gis model for geothermal resource exploration in akita and iwate prefectures, northern japan

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Computers & Geosciences 33 (2007) 1008–1021

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GIS model for geothermal resource exploration in Akita andIwate prefectures, northern Japan

Younes Noorollahi�, Ryuichi Itoi, Hikari Fujii, Toshiaki Tanaka

Department of Earth Resources Engineering, Kyushu University, Fukuoka 812-8581, Japan

Received 10 July 2006; received in revised form 27 October 2006; accepted 9 November 2006

Abstract

In this study, a Geographic Information System (GIS) is used as a decision-making tool to target potential regional-scale

geothermal resources in the Akita and Iwate prefectures of northern Japan. The aims of the study are to determine the

relationships between geothermal wells and geological, geochemical, and thermal data layers within the GIS and to use

these relationships to identify promising areas for geothermal exploration. We calculated the distances from existing

productive geothermal wells to Quaternary volcanic rocks, calderas and craters, faults, hot springs, fumaroles, and

hydrothermal alteration zones. The dominant distances were then defined for each evidence layer. We used ArcMap to

develop a GIS Model for Geothermal Resource Exploration (GM-GRE) consisting of geoprocessing tools and a

modelbuilder. Areas of geothermal potential were defined and prioritized by assigning a weighted overlying selection query

for geological, geochemical, and thermal data layers. The result shows that 97% of currently productive geothermal wells

in Akita and Iwate prefectures are located within the first priority zone selected by the GM-GRE.

r 2007 Elsevier Ltd. All rights reserved.

Keywords: Geothermal; Geochemistry; Temperature gradient; Heat flow; GIS; Geoprocessing

1. Introduction

Active geothermal areas have varied naturalmanifestations at the ground surface. Hot springs,fumaroles, mud pots, and hydrothermal alteration,particularly in areas of high thermal activity, arenatural indicators of geothermal activity, providinga visible indication of the transport of heat andmass through the earth’s crust. Geothermal ex-ploration programs make use of such manifesta-tions and other investigation techniques and

e front matter r 2007 Elsevier Ltd. All rights reserved

geo.2006.11.006

ing author. Tel.: +81 80 5274 2782;

3614.

ess: [email protected] (Y. Noorollahi).

measurements to identify prospective geothermalresources.

A geothermal exploration program is usuallydeveloped on a step-by-step basis, comprisingreconnaissance, feasibility, and assessment. Duringeach stage of the process, the less-prospective areasare gradually eliminated from consideration andremaining efforts are concentrated on the mostpromising areas (Dickson and Fanelli, 2004).

Geothermal exploration management combinesthe results of a number of exploration methods suchas geological, geochemical, and geophysical surveysto locate prospective areas for further development.The basic function of exploration management is toidentify the location and extent of areas that

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warrant further detailed investigation. Identifyingareas of high geothermal potential can be adaunting task for exploration project managers;however, the decision-making process can be madeless cumbersome if it is broken down into thefollowing general steps:

�
Development of site-selection criteria and alayer-combination model � Prioritization of selected potential sites � Selection of prospective areas � Assessment and characterization of the study
area
� Validation of selected area by comparison with
known geothermal fields

The decision-making process involved in locatingprospective areas involves combining the results of anumber of different surveys and studies; humanerrors are unavoidable during this complex proce-dure. To minimize human errors, in the presentstudy we use a Geographical Information System(GIS) to identify prospective areas by combiningvarious digital data layers.

GIS is an important tool for the integralinterpretation of geoscientific data using a compu-terized approach, especially in exploration work.This approach has been used to determine thespatial associations among diverse evidence layersin the area of interest (Coolbaugh et al., 2002,2005a, b; Prol-Ledesma, 2000).

GIS models have also been successfully used inregional exploration for mineral resources (Bon-ham-Carter et al., 1988; Agterberg, 1989; Bonham-Carter, 1991, 1994; Katz, 1991; Chung et al., 1992).The selection of evidence layers (layers involved inthe decision-making process for locating prospectiveareas) can be carried out by technical experts suchas engineers and scientists in order to makedecisions on further work (Campbell et al., 1982;McCammon, 1993). The application of GIS in thefield of mineral exploration is based on the fact thatthe fundamental principles involved in the forma-tion of ore deposits are too complex to beapproximated using analytical mathematical models(Bonham-Carter, 1991).

Geothermal exploration could potentially usesuch a GIS-based technique at several of theexploration stages. Geothermal exploration requiresthe analysis of data by combining various sets ofgeoscientific information, including surface geology,the location of geothermal signatures, geomagnetic

and gravity measurements, thermal data (tempera-ture gradient and heat flow), the geochemistry ofsurface manifestations, and remote sensing data.Analysis of the data is conducted by experts whothen decide upon the location and extent of themost promising geothermal prospect area.

A GIS-based decision-making system has beenapplied previously in a suitability analysis forgeothermal resource exploration in the NamafiallGeothermal Field in Iceland (Noorollahi, 2005) andin Nevada (Coolbaugh et al., 2002, 2005a, b). Theresults of these earlier studies show that the locationand extent of geothermal well sites defined by theGIS method correlates strongly with the areadefined by conventional methods. Similar to thework presented by Coolbaugh et al. (2002,2005a, b), the present work focuses on evaluatingthe potential of a GIS model during the early stagesof regional-scale geothermal exploration in theAkita and Iwate prefectures, northern Japan, todetermine the location and extent of the mostpromising geothermal fields.

2. Study area

Geothermal areas in Japan with high-enthalpyresources are mainly located along two volcanicfronts: one that trends north–south through easternJapan (from Hokkaido via eastern Honshu Islandto the Izu Islands), and another that trends fromKyushu Island to the Southwestern Islands (Kawazoeand Shirakura, 2005).

Most of the developed geothermal fields withinJapan are located within Quaternary and Tertiaryvolcanic zones. Hot springs and fumarolic fieldsaround Quaternary volcanoes are derived fromandesitic or dacitic volcanism. Most dacitic andandesitic lava domes or volcanic spines act as a heatsource, and natural hydrothermal systems thatoccur in the vicinity of the intrusive rocks producefumaroles and/or hot springs at the surface.Geothermal fields in Japan are associated withQuaternary andesitic and dacitic volcanism andTertiary acidic intrusives (Ishikawa, 1970).

The present study area is located across Akitaand Iwate prefectures within the Tohoku volcanicarc, northern Japan (Fig. 1). The Tohoku volcanicarc on the Japanese islands of Honshu and south-western Hokkaido is generated by subduction of theoceanic Pacific Plate beneath the continental NorthAmerican Plate and Okhotsk Microplate. The arc

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Fig. 1. Location map of study area showing existing geothermal power plants.

Y. Noorollahi et al. / Computers & Geosciences 33 (2007) 1008–10211010

generates significant volcanic and geothermal activ-ity (Tamanyu et al., 2000).

Several geothermal fields are currently in produc-tion in the central and southwest parts of the studyarea. Geothermal power plants are currently oper-ating at Sumikawa, Ohnuma, Matsukawa, Kak-konda, and Uenotai in the Akita and Iwateprefectures (Fig. 1). The goal of the present workis to define the geothermal potential of the areausing a GIS Model for Geothermal ResourceExploration (GM-GRE) and to validate the resultson the basis of the locations of known geothermalfields.

3. Methodology

We used GIS to carry out a suitability analysisand site selection because it can handle a largeamount of data, is a powerful tool to visualize newand existing data, can help produce new maps whileavoiding human errors made during decision mak-ing, and allows the effective management of the GISdata. Using GIS for the suitability analysis requiresassigning a set of suitability and weighting factors.

Three analytical methods were used for selectionqueries: the intersecting, union, and weighted over-lay raster calculating methods. These methodsare described briefly in the following sections.A diagram of the GM-GRE that was used in thedecision-making process to select potential geother-mal sites is illustrated in Fig. 2.

3.1. Intersecting method (AND operation)

The Intersect Tool in ArcInfo calculates thegeometric intersection of any number of featureclasses and data layers that are indicative ofgeothermal activity (e.g., elevated temperaturegradients, surface mapped alteration, etc.). Featuresthat are common to all input data layers are selectedusing this method (Bonham-Carter, 1994). Thisimplies that the selected area is suitable for thepurpose of a study based on all input data layers,and the selected area receives the highest suitabilityranking. Those areas that are common to some butnot all data layers are selected and ranked in thenext priority level. The ranking is carried out basedon the number of intersected layers.

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Fig. 2. Flow diagram of geothermal resource suitability analysis.

Y. Noorollahi et al. / Computers & Geosciences 33 (2007) 1008–1021 1011

Geological data layers were first used to run aselection query to select priority areas. Promisingareas were also selected using geochemical datalayers. These two layers were then overlaid using theintersecting method, and those prospective areasthat were common to the two layers were selected.Finally, the areas were prioritized from high to lowin terms of their potential as a geothermallyprospective area.

3.2. Union method (OR operation)

The Union Tool in Arcinfo creates a new cover-age by overlaying two or more polygon coverages.The output coverage contains the combined poly-gons and the attributes of both coverages. In usingthis method, those areas selected as suitable areas byany one of the evidence layers are combined toprevent the loss of any prospective area defined byjust a single evidence layer.

3.3. Weighted overlay

The powerful raster calculator performs multipletasks such as making selections, performing math-ematical functions, and weighting and combiningrasters for favorability analysis.

The weighted overlay raster calculating processmakes it possible to take all these issues intoconsideration. It reclassifies values in the inputrasters onto a common evaluation scale of suit-ability. The input rasters are weighted (Table 2)relative to their importance and added to producethe output raster.

Using this tool, we classified the study area intodifferent levels of favorability based on explorationdata. The classified data layers were then overlainwith weightings that reflected the importance ofeach data layer in the exploration process. Finally,we derived the output raster that represents thefavorability of the study area.

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4. Spatial distribution analysis of geothermal wells

and evidence layers

To find out the spatial distribution relationship ofknown geothermal resources and GM-GRE evi-dence layers the distance relationship analysisaccomplished in Tohoku district. The GM-GREevidence layers comprised of data layers providedby different exploration surveys, and were used in aGM-GRE. Distance relationship analysis was con-ducted using ArcMap to determine the dominantdistance association of the geothermal wells to datain the GM-GRE evidence layers. The Tohoku areahosts 430 productive geothermal wells in variousgeothermal fields such as Matsukawa, Sumikawa,Ohnuma, Kakkonda, and Uenotai fields. Thesewells were used for the distance relationship analysis.Distances were calculated between the locations ofgeothermal wells and Quaternary volcanic rocks,volcanic calderas and craters, active faults, hotsprings, fumaroles, and hydrothermal alterationzones.

For polygon layers such as those that containdata on Quaternary volcanic rocks and hydrother-mal alteration zones, distance was calculated fromgeothermal wells to the edge of the nearest polygonunit. The distance was defined as a ‘‘zero’’ meter forwells drilled within polygons. For layers thatcontain point data (hot springs and fumaroles),distance was defined from the wellhead to the hotspring or fumaroles. For layers that contain linedata such as volcanic calderas and craters and activefaults, distance was calculated from the wellhead tothe nearest point on the line data.

The calculated dominant distance data for eachlayer was then plotted as a histogram with a 1000mbin size; each bin contains information on the startand end value of the bin range. We performed arelative frequency analysis of calculated distance by

Table 1

Result of calculations and defined distances for evidence layers

Evidence layer Layer type Number o

including 4wells

Quaternary volcanic rocks Polygon 2

Volcanic craters Polyline 6

Active faults Polyline 6

Hot springs Point 4

Fumaroles Point 4

Hydrothermal alteration Polygon 3

specifying a dominant distance for the distributionof wells within each evidence layer. Relativefrequency analysis of measured distance was plottedon the vertical axis, and 5% relative frequency wasselected for identifying a dominant relative distancefor all data layers. In other words, the area withineach evidence layer was classified into 1000mdistance classes; if the numbers of wells locatedwithin a class are equal or more than 5% of allwells, the associated distance is marked up as aselection distance. In further calculations, thisdefined distance was used to define promising areasbased on the data in each layer. The results of thecalculation and defined distances for evidence layersare summarized in Table 1. As an example of theanalysis, Fig. 3 shows a histogram and distributionanalysis of the relative distances from geothermalwells to the locations of hydrothermal alterationzones.

5. Geoprocessing model for GM-GRE

The GM-GRE model was constructed usinggeoprocessing and modelbuilder tools within Arc-Map. The geoprocessing refers to a set of connectedtools and processes used to perform a set offunctions on input data layers and collate theresults into new datasets. Geographical datasetsrepresent raw measurements (for example, satelliteimagery), interpreted and compiled information(for example, geological maps, hot springs, andalteration zone types), or information derived fromother data sources using analysis and modelingalgorithms.

The geoprocessing tool was used to model thedata flows from one structure to another toautomatically perform many common GIS tasks,for example, to import data from various formats,integrate data into the GIS, and perform a number

f class

5% of

Wells inside selected

area (%)

Defined distance for

further analysis (m)

84 2000

94 6000

76 6000

97 4000

88 4000

91 3000

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Fig. 3. Histogram of relative distances from geothermal wells to

margin of the nearest hydrothermal alteration zone.

Y. Noorollahi et al. / Computers & Geosciences 33 (2007) 1008–1021 1013

of standard quality validation checks on importeddata. The ability to automate and repeat such tasksis a powerful capability of GIS.

The modelbuilder tool in ArcGIS was used as agraphical environment in which to develop adiagram of the multiple steps required to completecomplex geoprocessing tasks. When the model isrun, the Modelbuilder processes the input data inthe specified order and generates output data layers.In the GM-GRE for Akita and Iwate prefectures,the input data layers and related parameters arevariable and can be defined by the user when themodel is to be applied to other areas for theselection of potential geothermal sites.

6. Analyses of evidence layers

6.1. Geological evidence layers

Geological studies play an important role in allstages of geothermal exploration. The aim ofgeological evaluation at an early stage of explora-tion is to estimate the likelihood of obtaining usablequantities of steam produced from hot water(Healy, 1970). In the initial stages, a number ofgeothermal areas are typically studied together, withone being chosen for detailed investigation (Rybachand Muffler, 1981). Geological studies also providebackground information for interpreting the dataobtained using other exploration methods. Geological

information can also be used in the production stagefor reservoir development and management. Theduration and cost of exploration can be minimizedby adopting a well-designed exploration programand efficiently coordinating research. The presenceand distribution of young volcanic rocks, activevolcanoes, craters, calderas, and active faults are themain data used in geological evidence layers.

6.1.1. Young volcanic rocks

Most hot springs in Japan occur along Quatern-ary volcanic zones; consequently, their heat sourcesare considered to be linked to the young volcanoesthemselves (Ishikawa, 1970). The presence ofQuaternary volcanic rocks is one of the evidencelayers used for identifying geothermal prospectsbecause recent volcanic activity produces heatsources in the form of intrusive dikes. A locationmap of Quaternary volcanic rocks in the study areais presented in Fig. 4. Digital data on the geologyused for this analysis were extracted from theGeological Map of Japan (Sakaguchi and Takaha-shi, 2002). An analysis of the distance from existinggeothermal wells to Quaternary volcanic rocks inTohoku (Table 1) shows that most of the wells arelocated within 2000m of Quaternary rocks. Thus,the area selected using this criterion was assumed tobe an area of geothermal potential. A 2000m bufferanalysis was carried out on the Quaternary volcanicrocks data layer to identify promising areas basedon the distribution of volcanic rocks. The resultingselected area is shown in Fig. 4.

6.1.2. Active volcanoes, volcanic craters, and calderas

Volcanoes are obvious indicators of undergroundheat sources. Volcanic craters can constitute one ofthe elements in geological exploration for geother-mal resources, as the presence of craters leadsgeologists to assume that the area hosts or hosted agreat deal of volcanic activity. The location ofcraters is one line of evidence for deciding uponwhere to concentrate additional exploration work inthe area to locate a potential prospect.

Most of the craters identified in the present studyare located in the central and northern parts of thestudy area along the boundary of the two pre-fectures, with lesser numbers of craters in thesouthern and south-western areas.

On the basis of the distance calculation fromgeothermal wells to volcanic craters and calderasdescribed in Section 4, a distance of 5000m wasused to select promising areas within this data layer.

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Fig. 4. Distribution of Quaternary volcanic rocks and selected prospective areas.


The locations of craters and calderas in the studyarea were extracted from a digital geological map ofJapan (Geological Survey of Japan, 2004). Toidentify suitable areas based on the presence ofvolcanic features, we conducted a buffer analysiswith 5000m distance; selected areas were defined asprobable geothermal prospects.

6.1.3. Active faults

One of the keys to targeting a region ofgeothermal potential is to understand the role offaults in controlling subsurface fluid flow. Fracturesand faults can play an important role in geothermalfields, as fluid mostly flows through fractures in thesource rocks. The importance of fractures ingeothermal development is well recognized; Hanano(2000) pointed out that faults influence the char-acter of natural convection in geothermal systems.

Blewitt et al. (2003) indicated that at a regionalscale, the locations of existing power-producingplants in Great Basin, USA, and the spatial patternof geothermal wells is strongly correlated with GPS-measured rates of tectonic transtensional strain.

This indicates that in some regions geothermalplumbing systems might be controlled by Quatern-ary fault planes that act as conduits that arecontinuously being extended by tectonic activity.

Active faults in the present study area might alsocontribute to the occurrence of natural convectionin the observed geothermal systems. Accordingly,active faults can be used as an evidence layer in theselection of potential geothermal sites. Active faultswithin the study area were determined from ageothermal resource map of Japan (Geologicalsurvey of Japan, 2002) that defines the faults as apolyline feature class in the GIS environment.

Distance relationship analysis was conducted todetermine the dominant distance association of thegeothermal wells to location of active faultspresented in map 1:250,000 scale. The results showthat 95% of the wells are located in a zone within6000m distance to the active faults. This distanceseems too far to have permeability and fluidcirculation. However, in this scale only major faultzones are presented and there should be severalsmaller and associated faults in detailed scales


which are not presented here and not accounted forin distance relationship calculation. The under-progress work by authors in one of the geothermalfield in this area in the scale of 1:25,000, shows thatin this scale more faults appear and distancerelationship calculation shows 2000m associationdistance. However, in current paper for avoidingunwanted discarding of some prospected area bythis layer the 6000m (data-driven) criteria is appliedto the selection query. Using the ArcMap Buffertool, a selection query was made and the area within6000m of active faults was selected.

6.1.4. Geological suitability

Geological suitability is determined by integratingthe selected areas based on Quaternary volcanicrocks, volcanic craters, and active faults. The threelayers were overlain and the selected areas werecombined (union) to identify geologically suitableareas. A suitability map based on geologicalinvestigations in Akita and Iwate prefectures isshown in Fig. 5.

6.2. Geochemical evidence layers

Geochemistry plays an important role in anyinvestigation of geothermal resources. Geochemical

Fig. 5. Geological suitability map fo

methods are widely used in both preliminary pro-specting and at every stage of geothermal explorationand development. Geochemical evidence layers usedfor geothermal resource prospecting include thedistributions of hydrothermal alteration zones, hotsprings with temperatures in excess of 25 1C, andfumaroles.

6.2.1. Hydrothermal alteration zones

Hydrothermal alteration involves mineralogicalchanges resulting from the interaction of hydro-thermal fluids and rocks. The formation of second-ary minerals in geothermal systems is controlled bythe chemical/physical conditions of the system.For example, the presence, abundance, and stabilityof hydrothermal alteration minerals depend onthe temperature, pressure, lithology, permeability,and fluid composition of the system (Browne,1978; Harvey and Browne, 1991). Thus, analysisof the hydrothermal alteration provides informa-tion on the occurrence of geothermal resources,location of geothermally prospective areas, and thechemical characteristics of deep water within thesystem.

A field survey of alteration zones can indicatethe approximate lateral extent of the geothermalsystem, except where the field is covered with a thick

r Akita and Iwate prefectures.

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layer of impermeable rock. The location anddistribution of surface alteration zones can help toidentify prospective geothermal areas. In otherwords, it is more likely that geothermal resourcesoccur within and around hydrothermal alterationzones than in unaltered areas.

The statistical analysis presented in Table 1 showsthat more than 90% of existing geothermal wells inthe present study are located within 3000m of theedges of alteration zones. To define promising areasbased on the locations of hydrothermal alterationzones (Geological Survey of Japan, 2002), wecarried out a 3000m selection query using theArcMap Buffer tool.

6.2.2. Fumaroles

Fumaroles emit mixtures of steam and othergases to the atmosphere, and are geothermalfeatures that can occur only within active volcanicareas. The statistical analysis of the distance ofexisting geothermal wells from fumaroles in Tohokupresented in Section 4 shows that 88% of the wellsin known geothermal fields are located within4000m of fumaroles. Thus, this distance was usedfor selecting promising areas based on fumarolelocations. A selection query was conducted using

Fig. 6. Geochemical suitability map f

the ArcMap Buffer tool; we selected those areaswithin 4000m of fumaroles.

6.2.3. Hot springs

Hot springs have always provided irrefutableproof of a subsurface heat source. Those locationswhere hot water and steam rise to the surface aretermed geothermally active areas. It is assumed thatthe probability of the occurrence of a geothermalresource is higher in a geothermally active area thanthat in the surrounding area.

Analysis of the spatial distribution of hot springsand geothermal wells shows that 97% of geothermalwells are located within 4000m of hot springs. Thus,this distance was used as an evidence distance toselect promising geothermal areas based on thelocations of hot springs (Geological survey ofJapan, 2005).

6.2.4. Geochemical suitability

Geochemical suitability is defined by integratingselected areas identified on the basis of the locationsof alteration zones, fumaroles, and hot springs.These three layers were overlain and the selectedareas were combined (union) to identify thegeochemically suitable area. A suitability map based

or Akita and Iwate prefectures.


on geochemical investigations in Akita and Iwateprefectures is presented in Fig. 6.

6.3. Thermal evidence layers

Thermal methods in geothermal exploration areused to determine the temperature distribution andthermal anomalies in a study area. Thermalmethods used in geothermal exploration involvethe measurement of subsurface temperature inexploratory wells at specified depths. Using temper-ature–depth measurements coupled with rock con-ductivity data, heat flow can be determined fromgeothermal gradients. Such down-hole temperaturemeasurements provide the most important informa-tion on subsurface heat sources.

We undertook a study of the regional tempera-ture gradient and heat flow in the Akita and Iwateprefectures to identify the nature of geothermalanomalies related to recent volcanism and evaluateprospective geothermal areas.

6.3.1. Data sources

We compiled 200 temperature gradient and heatflow measurements from various sources. To modelthe geothermal temperature gradients and heat flowdistribution, we used data from a geothermalgradient and heat flow database (Geological Surveyof Japan, 2004), exploration reports from ageothermal-promotion survey conducted in Japanby New Energy and Industrial Technology Devel-opment Organization (NEDO), and a database oftemperature profile in wells throughout Japan.

6.3.2. Geothermal gradient

The geothermal gradient represents the rate ofchange in temperature (DT) with depth (Dz) withinthe earth. Measurements of temperature gradientare commonly used to investigate thermal condi-tions within geological formations. The averagetemperature gradient within continental crust is30 1C/km. Elevated geothermal gradients commonlyoccur along faults and in areas around hot springsand volcanoes. Measurement of the temperaturegradient provides an indication of the underlyinggeothermal heat source.

In the present study area, geothermal gradientdata from different sources described in differentunits and coordination systems were converted to1C/km and the Universal Transverse Mercator(UTM) coordination system. The distribution mod-el of the geothermal gradient in the study area was

calculated using the Natural Neighbor method thatis housed in ArcMap-3DAnalyst. Areas wereclassified into five different classes, and the areawith a geothermal gradient of less than 30 1C/kmwas discarded from further analysis. Fig. 7 showsthe distribution model of the geothermal gradient.As is clearly evident from the model, high geother-mal gradients are recorded in northern central partof the study area close to the Hachimantai,Yakeyama, and Iwatesan volcanoes, and in thesouthern area close to Kurikomayama volcano.

6.3.3. Heat flow

The average heat flow in continental regions isapproximately 62mW/m2. Values in excess of 80–100mW/m2 indicate anomalous subsurface geothermalconditions (Brott et al., 1976). Thus, heat-flowmapping is one of the main techniques used ingeothermal resource exploration. By measuringheat flow within boreholes, areas of high heat flowcan be identified directly. The goal of geothermalexploration is to locate and characterize suchgeothermal anomalies, as they may reflect the flowof hot water along a fault zone or the presence ofintrusive rock.

Quantitative results are obtained when geother-mal gradients are converted to heat flow viaFourier’s equation

Q ¼ KqT

qz,

where K is the thermal conductivity of the rocks andqT=qz the vertical temperature gradient.

The Natural Neighbor method within ArcMap-3DAnalyst was used for interpolation and toconstruct a distribution model of heat flow in thestudy area. The study area was classified into thefollowing different levels of heat flow: 61–80,81–100, 101–200, and 201–732mW/m2, with thoseareas with a heat flow of less than 60mW/m2 beingomitted from further analysis. The sites where heatflow was measured and the distribution model mapare shown in Fig. 8.

6.3.4. Thermal suitability: thermal anomalies

integration model

Thermal anomalies in the study area were defineddirectly using the geothermal gradient data and theheat flow measurement distribution model at equalweightings (50% for each layer). The temperaturegradient distribution model is classified into the fiveclasses. Table 2 shows the classes and assigned value

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Fig. 7. Distribution model of geothermal gradient in Akita and Iwate prefectures (in 1C/km).

Fig. 8. Distribution of heat flow within study area.


for each class. The heat flow map is also classifiedinto five classes and particular weight definedfor every classes (Table 2). Based on these layers,

we used weighted overlaying methods to create amap predicting the most likely high temperaturegradient and high heat flow area. Prospective areas


were then classified into five priority levels (Fig. 9).The southern and central parts of the study area arethe most favorable in terms of having a highgeothermal potential.

7. Model integration and favorability analysis

Favorable and unfavorable terrains in the Akitaand Iwate prefectures in terms of geothermal

Table 2

Factor maps and assigned weights

Layer name Factor class (1C/km) Weight

Temperature gradient o30 0.1

31–50 0.3

51–100 0.5

101–200 0.8

4200 0.9

Factor class (mW/m2) Weight

Heat flow o60 0.1

61–80 0.3

81–100 0.5

101–200 0.8

4200 0.9

Fig. 9. Geothermal favorability map based o

potential were defined using three suitability digitalmaps; geological suitability, a geochemical suitabil-ity data layer, and a thermal suitability map. Asdescribed above, each of the suitability maps wasgenerated from geothermal evidence layers.

We used the raster calculator for undertaking afavorability analysis and developing an integrationmodel. This tool overlays raster elements using acommon measurement scale, and each input rasteris weighted according to its importance. The weightis expressed as a relative percentage, and the sum ofthe ‘‘percent influence’’ weights must be equal to100%. The integration of each cell in input rastermaps is calculated by the following:

Rðx1; y1Þ ¼ aAðx1; y1Þ þ bBðx1; y1Þ þ dDðx1; y1Þ,

where, R, A, B, and D denote the map cells in theoutput and input rasters and a, b, and d are thecoefficients of the ‘‘percent influence’’ of each layer.

Geological suitability, geochemical suitability,and thermal suitability maps were used in the finalintegration model. In terms of the percent influenceof these layers, 30%, 30%, and 40% influences wereassigned to the geological, geochemical, and thermalsuitability maps, respectively.

n temperature gradient and heat flow.

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Fig. 10. Geothermal favorability map for Akita and Iwate prefectures.


The weight for each suitability layer are chosenempirically and based on the importance of theevidence layers, which are contributed by it. Thehighest percent influence (40%) value is given to thethermal suitability because thermal data demonstratesthe direct existence of a subsurface heat source, whichis very important in geothermal resource prospectingand two other suitability layers (geological, geochem-ical) received lower and similar weights.

Fig. 10 is a geothermal favorability map for theAkita and Iwate prefectures. The favorable zonesindicated in this map show a strong correlation withthe distribution of existing geothermal wells andknown high-temperature fields. As is illustrated inthe map, 283 producing wells (97.5% of the totalnumber of wells) are located within the first priorityarea (most favorable), with the remaining sevenwells (2.5%) located in the second priority area, andnone located in the third priority area. This clearlydemonstrates that the first and second priority areasrepresent the most prospective zones.

8. Conclusions

We analyzed three different data sources—geo-logy, geochemistry, and thermal conditions—using a

GIS model to assess geothermal potential in theAkita and Iwate prefectures of northern Japan.Digital data layers and maps were used in a GISenvironment to develop a geothermal favorabilitymap. Relationships in terms of the distancesbetween the locations of producing wells and theboundaries of geothermal features such as Quatern-ary volcanic rocks expressed by polygons wereextracted, and the results expressed as favorabilitymaps for the evaluation of geothermal potential.The results demonstrate that the vast majority ofproducing wells that are currently operated forpower generation are located within the first priorityarea.

The model developed in this study shows thatthere are numerous other areas that have a highpotential for geothermal development.

Acknowledgments

The authors gratefully acknowledge the assis-tance of Dr. Lucas Donny Setijadji, who providedtechnical advice and comments on early drafts ofthe manuscript.


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gis model for geothermal resource exploration in akita and iwate prefectures, northern japan

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