ yi˘git, 1984). The most spec-
tacular consequence of this extensional system is the exhumation
of the Menderes Massif with low-angle normal faulting (detach-
ment fault) during the Miocene and high-angle normal faulting
during the Pliocene–Quaternary. High-angle normal faults play an
influential role on the development of the graben system and the
geothermal systems as well. The geological map of Gediz Graben
is presented in Fig. 1. The geothermal springs emerge from the
intersections of the Quaternary and pre-Quaternary fault systems
(Yilmazer et al., 2010). The basement of the study area consists
mostly of Menderes Massif metamorphic rocks such as gneiss, mica,
schist, phyllite, quartz-schist and marble. The porosity and per-
meability of these reservoir basement rocks are highly variable.
The rocks that contain intense amounts of carbonate (marble and
dolomitic marble) are highly fractured and act as an efficient reser-
voir for both cold ground and thermo-mineral waters. Fractured
gneiss and quartz-schist units of the Menderes Massif also act as
aquifer rocks. Miocene-aged terrestrial sediments comprised of
conglomerate and limestone (Hamamdere/Gediz formations) cover
the basement rock and constitute minor aquifers. The Neogene
sediments, which are composed of alluvial fan deposits including
poorly cemented clay-rich horizons, have very low permeability
and act as a cap rock for the geothermal system (Ozen et al., 2010).
We would like to emphasize that the conglomerate/limestone unit
under the cap rock is relatively resistive compared to the clay-
like units, generally causing misinterpretations in determining the
depth of the basement rocks.
3. 3D conductivity model
The virtual conductivity model area describes the Eastern part
of Gediz Graben between the towns of Alas¸ ehir and Göbekli towns
(Fig. 2a). We designed a large 3D conductivity model with real
topographical variations and geological settings. To simulate actual
fieldwork, we placed the MT sites at the actual coordinates with
1 km of space between them. The MT sites were located on a profile
direction with 25◦ east of north rotation considering the orientation
of the graben. The MT grid consists of 18 NE-SW profiles with 13 MT
sites on each profile. We discretized the mesh with zero orienta-
tion (N-S direction). The distance between the MT sites was equally
divided into 250 m sub-blocks, and to achieve accurate boundary
conditions, 16 blocks were added in x and y directions. A total of
70 blocks were used in −z direction including the air layers, which
represent the topographical variations. The topographical data of
the area was acquired from the SRTM (Shuttle Radar Topography
Mission, NASA) with 3” resolution and incorporated into the mesh.
The minimum and maximum block dimensions in −z direction are
8 m and 16.205 m respectively. The entire mesh consists of 829,920
blocks.
For simulating a real-world geological model, we benefited from
13 profiles of seismic data acquired by the TPIC (Turkish Petroleum
International Company) for oil and gas exploration. These seismic
data were studied and published by many researchers (Bozkurt and
C¸ iftc¸ i, 2008; Turk, 2014). We used the study by C¸ iftc¸ i (2007) to
define the depth of the metamorphic basement and also the litho-
logical boundaries of the sedimentary graben fill. The directions of
the seismic profiles are shown in Fig. 2. The sample-interpreted
seismic 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. The
alluvial fill that is covering the Menderes Massif generally con-
sists of four layers. The conglomerate/limestone unit, named the
Alas¸ ehir Formation (brown), is located above the basement. This
formation is relatively conductive (20–30 ohm-m) compared to
the basement rocks. Above the Alas¸ ehir Formation, there is a
sandstone/claystone unit. This unit shows the highest conductiv-
ity (1–3 ohm-m) due to the geothermal alteration. Although the
seismic section is capable of separating this formation into two dif-
ferent layers (pink and orange), there is no conductivity contrast
to distinguish these two units. Therefore, this unit was considered
as a single layer. The quaternary alluvial deposits (white) that are
placed at the top of the section also show moderately high resistiv-
ity (30–50 ohm-m). All of the seismic sections were sampled using a
250 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 information
for the 18 boreholes previously drilled inside the study area was
utilized. We assigned resistivity values to each of the geological for-
3. 172 E. Erdo˘gan, M.E. Candansayar / Geothermics 65 (2017) 170–179
Fig. 1. Geology map of the Gediz Graben (C¸ iftc¸ i, 2007).
mations obtained from the seismic sections and borehole data. We
used 100 ohm-m for the basement rocks, 25 ohm-m for the Alas¸ ehir
Formation, 3 ohm-m for the conductive sandstone/claystone unit,
and 50 ohm-m for the alluvial deposits. All thickness information
was obtained from seismic sections, and boreholes were gridded
using 200 m steps for adapting the layer thicknesses to the whole
3D conductivity model. The x-y maps of the created conductivity
model are presented in Fig. 4.
3D MT forward modeling was applied to the model pre-
sented above using ModEM software (Kelbert et al., 2014). Four
components of the impedance tensor and two vertical magnetic
components were calculated for 46 frequencies between 10 KHz
and 0.001 Hz. The calculation of the MT response data took 208 s
on a parallel computer with 128 cores and 256 GB memory; a 5%
Gaussian error function was applied to the impedance tensor and
the vertical magnetic component.
4. Inversion of the synthetic data
Synthetic data calculated from the 3D graben model is used
for evaluating the resolving power of the MT data measured at
the graben structures and also to compare the 2D and 3D inver-
sion results. First, we applied 3D inversion to the synthetic data
using ModEM software. The inversion mesh was equally divided
into 300 m blocks in x and y directions inside the solution area, and
16 blocks were added for the boundary conditions. We would like to
emphasize that we used different lateral discretization compared
to the forward mesh we used for calculating the synthetic data.
We selected a minimum block thickness of 8 m in the z direction to
4. E. Erdo˘gan, M.E. Candansayar / Geothermics 65 (2017) 170–179 173
Fig. 2. Aerial (a) and side view (b) of the study area. The blue lines show the seismic
profiles. The dots represent the MT site locations. The red paths are known active
faults. The yellow line shows the S6 seismic profile presented in Fig. 3. (For inter-
pretation of the references to colour in this figure legend, the reader is referred to
the web version of this article.)
smoothly represent the topographical variations; 18 air layers were
used for incorporating the topography in the mesh. The inversion
mesh consisted of 631,120 blocks. Full impedance tensor and ver-
tical magnetic components for 46 frequencies between 10 KHz and
0.001 Hz were used as input data. The inversion of the noisy on-
diagonal impedance data does not significantly change the model
for geothermal exploration studies carried out for depths accessi-
ble by drilling (Lindsey and Newman, 2015). Therefore, we applied
a 30% error floor to the on-diagonal impedance data while using
3% for off-diagonal and vertical magnetic components. Inversion
started with a 100 ohm-m homogenous half-space and 14.3 rms
(root mean square) value. After 16 iterations, the rms value was
minimized to 1.5. Each iteration took 50 min, and the inversion
workflow was completed in 812 min using parallel computers with
128 cores and 1024 GB memory.
Horizontal slices of the virtual graben model (on the left) and 3D
inversion results of the synthetic data (on the right) are presented in
Fig. 5 for different depth values. The figure clearly shows that the
3D inversion results represent the general pattern of the graben
fill. The white lines plotted on the inversion results represent the
actual model boundaries. The border of the resistive basement rock
resolved distinctively for −40 m, and it matches the white line well.
Although the pattern of the resistive border only slightly fits the
white line for −542 m and −661 m, it is not completely overlapping
due to the increasing depth.
The edges of the large shallow conductive anomaly are compa-
rable with the model border. The northern border of the shallow
conductive anomaly is better resolved when compared to the
southern border because of the sinuous structure of the conduc-
tive anomaly in the southern part. There are two deep conductive
anomalies in the graben model (−452 m and −661 m). These deep
conductors represent the deepest part of the graben. The 3D inver-
sion has adequately recovered the location and orientation of these
deep conductors. Although the conductive anomaly outside the MT
measurement grid exists, it could not be resolved by 3D inversion
and 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, which
is perpendicular to the graben direction. We applied decomposi-
tion analysis as described by Groom and Bailey (1989) to determine
the 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 by
Candansayar (2008) was used for the 2D inversion of the synthetic
data. TE and TM (Transverse Magnetic) modes of apparent resistiv-
ity, phase data, and tipper magnitude data were used as inputs. It
is well known that TM mode data is less affected from the three-
dimensionality of the underground structure compared to the TE
mode data (Wannamaker et al., 1989; Berdichevsky et al., 1998).
We applied all single mode and joint inversion methods for 2D
inversion of the synthetic data. Joint inversion results of the TE/TM
modes with tipper data which give better correlation with the real
model section are presented in this paper. We used the same mesh
dimensions with the 3D mesh in x and z directions, and a total of
4888 cells were used for the 2D inversion. The homogenous half-
space with 100 ohm-m resistivity was used as a starting model. The
inversion started with 12.2 rms value and decreased to 2.08 at the
end of the inversion scheme. All of the inversion workflow took
only 6 min on a regular desktop computer.
Fig. 6 shows the comparison of the resistivity cross-sections
extracted 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
almost the same as the actual graben model section. The conduc-
tive anomaly is adequately recovered by the 3D inversion. However,
when we follow the white line representing the resistive basement-
Fig. 3. Sample seismic section S-6 (C¸ iftc¸ i, 2007).
5. 174 E. Erdo˘gan, M.E. Candansayar / Geothermics 65 (2017) 170–179
Fig. 4. X-Y maps of the 3D resistivity model for various depths.
conglomerate/limestone interface, the top of the basement looks
shallower at the SW part of the section compared to the virtual
graben model (real model). In addition, the deepest part of the
section looks like it has shifted slightly to the SW. By contrast,
even if the 2D inversion had detected the conductive anomaly,
the shape and the borders of the anomaly would not have aligned
with the white line representing the real model. Furthermore, the
2D inversion appears to be insufficient for recovering the resistive
basement topography, especially under the deep conductor. In 2D
and 3D inversion, regularized inversion with smoothing stabilizing
functional was used and in both cases we obtained regulariza-
tion parameter by using cooling approximation (e.g. Newman and
Alumbaugh, 1997; Candansayar, 2008). Therefore, we think that
main differences between 2D and 3D inversion results are caused
by the three dimensionality of the synthetic graben model.
A fundamental assumption of 2D inversion is that the pro-
file direction must be perpendicular to the geo-electrical strike
direction. However, in some cases, the MT profiles parallel to the
strike direction are used for 2D inversion. We selected a sec-
ond synthetic-data example to examine and discuss this issue.
Fig. 7a shows the resistivity cross-section extracted from the virtual
graben model. The direction of the profile is selected parallel to the
northern margin of the graben and also parallel to the geo-electric
strike.
The 2D inversion mesh was designed using similar dimensions
as those used with 3D, and a total of 6392 cells were used for the
inversion. The inversion scheme started with a 13.1 rms error and
was finalized with a 2.9 error after 8.2 min. When we compare the
inversion results, it is clearly seen that the 2D inversion results
appear to be unsatisfactory for imaging the conductive anomaly, in
particular for the thin layer located between 500 m and 8000 m. In
addition, the shape of the anomaly looks quite different compared
to 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 and
the basement topography. Only the sharp undulations on the top
of the basement could not be resolved. This synthetic-data study
6. E. Erdo˘gan, M.E. Candansayar / Geothermics 65 (2017) 170–179 175
Fig. 5. A comparison of the virtual graben model (left) and the 3D inversion results (right) of the synthetic data. In this figure and the following figures, the white line on the
inversion results represents the actual model boundaries.
shows that 2D inversion parallel to the strike direction could easily
cause misinterpretations of geological structures.
5. 3D inversion of the field data
We used the MT data provided to us by Energy Holding Com-
pany for our field data study. All recorded MT sites are located inside
the virtual graben area. The study area is located in the northern
margin of Gediz Graben (Fig. 8). The geothermal license borders are
not plotted on the map because of the confidentiality rights of the
licensed operator company. The area is completely covered by qua-
ternary alluviums and does not provide any geological evidence.
The MT data were recorded at 350 sites in order to understand the
geological structures and to determine the locations of the pro-
duction and re-injection boreholes. Remote reference processing
was applied to the time series data, utilizing the remote site based
8 km away from the study area on the northern horst. The distance
between each MT site was selected to be 250 m inside the licensed
area and 1000 m at the outside of the licensed area. The quality
of the MT data was good for most of the sites. Only 3 of the sites
were affected by cultural noise, irrigation activities, and power-
lines crossing the area. Those three stations were excluded from
the inversion.
We applied 3D inversion to all of the MT Data obtained from 350
sites using ModEM (Kelbert et al., 2014) software. Discretization of
the 3D inversion mesh needed to be designed for sufficient accuracy
with 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 were
appended to the mesh boundaries, and the dimensions of these
boundary blocks were logarithmically increased in all directions.
7. 176 E. Erdo˘gan, M.E. Candansayar / Geothermics 65 (2017) 170–179
Fig. 6. Resistivity cross-sections extracted from the virtual model (a), the 3D inversion result (b), and the 2D inversion result (c); the small map shows the direction of the
cross-section.
The slopes of the topographical variations are less than 4◦ inside
the study area. Therefore, we did not incorporate the topography
into the 3D inversion mesh. We used 70 blocks in z direction with a
minimum block thickness of 10 m. The total number of parameters
used for 3D MT inversion was 1,014,000. A full impedance tensor
was used as input for the inversion as well as with the two compo-
nents of the vertical magnetic data. We used the same frequency
range and error floors described in the synthetic data example.
The 3D inversion was started on the same parallel computer
with a 100 ohm-m homogenous half-space and 26.8 rms error.
Regarding the number of frequencies used (46 frequencies), 46
nodes for each polarization and one node for data transportation
were allocated. A total of 93 nodes were used during parallel com-
putation. After 28 iterations, the inversion scheme was completed
with a 2.4 rms error.
The final 3D MT model was used for the selection of the pro-
duction and re-injection zones. After the interpretations of the 3D
MT model, the company achieved 100% success on targeting pro-
ductive boreholes. The construction of the geothermal power plant
has already been completed, and the test productions are planned
to start in the following weeks. With the permission of the com-
pany, we present in this paper only one resistivity cross-section
with lithological data for 3 completed boreholes.
Fig. 9 shows the NE-SW resistivity cross-section extracted from
the 3D MT model. The section represents the major characteristics
of the graben structure. The depth of the resistive metamorphic
basement increases from the NE to the center of the graben fill
(SW). We observed two conductive anomalies in the section. The
shallow conductive anomaly is located within 2–3 km. The upper
boundary of this anomaly starts at 250 m deep and continues to the
750 m range. This shallow conductive anomaly is separated from
the deep conductor by a high-angle normal fault. The lower bound-
ary of the deep conductive anomaly reaches a depth of 1750 m and
was probably formed by higher-temperature geothermal activity.
There is also a relatively resistive unit (10–30 ohm-m) between the
metamorphic basement and the conductive cap rock. This unit is
clearly separated as a conglomerate/limestone layer, represented
by the green color. The alluvial deposits also show resistive anomaly
on the top of the section.
The fault zone between the deep and shallow conductive
anomalies 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 the
same resistivity cross-section with the observed borehole geolog-
ical data. The distance between production wells PW1 and PW2 is
300 m, and the depths of these wells are 3100 m and 3005 m respec-
8. E. Erdo˘gan, M.E. Candansayar / Geothermics 65 (2017) 170–179 177
Fig. 7. Resistivity cross-sections extracted from the virtual model (a), the 3D inversion result (b), and the 2D inversion result (c); the small map shows the direction of the
cross-section.
Fig. 8. Aerial view of Western Gediz Graben; the border shows the field study area.
tively. These two wells produce an average of 350 t/h geothermal
water at a temperature of 210 ◦C. The re-injection well RW1 is
1300 m deep and produces 400 t/h geothermal water at a tempera-
ture of 130 ◦C. Fig. 9b clearly shows that the lithological boundaries
of the observed borehole geological data accurately align with the
resistivity transactions of the 3D MT model section.
6. Conclusions
In this paper, we focused on a comparison of the effectiveness
of 2D and 3D MT inversion methods on geothermal exploration
using synthetic and field data examples. A virtual 3D conductiv-
ity model of Gediz Graben was created with actual topographical
variations and geological settings. A 3D MT response of the graben
model was calculated and synthetic data used for comparing the 2D
and 3D inversion methods. Comparisons show that 2D inversion
is capable of detecting conductive anomalies, but it is less capa-
ble compared to 3D for determining the shape of the conductive
anomalies and for imaging the resistive basement rock, especially
under the deep conductor. In addition, misinterpretations caused
by the 2D inversion applied parallel to the strike direction were
pointed out using synthetic data. Resistivity cross-sections that
were extracted from the 3D inversion model are more compati-
ble with the virtual model sections. The orientation and shape of
the conductive anomalies are accurately recovered by 3D inversion.
The major character of the metamorphic basement is resolved by
3D inversion, but there are deficiencies for determining the deepest
part of the graben. This issue was presumably caused by the inver-
sion mesh refinement and can be overcome by using more-detailed
measurement grid and mesh discretization. The other reason is that
the MT data is not capable of resolving the deep resistive meta-
9. 178 E. Erdo˘gan, M.E. Candansayar / Geothermics 65 (2017) 170–179
Fig. 9. Resistivity cross-section extracted from the 3D inversion model of the MT
field data.
Fig. 10. Resistivity cross-section extracted from the 3D inversion model of the MT
field data with borehole results.
morphic basement accurately due to the employed regularization
parameter and/or regularized inversion with smoothing stabiliz-
ing functional. The ability of 3D inversion to image the resistive
basement rock shows that 3D inversion is a powerful tool for inter-
pretation of the geological structures formed by extensional graben
tectonics. The efficiency of 3D inversion was also tested on the field
data applications and compared to the borehole results. The con-
gruity of the resistivity intersections with lithological boundaries
of the borehole data is remarkable. A new geothermal source was
discovered using the MT data and the 3D inversion results. The dis-
covery was based on the ability of the 3D resistivity model to imply
structural offsets in the geological units at depth which proved to
be productive geothermal fault zones.
Acknowledgements
This study is a part of PhD thesis undertaken by the first author
and supported by the Scientific and Technical Research Council of
Turkey, TUBITAK under grant no: 105G145. The authors are grateful
to Energy Holding Company and the MT crew for providing the MT
field data. We also thank Naser Meqbel for his contributions on
virtual graben model. Special thanks to Phil Wannamaker for his
constructive and versatile comments that improve the paper.
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