Natural state Modeling of Geothermal reservoir at Dieng, central

GRC Transactions, Vol. 37, 2013
Natural State Modeling of Geothermal Reservoir
at Dieng, Central Java, Indonesia
Takeshi Hino1, Ryuichi Itoi1,Toshiaki Tanaka1, N. Agung Pambudi1, and Khasani2
Department of Earth Resources Engineering, Kyushu University, Fukuoka, Japan
Department of Mechanical and Industrial Engineering, Faculty of Engineering,
GadjahMada University, Yogyakarta, Indonesia
tion. The natural state means a state before any exploitation Then,
optimum boundary conditions and values of physical parameters
of the rocks in the model were determined.
Dieng, Indonesia, numerical model, forward analysis method,
natural state, reservoir simulation
2. Conceptual Model
To develop a numerical model, we started with a conceptual
model of the reservoir on the basis of informations on geology,
geophysics and geochemistry obtained in the field. Data on the
Dieng geothermal field have been reported by Layman et al. (2002)
and Boedihardi et al. (1991).
According to Layman et al. (2002), areas of high conductance
(or low resistivity) at Dieng are associated with clay-rich, electrically conductive hydrothermal alteration overlying the productive
reservoir. Results of a 126-station magnetotelluric (MT) resistivity
A three dimensional numerical reservoir model of the Dieng
geothermal field was developed for the pre-exploitation stage using the TOUGH2 simulator with a forward analysis method. The
model was verified by matching temperature profiles of exploration wells. The numerical model in the natural state simulation was
able to successfully reproduce initial temperatures from 11 wells.
1. Introduction
The Dieng geothermal field is located in Central Java, Indonesia (Figure 1). It is situated within the cool volcanic highlands
of the Dieng Plateau at elevations around 2000 m. Most of the
plateau is intensely cultivated, and villages and farms are located
in close proximity to the geothermal facilities.
The Dieng geothermal field began its development in the
1990s. The power plant installed with 60 MWe started operation
in 1998. There are three known discharge areas around Dieng:
Sileri, Sikidang and Pakuwaja (Figure 1). The Sileri area is
characterized by relatively deep, high temperature production.
Reservoir temperatures range from 300-335°C, with the first
production zone typically encountered at or below sea level, at
depths between 2000-2300 m. The production zone in Sikidang
is relatively shallow and at lower temperatures than at Sileri.
Reservoir temperatures range from 240-300°C, with the production zone in most wells encountered at depths of 1400-1500 m, or
about +500 m to +750 m a.s.l. (Layman et al., 2002). In 2012, the
plant is operating at 22MW because of a lack of steam production.
In this study, a conceptual model of the Dieng geothermal
system was first developed using geological data and temperature
data of exploration wells. Then, a three dimensional reservoir
model using porous media was developed. Unknown parameters
in the numerical model were estimated by natural state simula-
Figure 1. Location map of Dieng geothermal field.
Hino, et al.
survey conducted in Dieng are summarized in a map of total
conductance to 1 km depth (Figure 2). An elongated, northwesttrending area of high conductivity (log total conductance >2.0),
with dimension 3 km×10 km, encloses the three main fumarolic
areas. Within this broad conductive region, three separate and
more intense anomalies (log total conductance >2.4) are associated with the fumarolic areas at Sileri, Sikidang and Pakuwaja.
Therefore, we assumed that there are domical high temperature
zones at depth (Figure 3).
According to Boedihardi et al. (1992), there are faults running
from northwest to southeast between Sileri and Sikidang (Figure4).
The conceptual model for the Dieng geothermal field was then
developed accordingly as shown in Figure 3. Two heat sources
exist at deep zone below the Sileri and Sikidang areas, then high
temperature fluid flows laterally from northwest to southeast at
or near sea level. Fluid then discharges at the surface in the two
fumarole regions: Sileri and Sikidang.
Figure 4. Geological map of the Dieng geothermal field (Boedihardi,
Figure 2. Map of log total conductance (mho) to 1 km depth (Layman et
al., 2002).
3. Numerical Simulation
3.1 Grid System
The code Mulgraph was used as pre-and postprocessor
(O’Sullivan and Bullivant, 1995). The grid system of the numerical
model measures 8.0 km by 8.5 km. Elevation of the model was
given in a range from -2.0 km to 2.0 km above sea level. Figure 5
shows the three dimensional blocks of the numerical model. The
model consists of 4560 grids in a size ranging from 250 m by 250
m to 1.0 km by 1.0 km. The model was further divided into 12
layers in the vertical direction with different thickness ranging
from 200 m to 1.0 km. 12 layers were named starting with Layer
A from the top of the model down to Layer L at the bottom layer.
3.2 Rock Properties
After the grid system of the model was developed, the next
step is to divide the system into several zones on the basis of information on geology, reservoir boundary, and location of faults.
Then, rock properties are assigned to each zone.
The rock properties consist of density, porosity, permeability,
thermal conductivity and specific heat, of which permeability is
considered as the most important parameter in controlling fluid
Figure 3. Conceptual model of the Dieng geothermal field.
Hino, et al.
4.Calibration of the Model – Natural State Simulation
Optimal values of permeabilities of rock types and recharge
rate of high temperature fluid and its specific enthalpy were
estimated through natural state simulation. The simulation was
conducted with the code TOUGH2 (Pruess et al., 1999).
Figure 5. Three dimensional grid blocks for the numerical model of Dieng
geothermal field.
flow in geothermal systems. Twelve rock types were used in this
study to express heterogeneous and isotropic characters of the
model mainly in permeability. Permeability-thickness products
(kh) of wells were determined from well testing, and their values
range from 1.3 to 6.5 darcy-m. These kh values were used as an
initial guess of permeability of rock types by assuming a thickness of the formation.
Other rock properties were given the same values for all rock
types density, porosity, thermal conductivity and specific heat
as 2500 kg/m3, 0.1, 2.5W/m/K and 1000 J/kg/K, respectively.
Then, rock type was assigned for each grid on the basis of conceptual model, and the distribution of rock types at each layer
are shown in Figure 6. In order to realize surface discharges
at Sileri and Sikidang, high permeable rock type was given in
these areas and other areas in Layer A was assigned with low
permeable rock type.
Figure 7. Locations of exploration well and mass source.
Simulation results were compared with temperature profiles
in 11 exploration wells. If the agreement between two kinds of
temperature profiles was not good, the following conditions were
adjusted: the amount of high temperature fluid recharge rate, heat
flux at the bottom layer and permeabilities of rock types. Then, the
simulation was repeated. This process was
iterated until good agreement with well
temperature was obtained (Ishido, 2002).
The simulation period was given as 2
million years. Locations of 11 wells are
shown in Figure 7. As for the initial conditions, the model domain was filled with
water at 15°C under hydrostatic conditions.
For the boundary conditions, constant
temperature and pressure of atmosphere
were given as 15°C and 0.803 bar at the
top surface. Peripheries of the model were
considered to be impermeable to mass and
adiabatic to heat. Two zones were assigned
for mass recharges as shown in Figure 7.
Recharge A and B were assigned at the
bottom layer below the Sileri and Sikidang
areas, respectively. These locations were
determined on the basis of the conceptual model. Flow rate of Recharge A was
estimated to be 18 kg/s with enthalpy of
1672 kJ/kg. For Recharge B, 6.5 kg/s and
1345 kJ/kg were estimated. The heat flux
of 0.1 W/m2 was given to all grids at the
bottom layer.
Figure 6. Distribution of rock types in layers.
Hino, et al.
A relatively good match is obtained for Wells
DNG-8, DNG-11, DNG-6, and DNG-5, which are
representative wells near Sikidang and Pakuwaja.
Although simulated temperatures for wells at Sileri,
Well DNG-7 and DNG-9, show a feature that the
temperature reaches 300°C at about +500m a.s.l., the
match is poor in the shallow zone between 1000 m
and 2000 m a.s.l. and the deeper portion from 0 m
a.s.l. to the bottom. In order to improve the matching for these two wells, permeability values of rock
type assigned to the area where these wells locate
need to be adjusted.
Figure 9 shows a temperature distribution in
Layer G (+100 m a.s.l.). The high temperature zone
extends to the southeast from Sileri. Temperature
distributions reported by Layman et al. (2002)
extends also from northwest to southeast in Dieng.
Estimated permeabilities of the optimal model in
Table 1 range from 1.0×10-18 m2 to 3.0×10-14 m2 in
x and y directions, and from 1.0×10-18 to 1.0×10-15
m2 in z direction. These permeabilities are 0.2 to 2.0
times as large as those of initial values. In the zones
assigned with rock type ROCK2 where high temperature fluid flows horizontally from northwest to
southeast between Layer F and Layer H, the highest
permeability for horizontal and vertical directions
were estimated to be 3.0×10-14 m2 and 1.0×10-15 m2,
Figure 8. Measured and simulated temperature profiles of 6 wells DNG-7,
DNG-8, DNG-11, DNG-9, DNG-6 and DNG-5.
Table 1. Estimated permeabilities of rock types.
Rock type
5. Simulation Results and Discussion
Figure 8 compares measured and simulated temperature profiles of 6 wells. The simulation was conducted using parameter
values of the optimal model. Permeabilities of the optimal model
are summarized in Table 1, deep recharge rates were the same as
those used in Section 4.
kx, ky
6. Conclusions
We developed a numerical model of the Dieng geothermal
field by forward analysis with TOUGH2. Parameters included in
the model such as permeability, flow rates and enthalpies of deep
recharges were estimated. The results are summarized as follows:
1) The model can successfully reproduce the temperature profiles of 11 exploratory wells with natural state simulation.
2) The temperature distribution in natural state as shown by
Layman et al. (2002) was reproduced. A high temperature
zone of more than 300°C was confirmed in the Sileri area
at depth.
Figure 9. Temperature distribution in Layer G.
Hino, et al.
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Authors thank Geo Dipa Energi for their permission using
field data in this paper.
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