SUMMARY
Commissioned Project on Precision Survey and Analysisof Geothermal Power Generation Introduction Potential (FY 2013)
To promote global warming prevention and ensure energy security, it is important tomake further efforts for reinforcement of renewable energy. Particularly after theGreat East-Japan Earthquake and the disaster of the Fukushima First Nuclear Power
Plant, there has been a growing need for these efforts. Among others, renewableenergy ensures more stabilized power generation than the solar power or wind power
generation. It is extremely important to encourage the geothermal power generation asa base power source.
In Japan, however, there is no new site for geothermal power generation in recent years(after the construction of Hachijojima geothermal power plant in 1999). This will be
due to the high development risk and cost as well as difficulties in reaching agreementwith the local authorities for development. To reduce the geothermal development risk,
it is essential to obtain more precise information on the distribution of geothermal
power generation resources and to share information among the related peoples.
With respect to the geothermal power generation introduction potential, the Ministry of
the Environment has been implementing a "renewable energy introduction potential
survey and "collection of zoning basic information on renewable energy" since fiscal
2009, and has make estimates on a nation-wide scale. This project is intended to
upgrade precision of the information on the distribution of geothermal power generation
resources, to make a more precise estimate of the introduction potential than that of theconventional surveys and to enhance the convenience of wide-ranging business
operators involved in geothermal development.
1. Collection and organization of related information
We have collected and organized the topographic and geographical data, hot spring dataand existing well data required to estimate the density of the geothermal power
generation resources.
2. Estimate of underground temperature structure
Using the hot spring data and well temperature profile data having been collected ororganized, we estimated the underground temperature structure on a nationwide scale bydepth (at intervals of 50 meters) in units of 500-meter mesh. To put it more
specifically, we picked up 8,254 points on available hot spring data and calculated theS-1

Activity Index (AI) for each hot spring point, thereby creating temperature profile data
across the depth. For 459 points in 67 regions where we could obtain the well data ofhigher precision than hot spring data, we created the temperature profile data for eachelevation and replaced the data (in units of 500-meter mesh). Correction andinterpolation were conducted by the principle of least curvature for each depth, with theresult that underground temperature structure was estimated on a nationwide scale(Figures 1 to 3).
To visualize the underground temperature structure at a given site, we created an"underground temperature structure visualization tool" capable of visualizing theunderground structure database (temperature data by 500-meter mesh/depth (at intervalsof 50 m)).
This tool was utilized to configure the following two functions:
Creation of temperature distribution diagram by depth in a given range(approximately 10-km mesh assumed)
Representation of underground temperature data at a given point (center of 500-metermesh) (or graphic representation)

Figure 1

Undergroundtemperature
structure data(G.L. 0 m)

Figure 2

Undergroundtemperature structuredata(G.L. -1000 m)

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Figure 3

Undergroundtemperature structuredata(G.L. -2000 m)

Temperature distribution diagram by depth

Figure 4

Underground temperature
data in 500-meter mesh

Underground temperature structure visualization tool

3. Creation of reservoir bedrock elevation diagram for hydrothermal
resources
Using the geochemical temperature gauge for the existing geographical data, gravity
bedrock depth and hot spring data (a technique for estimating the undergroundtemperature from the result of componential analysis of hot spring water), we estimatedthe reservoir bedrock elevation (reservoir bottom elevation) in units of 500-meter meshand created a reservoir bedrock elevation diagram (Figures 5 and 6). For estimation,
the New Tertiary system and Quaternary system were assumed to be the stratus where
the hydrothermal reservoir bedrock was allowed to be present. Further, since thegeochemical temperature gauge does not provide an effective means for all the hotsprings, we used it after specifying the type of hot spring where this technique wasvalid.

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Figure 5

Reservoir bedrockelevation diagram(across Japan)

Figure 6

Reservoir bedrock elevation diagram(sample: Hokkaido)

4. Setting the scope of possible reservoir bedrocks and creation ofresource density distribution diagram based on the USGS volumetricmethodAfter having studied the scope of possible geothermal reservoir bedrocks, we created a
distribution diagram by estimating the resource density using a USGS volumetricmethod. The following illustrates the assumptions used for estimation:
1)The reference temperature and power generation efficiency were assumed for eachpower generation method.
2)More than one applicable lower limit temperature was assumed.(Steam flash: 150 C,180 C, etc.)
3)In the previous surveys, the low-temperature binary (hot spring power generation)
lower limit temperature was set at 53 C. Based on the result of hearing in thesurvey for last fiscal year, the low-temperature binary (hot spring power generation)
lower limit temperature was also set for 80 C which is the current practical lower
limit temperature.
4)To estimate the resource density (kW/km2), the volume of resources assessed by theUSGS volumetric method was divided by 30 on the assumption that this volume
would be used during the 30-year period.
Figures 7 to 9 illustrate the resource density distribution diagram having been created,while Table 1 shows the volume of geothermal resources (across Japan).

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Figure 7

Resource density
distribution diagram(Steam flash 150 C ormore)

Figure 8

Resource density
distribution diagram(Binary (Rankinecycle assumed) for
120 to 150 C ormore)

Figure 9

Resource density
distribution diagram(Low-temperaturebinary (Carina cycleassumed) for 53 to120 C or more)

Table 1
Power generationmethod

Steam flash

Binary (Rankinecycle assumed)

Calculation of the volume of geothermal resources (across Japan)
Reference: Estimated in 2010 (*)
Volume of geothermal
Targetresourcestemperature
Volume of geothermal resources(unit: 10,000 kW)
classification(unit: 10,000 kW)

150 C or more

2,219

2,357

180 C or more

1,314

Not estimated

200 C or more933

Not estimated

120 to 150 C

120

120 to 180 C

239

108
Not estimated

Low-temperature
199
849
53 to 120 C
binary (Carina143
Not estimated80 to 120 C
cycle assumed)* This estimate is based on the geothermal potential map created by the Institute of Advanced Industrial
Science and Technology in a project "Renewable energy introduction potential survey for fiscal 2010",
Ministry of the Environment.

5. Creating the resource distribution chart on hot spring power
generation
Based on the hot spring data (3,702 spots) having been collected or organized, weextracted 149 spots where the hot springs would meet the requirements of watertemperature of 80 C with a volume of 100 L per minute, which were determined as hot
spring power generation requirements. Further, we studied the procedure forS-5estimating the facility capacity compatible with hot spring power generation. For
these hot springs, we estimated the volume of possible hot spring power generation
where the Carina and Rankine cycles were assumed. This calculation has yielded
76,500 kW for the Carina cycle and 41,400 kW for Rankine cycle. Figures 10 and 11
illustrate the resources distribution chart for hot spring power generation.

Figure 10

Resource distribution chart for
hot spring power generation
where Carina cycle is assumed

Figure 11

Resource distribution chart for
hot spring power generation
where Rankine cycle is assumed

6. Re-estimation of introduction potential
We determined the requirements for the development in the National Parks (special areaof Classes 2 and 3) and requirements for the development by slant excavation, andestimated three types of introduction potential. The introduction potential distribution
chart is illustrated in Figures 12 to 14, and the result of summary is given in Table 2.
For the steam flash power generation of 150 C or more, comparison was made between
the result of survey this year and the result in past years. It has been revealed that theresult of this year is about three times greater than that of the past years. This isconsidered to be due to the addition of the well data. In the meantime, thelow-temperature parity generation of 53 to 120 C is about 20 percent smaller than theresult in the past years. This is because dummy data (AI=0) was added in the areas
devoid of temperature data within 5 km on the periphery, with the result that theunderground temperature in these areas was reduced below that in the previous years.

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Figure 12

Steam flash
introduction potential
distribution chart(150 C or more, basic)

Figure 13 Binary powergeneration
introduction
potential distribution
chart (120 to 150 C
or more, basic)

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Figure 14 Low-temperature binary
power generation
introduction potential
distribution chart (53to 120 C or more,basic)

Table 2Powergeneration
methodIntroduction
potential(unit:10,000 kW)(Reference)
Result ofestimationby thesurvey inpast years

Basic (without National Park or slant
excavation)

785

233(*1)Requirement 1(without National Park or with slant
excavation)

1,267

534(*1)Requirement 2 (with National Parkwithout slant excavation)

1,407

848(*1)

Basic (without National Park or slantexcavation)

446

Not yetestimated

Requirement 1(without National Park or with slantexcavation)

787

Not yetestimated

Requirement 2 (with National Parkwithout slant excavation)

887

Not yetestimated

Basic (without National Park or slantexcavation)

313

Not yetestimated

Requirement 1(without National Park or with slantexcavation)

574

Not yetestimated

Requirement 2 (with National Parkwithout slant excavation)

648

Not yetestimated

Basic (without National Park or slantexcavation)

49

Requirement 2 (with National Parkwithout slant excavation)

68

Not yetestimated

Basic (without National Park or slantexcavation)

93

Not yetestimated

Requirement 2 (with National Parkwithout slant excavation)

136

Not yetestimated

53 to 120 C

Basic (without National Park or slantexcavation)

171

80 to 120 C

Basic (without National Park or slantexcavation)

121

Temperatureclassification

150 C or
more

Power
generation bysteam flash

180 C ormore

200 C ormore

120 to150 C
Binary power
generation
120 to180 C

Low-temperaturebinary power
generation

Steam flash introduction potential summary result

Estimation requirements33(*2)

751(*2)
Not yetestimated* 1 Result of estimation according to "Organization of basic zoning information for renewable energy for fiscal*22012", Ministry of the Environment
Result of estimation according to "A survey of renewable energy introduction potential for fiscal 2010",
Ministry of the Environment.

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7. Verification of the estimation result
We made a comparative verification of the power generation capability of the alreadydeveloped geothermal power plant and the capacity of the virtual facilities. As a result,the volume of the resources was verified for the geothermal power plant that had
already been developed, where the volume of resources had not been found out in thesurvey of the previous years. Further, a hearing was conducted with two business
operators for geothermal development on the overall survey results for the purpose ofverifying the adequacy and validity.
8. Subsequent problem
The problem with the estimation of underground temperature structure is how to cover
the shortage of information and how to handle the high temperature in the deep part.
In the creation of an elevation chart of reservoir bedrock for hot water resources, it isimportant to find out ways for covering the shortage of the information on thepermeability of the ground and to develop a chemical technique including use of ageochemical temperature gauge. In creating the resources density distribution chartand the like, the problems to be solved will be how to set the lowest possible
temperature for power generation according to each power generation method, how toverify the adequacy of the parameters in the volumetric method, and how to ensure
consistency with the actual conditions of power plants. The problem with the hotspring power generation is how to cover the shortage of data on the volume of hot waterand information on steam wells. Further, the common problem is how to ensure
coordination and cooperation with various forms of agencies and organizations that will
promote expansion of the relevant area for detailed surveys, establishment of less costly
survey techniques, and collection/organization of information.

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