Keywords: Geothermal, low-temperature, district heating, pressure draw-down, lumped modelling, management

Transcription

1 Proceedings World Geothermal Congress 2015 Melbourne, Australia, April 2015 The Role of Lumped Parameter Modelling of Reservoir Pressure in the Resource Management of 6 Low-Temperature Geothermal Systems Utilized by the District Heating Network of Nordurorka in Central N-Iceland Gudni Axelsson 1),2), Thorsteinn Egilson 1), Bjarni Gautason 1) and Stefán H. Steindórsson 3) 1) Iceland GeoSurvey (ÍSOR), Grensásvegur 9, 108 Reykjavík, Iceland; 2) University of Iceland, Saemundargata 2, 101 Reykjavík, Iceland; 3) Nordurorka, Rangárvellir, 603 Akureyri, Iceland gax@isor.is Keywords: Geothermal, low-temperature, district heating, pressure draw-down, lumped modelling, management ABSTRACT Six distinct low-temperature geothermal systems, located in the Eyjafjördur region in N-Iceland, are utilized by Nordurorka for district heating of the town of Akureyri and surrounding regions. Five of these systems (Botn, Laugaland, Ytri-Tjarnir, Glerárdalur and Thelamörk) are of low productivity because of their size and geological setting, ranging from 15 to 45 kg/s in average production capacity (60 to 100 C resource temperature). The sixth system, Hjalteyri, which came on line at the end of 2003, is much more productive (> kg/s of 90 C water on average). This blend of several systems of different capacity, along with the fact that production from many of the systems was often uncomfortably close to their capacity before Hjalteyri came on line, has required intricate resource management to be practiced. It has mainly included maintaining reservoir pressure above a certain level in each system and at the same time meeting the demand of the district heating system. Lumped parameter modelling of the pressure changes in all the geothermal systems, with associated future reservoir pressure predictions, has played a key role in this management. The lumped parameter models have been updated intermittently since they were first set up in The repeated modelling has proven to be a very effective resource management tool. Firstly by indicating how to limit production from the less productive systems and secondly by suggesting how much the other systems can additionally contribute. During the history of repeated modelling the capacity estimates for the different systems have either remained relatively unchanged or they have declined somewhat with time. In the case of Hjalteyri, however, the first model revision resulted in a capacity estimate that is 25% higher than the earlier one. 1. INTRODUCTION Geothermal energy plays a major role in the economy of Iceland. At present, high- and low-temperature resources provide about 69% of the primary energy supply for the almost 320,000 inhabitants, or about 170 PJ (1 PJ = J; data for 2012). The principal use of geothermal energy in Iceland is for space heating and currently about 89% of the space heating is by geothermal energy. Other uses of geothermal energy in Iceland include direct uses, such as for industrial applications, swimming pools, snow melting, greenhouses, and fish farming, as well as electricity generation. The low-temperature systems, which by definition have a reservoir temperature below 150 C at 1 km depth, are mainly located outside the volcanic zone that passes through Iceland. The largest such systems are located in SW-Iceland on the flanks of the volcanic zone, but smaller systems are found throughout the country. The heat-source for the low-temperature activity is believed to be the abnormally hot crust of Iceland, with the geothermal gradient in the range of about C/km, outside the volcanic zone. Faults and fractures, which, are kept open by continuously ongoing tectonic activity, play an essential role by providing the channels for the water circulating through the system and extracting the heat. At present, there are 22 public, or municipally owned, geothermal heating companies in Iceland operating 62 separate district heating systems or networks. In Icelandic these are called hitaveita (in the singular). In addition there are numerous smaller private heating systems. Fifty-four of the public hitaveitas, and all of the private ones, use energy from low-temperature geothermal systems. Most of the hitaveitas use the geothermal water directly within the distribution systems. Many hitaveitas have been in operation for several decades, the oldest ones for more than 80 years and several others for years. Much can be learned from their operation, in particular regarding long-term management of low-temperature geothermal resources (Axelsson et al., 2010). Several problems have faced these operations, however, such as excessive pressure drawdown due to overexploitation, cold water inflow, and sea water incursion. None of the hitaveitas have ceased operation, however, and solutions have been found to all the problems. By far, the largest heating company in Iceland is the one serving the capital city of Reykjavik and five neighboring communities (Axelsson et al., 2010). It is operated by Reykjavík Energy and serves more than 180,000 inhabitants. Its geothermal energy use currently amounts to about 12 PJ/yr. Another two hitaveitas serve 18,000 20,000 inhabitants, each. The second largest hitaveita is the one serving several communities on Reykjanes, the very southwest tip of Iceland, which HS Orka supplies with geothermal energy. The third largest hitaveita is the one operated by Nordurorka in the Eyjafjördur-region of central N-Iceland (see Fig. 1). Nordurorka uses 6 distinct low-temperature geothermal systems for district heating of the town of Akureyri (population 18,000) and surrounding regions. The management of these systems, Botn, Laugaland, Ytri-Tjarnir, Glerárdalur, Thelamörk and Hjalteyri, is the subject of this paper. In addition Nordurorka operates 3 other small hitaveitas in the region. The remaining public and private heating companies in Iceland are all relatively small, serving communities ranging in size from a few households to a few thousand inhabitants. 1

2 Comprehensive and efficient resource management is an essential part of successful geothermal utilization (Axelsson, 2008). Such management relies on proper understanding of the geothermal system involved and its dynamic behavior, understanding which depends on extensive data and information collected during exploration, development and utilization. The most important data on a geothermal system s nature and properties are obtained through careful monitoring of its response to long-term production. This includes physical monitoring of mass and heat transport as well as monitoring changes in reservoir pressure and energy content, chemical monitoring and indirect monitoring of reservoir changes and conditions. Therefore, comprehensive and careful monitoring plays a major role in geothermal resource management. Predictions on reservoir response to possible future utilization scenarios, which also play a key role in geothermal reservoir management, are calculated by different kinds of reservoir models. The blend of several geothermal systems of different capacity utilized by Nordurorka, along with the fact that production from many of the systems has often been uncomfortably close to their capacity, has required intricate resource management to be practiced. It has mainly included maintaining reservoir pressure above a certain level in each system and at the same time meeting the demand of the district heating system. Lumped parameter modelling of the pressure changes in all the geothermal systems, with associated future reservoir pressure predictions, has played a key role in this management. The lumped parameter models have been updated intermittently since they were first set up in 1988 and the repeated modelling has proven to be a very effective resource management tool. Figure 1: A map of the Eyjafjördur region showing the geothermal production areas of Nordurorka and the main hot water transmission pipes (updated from Flóvenz et al., 2010). The geothermal areas under discussion here are marked in bold, while other areas in the region are also shown. This paper presents how repeated lumped parameter modelling has been used in the management of the geothermal resources utilized by Nordurorka for providing energy for district heating in Akureyri and selected parts of the Eyjafjördur region. It starts out by reviewing the history and status of geothermal district heating in Eyjafjördur. This is followed by a review of the method of lumped parameter modelling of pressure changes in geothermal systems. Subsequently the repeated lumped parameter modelling of the six geothermal systems, Botn, Laugaland, Ytri-Tjarnir, Glerárdalur, Thelamörk and Hjalteyri, is discussed. The paper is concluded by a brief summary and concluding remarks. 2. GEOTHERMAL DISTRICT HEATING IN EYJAFJÖRDUR Nordurorka is a municipal utility company serving the city of Akureyri (population 18,000) in central N-Iceland and surrounding areas with cold water for consumption, geothermal water for space heating and electricity as well as operating the local sewage disposal system. It has also taken over service in 3 other separate communities in the region; Ólafsfjördur, Hrísey and Grenivík (see Fig. 1). Attempts at finding local geothermal resources for heating Akureyri started as soon as during the middle of last century, but these turned out to be futile at first. During the first oil crisis in the early 1970 s a decision was made to attempt an ultimate exploration effort in the vicinity of Akureyri. This mainly consisted of DC resistivity soundings along with other geophysical as well as geological and geochemical research. This research revealed clear indications of a geothermal anomaly resistivity at 2

3 Laugaland, 13 km south of Akureyri (Flóvenz et al., 2010). This was followed up in 1975 by the drilling of a deep geothermal well which surprisingly yielded around 100 L/s of 95 C by free-flow at the end of drilling. Based on these results the decision was made to build a hitaveita for Akureyri, based on the assumption that it wouldn t be difficult to find more hot water to fulfill the energy demand in Akureyri. The history of district heating in Akureyri and surroundings, which didn t turn out to be as easy as assumed initially, is described by Flóvenz et al. (2010) and in references cited therein. The main highlights are reviewed below. A hitaveita for Akureyri was established in 1977 based on hot water from Laugaland. Drilling was continued in the area but with disappointing results as only 3 out of 8 deep wells turned out to be successful, yet connected with the same fracture zone. Therefore, deep drilling was also performed at Ytri-Tjarnir, 2 km north of Laugaland, which yielded initially 50 L/s of 80 C water. Based on short term pumping tests, and simulations by a Theis model, these two fields were estimated to jointly yield 240 L/s with conventional submergible pumps, which was sufficient for the Akureyri space-heating market. Soon after utilization of the two fields started it became evident that pressure drawdown in both systems would be much greater than had been predicted and after a few years the combined average annual production had declined to 75 L/s. In response to this almost desperate exploration for more geothermal energy was carried out, first by continued deep drilling, which later was reinforced by careful surface exploration. This resulted in the discovery of productive resources in three additional locations (see Fig. 1); at Botn in 1980, in Glerárdalur in 1981 and at Thelamörk in In addition two heat pumps, electric boilers and an oil burner were installed to boost the capacity of the Akureyri hitaveita, as well as the incorporation of comprehensive energy efficiency saving efforts. In addition permanent reinjection of return water was started at Laugland in 1997, which increased the productivity of that system. Through all this it was possible the hitaveita was able to provide enough energy for space heating through its distribution system, yet every winter was associated with the challenge of meeting the heating demands during cold spells. The Hjalteyri geothermal system, which is located on the western shore of the Eyjafjordur fjord in central N-Iceland (Fig. 1), was discovered after a shallow well drilled there revealed an above average temperature gradient. Following this extensive and detailed geothermal prospecting was conducted in the area, which culminated by the drilling of a highly productive production well during the summer of It intersected productive aquifers at around 1200 m depth with a temperature of 90 C, associated with a basaltic dyke, which had been targeted. At the end of drilling the well yielded about 45 L/s by free-flow and more than 100 L/s through air-lift testing. Consequently this new geothermal resource was tested for a period of 13½ months and the observed pressure changes simulated by a lumped parameter model (Axelsson et al., 2005b). According to a conservative estimate, based on predictions by a closed version of the lumped parameter model for Hjalteyri, the production potential of the reservoir was estimated to be of the order of 200 L/s assuming down-hole pumps at depth above m. This is comparable to the production capacity of a few of the most productive low-temperature systems in Iceland. In 2003 a hot water pipeline was constructed from Hjalteyri to Akureyri and towards the end of that year Hjalteyri was hooked up to the hitaveita. This more than doubled the energy production capacity of Nordurorka s district heating system, which for the first time was much greater than the demand. The Hjalteyri reservoir appears to very permeable, or with an internal permeability-thickness of 110 Darcy-m, which is comparable to that of other highly productive low-temperature geothermal systems in Iceland. It also appears large in size, i.e. with a great volumetric storage. This is quite different from the other systems utilized for the Akureyri hitaveita up to that time, which are all of low permeability and relatively small in size. This is believed to result from the fact that the western shore of Eyjafjördur is tectonically active, as evidenced by some recent N-S faulting, in contrast with the region further to the south. The Hjalteyri geothermal anomaly is, furthermore, aligned with three other N-S trending anomalies along the western shore of Eyjafjördur, namely Ytrivik, Brimnesborgir and Hrisey (Fig. 1). Table 1 provides basic information on all the low-temperature geothermal systems utilized by Nordurorka today, including their estimated capacity. The blend of several systems of different capacity, along with the fact that production from many of the systems was often uncomfortably close to their capacity before Hjalteyri came on line, has required intricate resource management to be practiced. It has mainly included maintaining reservoir pressure above a certain level in each system and at the same time meeting the demand of the district heating system. Lumped parameter modelling of the pressure changes in all the geothermal systems, with associated future reservoir pressure predictions, has played a key role in this management, as will be discussed in the following. 3. LUMPED PARAMETER MODELLING Modelling plays an essential role in geothermal reservoir engineering research and hence in geothermal resource development and management. The different modelling methods range from basic volumetric resource assessment or simple analytical modelling of the results of well tests to detailed numerical modelling of a structurally complex geothermal system undergoing an intricate pattern of changes resulting from long-term production. The purpose of geothermal modelling is firstly to obtain information on the conditions in a geothermal system as well as on the nature and properties of the system. This leads to proper understanding of its nature and successful development of the resource. Secondly, the purpose of modelling is to predict the response of the reservoir to future production. Based on the predictions the production potential of the system can be estimated. Model predictions also play a key role in geothermal resource management during long-term utilization, such as to estimate the outcome of different management actions. Numerous examples are available on the successful role of modelling in geothermal resource management (Axelsson and Gunnlaugsson, 2000; O Sullivan et al., 2001). The modelling methods may be classified as either static modelling methods or dynamic modelling methods, with the volumetric method being the main static method. Both involve development of some kind of a mathematical model that simulates some, or most, of the data available on the system involved. The volumetric method is based on estimating the total heat stored in a volume of rock and how much of that can be efficiently recovered. The dynamic modelling methods, in contrast, are based on modelling the dynamic conditions and behavior (production response) of geothermal systems. The main dynamic modelling methods applied to geothermal systems are discussed by Axelsson (2013). They include simple mathematical (analytical) modelling methods, lumped parameter methods and detailed numerical modelling. 3

4 In simple models, such as simple analytical models and lumped parameter models, the real structure and spatially variable properties of a geothermal system are greatly simplified so that analytical mathematical equations, describing the response of the model to energy production may be derived. These models, in fact, often only simulate one aspect of a geothermal system s response. Detailed and complex numerical models, on the other hand, can accurately simulate most aspects of a geothermal system s structure, conditions and response to production. Simple modelling takes relatively little time and only requires limited data on a geothermal system and its response, whereas numerical modelling takes a long time and requires powerful computers as well as comprehensive and detailed data on the system in question. The complexity of a model should be determined by the purpose of a study, the data available and its relative cost. In fact, simple modelling, such as lumped parameter modelling, is often a costeffective and timesaving alternative. It may be applied in situations when available data are limited, when funds are restricted, or as parts of more comprehensive studies, such as to validate results of numerical modelling studies. Table 1: Basic information on the geothermal systems utilized by Nordurorka (updated from Flóvenz et al., 2010). The six systems under discussion here are marked in bold. System Botn Laugaland Ytri-Tjarnir Glerárdalur Thelamörk Hjalteyri Hrísey Ósbrekka Skeggjabrekkudalur Reykir Initial whp 1) (bar) ) 5.8 ~0 Max. pump depth (m) 400 3) ff 4) 100 ff 100 Temperature ( C) ) Estimated well-head pressure, usually not measured directly. 2) Unknown. 3) A submergible down-hole motor pump. 4) Artesian flow / free flow. 5) Mainly based on the results of lumped parameter modelling (see later). 6) With 10 L/s average reinjection. 7) Based on a 30 C reference temperature. Production capacity 5) (l/s) ) (15) Thermal power capacity 7) (MW th ) ) (3.1) Simple modelling has been used extensively to study and manage the low-temperature geothermal systems utilized in Iceland, in particular to model their long-term response to production (Axelsson and Gunnlaugsson, 2000). Lumped parameter modelling of water level and pressure change data, has been the principal tool for this purpose (Axelsson et al., 2005a). Lumped models can simulate such data very accurately, even very long data sets (several decades). Axelsson (1989) presents an efficient method of lumped parameter modelling of pressure response data from geothermal systems and other underground hydrological systems, with pressure changes, in fact, being the primary production induced changes in geothermal systems. The method tackles the simulation as an inverse problem and can simulate such data very accurately, if the data quality is sufficient. It automatically fits the analytical response functions of the lumped models to observed data by using a non-linear iterative least-squares technique for estimating the model parameters. Today, lumped models have been developed by this method for more than 20 low-temperature and 3 hightemperature geothermal systems in Iceland, as well as geothermal systems in China, Turkey, Eastern Europe, Central America and The Philippines, as examples (Axelsson et al., 2005a). The theoretical basis of this automatic method of lumped parameter modelling, and relevant equations, are presented by Axelsson (1989), with a general lumped model consisting of a few tanks and flow resistors. Figure 2 shows the type of lumped parameter model most commonly used. The tanks simulate the storage capacity of different parts of a geothermal system and the pressure in the tanks simulates the pressure in corresponding parts of the system. The first tank of the model in the figure can be looked upon as simulating the innermost (production) part of the geothermal reservoir, and the second and third tanks simulate the outer parts of the system. The third tank is connected by a resistor to a constant pressure source, which supplies recharge to the geothermal system. The model in the figure is, therefore, open. Without the connection to the constant pressure source the model would be closed. An open model may be considered optimistic, since equilibrium between production and recharge is eventually reached during long-term production, causing the pressure draw-down to stabilize. In contrast, a closed lumped model may be considered pessimistic, since no recharge is allowed into such a model and the water level declines steadily with time, during long-term production. In addition, the model presented in Fig. 2 is composed of three tanks; in many instances models with only two tanks have been used. In the lumped parameter model of Fig. 2 hot water is assumed to be pumped out of the first tank, which causes the pressure in the model to decline. This in turn simulates the decline of pressure in the real geothermal system. When using this method of lumped parameter modelling, the data fitted (simulated) are the pressure (or water level) data for an observation well inside the well-field, while the input for the model is the production history of the geothermal field in question. Axelsson et al. (2005a) present examples of long pressure response histories of geothermal systems distributed throughout the world simulated by lumped parameter models. The examples show that in all of the cases the models developed simulate the pressure changes quite accurately. Yet because of how simple the lumped parameter models are, their reliability is sometimes questioned. Experience has shown that they are quite reliable, however, and examples involving repeated simulations, demonstrate 4

5 this clearly (Axelsson et al., 2005a). This applies, in particular, to simulations based on long data sets, which is in agreement with the general fact that the most important data on a geothermal reservoir are obtained through careful monitoring during long-term exploitation. Lumped parameter modelling is less reliable when based on shorter data sets, which is valid for all such reservoir engineering predictions. Once a satisfactory fit with observed pressure data has been obtained the corresponding lumped parameter models can be used to calculate predictions for different future production scenarios. Future pressure changes in geothermal systems are expected to lie somewhere between the predictions of open and closed versions of lumped parameter models, which represent extreme kinds of boundary conditions. The differences between these predictions simply reveal the inherent uncertainty in all such predictions. Real examples demonstrate that the shorter the data period a simulation is based on is, the more uncertain the predictions are (Axelsson et al., 2005a). They also demonstrate that the uncertainty in the predictions increases with increasing length of the prediction period. Figure 2: A 3-tank lumped parameter model commonly used to simulate pressure changes in geothermal systems (from Axelsson et al., 2005a). 4. LUMPED PARAMETER MODELLING IN NORDURORKA S RESOURCE MANAGEMENT Lumped parameter modelling of the pressure changes in the geothermal systems utilized by Nordurorka has played a key role in their resource management, as already mentioned. This has mainly involved utilizing both short- and long-term pressure predictions calculated by the models. Firstly by using the predictions to estimate how to limit production from the less productive systems and secondly by suggesting how much the other systems can additionally contribute. In the cases of the systems at Botn, Laugaland, Ytri-Tjarnir, Glerárdalur and Thelamörk, the lumped parameter modelling has been repeated on three occasions, as can be seen in Table 2. In addition, the lumped parameter modelling for Hjalteyri has been repeated once. Table 2: Overview of lumped parameter modelling studies of the six main geothermal systems utilized by Nordurorka, and consequent revisions of the models. System Initial study Later revisions Botn Laugaland Ytri-Tjarnir Glerárdalur Thelamörk Hjalteyri , 1999, , 1999, , 1999, , 1999, , 2002, Repeating the modelling, i.e. updating the models based on new reservoir pressure observations, has been considered important for the following reasons: The accuracy of reservoir response modelling increases as longer datasets are used; The accuracy of reservoir pressure (water-level) predictions diminishes with the length of time since the end of a simulation period; Changes can, furthermore, occur in a geothermal systems, either suddenly or gradually, which can be difficult to detect except with modelling; Finally, interference between adjacent systems can disturb modelling calculations as being applied here, where systems are treated as separate and isolated. This chapter describes briefly the latest revisions of the lumped parameter models for the six geothermal systems, which is described in full detail by Axelsson et al. (2013). Only some selected examples are presented, as space does not allow a full presentation of the modelling and results for all the six systems. It should be noted that in all the cases reservoir pressure changes are monitored as changes in water level, either in the particular production wells involved or in specially designated observation wells. Also that lumped parameter modelling has been deemed to be the most effective modelling method for the resource management of Nordurorka, as it is both time-saving, accurate and reliable. 5

6 4.1 Reliability of Earlier Models Before the lumped parameter models are updated the reliability, or consistency, (see also a discussion of this by Axelsson et al., 2005) of the previous revision is usually checked. This is done by using a previous model version to calculate water-level changes according to the production history of the system in question, from the time of the previous revision up to the present. The discrepancy between observed and calculated values can then be used to evaluate the reliability of the particular model in question. In general the discrepancy reduces, and the reliability increases, as the time-series in question grow longer. In the case of Botn, Laugaland, Ytri-Tjarnir and Glerárdalur the previous models are from 1999, while in the cases of Telamörk and Hjalteyri the previous models are from 2002 and 2003, respectively (Table 2). Figures 3 and 4 show the results of such reliability checks for two of the Nordurorka systems, Glerárdalur and Hjalteyri, as examples. Figure 3: Comparison between measured water level in the Glerárdalur geothermal system and water level calculated by a lumped parameter model developed in 1999 (Axelsson et al., 2013). The filled black boxes show water level values on which the 1999 model was based but the open purple boxes measured values after the 1999 model was set up. The red line show the water level calculated by the 1999 model. The divergence between the open boxes and the red line reflects the reliability of the 1999 model. The lower half of the figure shows the production history of Glerárdalur. In general the reliability of the older models appears to have been quite good. In the case of Glerárdalur (Fig. 3) the 1999 model seems to have been somewhat conservative. In the case of Hjalteyri the original models for the system are seen to have been quite realistic, in particular in view of the short production history the earlier model was based on (about a year). The same applies to the other four systems, except perhaps Laugaland were an increasing discrepancy is seen for the last few years modelled. 4.2 Updated Modelling The lumped parameter models for the six geothermal systems were revised, or updated, once again in 2013 by making them simulate revised water-level data-series extending up to that year as accurately as possible. Figures 5 and 6 show examples of the simulation results for two of the systems, Botn and Ytri-Tjarnir. In the case of Ytri-Tjarnir a quite good fit between data and model simulation is achieved, while a somewhat greater data scatter is seen in the case of Botn. The simulations for the other four systems are considered reasonably good, while the general observation is made that the quality of water-level data has diminished during the last decade or so, compared with earlier data which generally was of quite high quality (Axelsson et al., 2013). It should be noted that modelling of the Laugaland system did turn out to be less straightforward than modelling of the other five systems, mainly because of discontinuities in its water-level history (disparate wells used for observations) and uncertainties due to the incorporation of reinjection into the net production used as input for the lumped parameter modelling. The parameters of the lumped parameter models reflect the reservoir properties of the geothermal systems involved. These will not be discussed here in detail, but overall permeability estimates range from about 1 to 200 Darcy-m in production parts of the systems, with the value for Hjalteyri being highest and the value for Botn lowest. This large range reflects a great variability in the nature of the systems, in particular when comparing the Hjalteyri system with the rest. The nature and properties of the geothermal systems utilized by Nordurorka are discussed in more detail by Flóvenz et al. (2010). The volumes of the six systems are estimated 6

7 to range from about 7 to 200 km 3. It should be noted that these refer, in fact, to the volumes of the whole geothermal systems, including recharge and reservoir parts (the whole hydrological system) in each case. Figure 4: Comparison between measured water level in the Hjalteyri geothermal system and water level calculated by lumped parameter models developed in 2003 (Axelsson et al., 2013). The filled black boxes show water level values on which the 2003 models were based but the open purple boxes measured values after the 2003 models were set up. The red and green lines show water level calculated by the 2003 models. The divergence between the open boxes and lines reflects the reliability of the 2003 models. The lower half of the figure shows the production history of Hjalteyri. Figure 5: Comparison between measured water level in the Botn geothermal system and water level calculated by revised lumped parameter models (Axelsson et al., 2013). The filled boxes show water level values on which the model is based. The green and red lines show the water level simulated by a closed and an open model, respectively. The lower half of the figure shows the production history of Botn. 7

8 Figure 6: Comparison between measured water level in the Ytri-Tjarnir geothermal system and water level calculated by revised lumped parameter models (Axelsson et al., 2013). The filled boxes show water level values on which the model is based. The green and red lines show the water level simulated by a closed and an open model, respectively. The lower half of the figure shows the production history of Ytri-Tjarnir. 4.3 Reservoir Pressure Predictions Finally the updated lumped parameter models were used to calculate reservoir pressure, or water-level, predictions for all of the six Nordurorka low-temperature systems. The predictions were in all cases calculated with both the open and closed model. These, in fact, provide upper and lower bounds for the predictions, or a kind of sensitivity analysis as discussed by Axelsson et al. (2005). Figures 7 and 8 show examples of future water-level predictions for two of these, Laugaland and Hjalteyri. In these two cases predictions were calculated for two different scenarios for each of the systems; a base-load scenario with constant production and a scenario with annual variations. Predictions were calculated for comparable scenarios for the other four systems and, in addition, for constant rate scenarios with summer breaks for two of the systems. For the two examples presented here (figures 7 and 8) the divergence between the open and closed predictions is quite small for Hjalteyri, but somewhat greater for Laugaland. In general smaller divergence would be expected for longer production histories, but other factors can influence it, e.g. data quality. The divergence for the other four systems is relatively small. The predictions were in all six cases calculated for 15 years, which can be considered an acceptably long prediction period, considering the relatively long water-level histories involved. The predictions were calculated on the premises that the water level in each system stay well above the maximum pump depth of each system (see Table 1), i.e. by varying the flow-rate values of the scenarios so that water-level didn t exceed the maximum limit during the prediction period. In the case of Hjalteyri (Fig. 8), the most productive system, a pump depth of only 200 m was assumed, even though the production wells at Hjalteyri and the pumps presently in use would allow a depth of m. This results in a relatively conservative capacity estimate, in view of the relatively short production history of the system. The revised capacity estimates for the six Norduorka systems will not be discussed in detail here, but the total production capacity of the six geothermal systems combined is estimated in the range of L/s (depending on different prediction scenarios), corresponding to a total thermal power of about 91 MW th (see a summary in Table 1). The Hjalteyri system, which is by far the most productive system, provides about 2/3 of the total thermal power capacity of Nordurorka. During the history of repeated modelling the capacity estimates for the different systems have either remained relatively unchanged or they have declined somewhat with time. In the case of Hjalteyri, however, the first model revision resulted in a capacity estimate that is 25% higher than the earlier one. 5. CONCLUSIONS This paper has described the utilization of lumped parameter modelling of pressure changes in low-temperature geothermal systems utilized by the municipal utility company Nordurorka for district heating of the town of Akureyri and surrounding regions. Six distinct low-temperature geothermal systems, located in the Eyjafjördur region in N-Iceland, are utilized by Nordurorka, in addition to a few others further afield. Five of the six systems (Botn, Laugaland, Ytri-Tjarnir, Glerárdalur and Thelamörk) are of low productivity because of their size and geological setting while the sixth system, Hjalteyri, is much more productive. This blend of several systems of different capacity, along with the fact that production from many of the systems was often uncomfortably close 8

9 to their capacity before Hjalteyri came on line, has required intricate resource management to be practiced. It has mainly included maintaining reservoir pressure above a certain level in each system and at the same time meeting the demand of the district heating system. Lumped parameter modelling of the pressure changes in all the geothermal systems, with associated future reservoir pressure predictions, has played a key role in this management. The lumped parameter models have been updated intermittently since they were first set up in 1988, which has proven to be a very effective resource management tool. Figure 7: Water level predictions for well LJ-8 at Laugaland (used as reference), for two future production scenarios, calculated by a closed and an open lumped parameter model of the system. The lower half of the figure shows total production minus 50% of reinjection in the area (i.e. production values used in the modelling); 25% reinjection is assumed in both scenarios. Figure 8: Water level predictions for well HJ-20 on Hjalteyri for two future production scenarios, calculated by a closed and an open lumped parameter model of the system. The lower half of the figure shows the total production (no reinjection). 9

10 The lumped parameter models were updated again in 2013, based on water-level data collected up to that time. Based on predictions calculated by all the models up to 2025 for different future utilization scenarios, and maximum pump setting depths, the average combined production capacity of the six systems corresponds to about 380 L/s. Yet, the production capacity of each of the systems is somewhat variable depending on whether constant base load is assumed or annual variations in production. The combined mass flow production capacity, furthermore, corresponds to about 91 MW th, or about twice the present average thermal energy utilization. At a 2% annual increase in energy demand the currently estimated capacity will meet the needs of the Nordurorka hitaveita up to the year The repeated modelling has proven to be a very effective resource management tool. Firstly by indicating how to limit production from the less productive systems and secondly by suggesting how much the other systems can additionally contribute. During the history of repeated modelling the capacity estimates for the different systems have either remained relatively unchanged or they have declined somewhat with time. In the case of Hjalteyri, however, the first model revision resulted in a capacity estimate that is 25% higher than the earlier one. The Hjalteyri system, which only came on-line in late 2003, supports about 2/3 of the presently estimated thermal power capacity of the six geothermal systems presented in this paper, owing to its much greater permeability and size, which can be attributed to the tectonic activity of the western shore of Eyjafjördur, where Hjalteyri is located. The other five systems are embedded in much less active parts of the Eyjafjördur region, even though they are not far from Hjalteyri. REFERENCES Axelsson, G.: Dynamic modelling of geothermal systems, Proceedings, Short Course V on Conceptual Modelling of Geothermal Systems, organized by UNU-GTP and LaGeo, Santa Tecla, El Salvador, (2013), 21 pp. Axelsson, G.: Management of geothermal resources, Proceedings, Workshop for Decision Makers on the Direct Heating Use of Geothermal Resources in Asia, organized by UNU-GTP, TBLRREM and TBGMED, Tianjin, China, (2008), 15 pp. Axelsson, G.: Simulation of pressure response data from geothermal reservoirs by lumped parameter models, Proceedings, 14 th Workshop on Geothermal Reservoir Engineering, Stanford University, USA, (1989), Axelsson, G., and Egilson, Th.: Re-assessment of the production capacity of the geothermal systems at Botn, Laugaland, Ytri- Tjarnir, Glerárdalur, Thelamörk and Hjalteyri in Eyjafjördur, Iceland GeoSurvey report (in Icelandic), ÍSOR-2013/052, Reykjavík, (2013), 58 pp. Axelsson, G., and Gunnlaugsson, E. (convenors): Long-term monitoring of high- and low-enthalpy fields under exploitation, International Geothermal Association, World Geothermal Congress 2000 Short Course, Kokonoe, Kyushu District, Japan, (2000), 226 pp. Axelsson, G., Gunnlaugsson, E., Jónasson, Th., and Ólafsson, M.: Low-temperature geothermal utilization in Iceland Decades of experience, Geothermics, 39, (2010), Axelsson G., Björnsson, G., and Quijano, J.: Reliability of lumped parameter modelling of pressure changes in geothermal reservoirs. Proceedings, World Geothermal Congress 2005, Antalya, Turkey, (2005a), 8 pp. Axelsson, G., Björnsson, G., Egilson, Th., Flóvenz, Ó.G., Gautason, B., Hauksdóttir, S., Ólafsson, M., Smárason, Ó.B., and Sæmundsson, K.: Nature and properties of recently discovered hidden low-temperature geothermal reservoirs in Iceland. Proceedings, World Geothermal Congress 2005, Antalya, Turkey, (2005b), 10 pp. Flóvenz, Ó.G., Árnason, F., Gautason, B., Axelsson, G., Egilson, Th., Steindórsson, S.H., Gunnarsson, H.S.: Geothermal District Heating in Eyjafjördur, N-Iceland; Eighty Years of Problems, Solutions and Success, Proceedings, World Geothermal Congress 2010, Bali, Indonesia, (2010), 8 pp. O Sullivan M.J., Pruess, K., and Lippmann, M. J.: State of the art of geothermal reservoir simulation, Geothermics, 30, (2001),