Development of an assessment tool to evaluate the geothermal potential of countries

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Development of an assessment tool to evaluate the geothermal potential of

countries

Master-Thesis of

Maximilian Trombitas, MSc

Submitted at the

Department of Economics- and Business Management at the

University of Leoben

Leoben, 21

^st

of August 2011

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AFFIDAVIT

I declare in lieu of oath, that I wrote this thesis and performed the associated research my- self, using only literature cited in this volume.

Date Signature

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Acknowledgements

I have to say many thanks to O.Univ.-Prof. Dipl.-Ing. Dr.mont. Hubert Biedermann, Dipl.- Ing.Alexander Rabengruber and Dipl.-Ing. Dr. Leopold Bräuer for the excellent and interesting theme of the master thesis and their support. The thesis gave me the chance to prove my capabilities and taught me to carry out a project on my own.

I would also like to thank Prof. Dipl.-Ing. Dr.mont. Christian Schmid and Dipl.-Ing. Peter Naderer who answered my numerous questions.

Finally, I would like to thank my family for their help and their support during my whole study period.

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Abstract

OMV is on its way to establish itself as one of Europeans major energy supplier. Therefore, the company is interested in green energy technology and likes to invest in that field of energy production in the future. OMV has already done research on geothermal energy technology and carried out one geothermal energy project in Austria. To be able and ready to increase their geothermal energy portfolio in the next few years, OMV was interested in developing an assessment tool for the geothermal energy potential of their E&P country portfolio.

In a first step, a research on all countries from the OMV E&P portfolio was done and based on the facts the countries were described shortly by their political, economic and geological as- pects. As the OMV E&P portfolio consists of 17 countries which all have different geothermal energy potentials, it was decided to run a pre-screening upfront to filter out all countries with an economical meaningful geothermal energy production potential, to be able to achieve better results regarding the sensitivity of the needed data-packages. By conducting this step, the countries could be minimized to nine potential countries.

To establish the desired assessment tool, a system has been defined as framework for all fur- ther steps. However, multiple criteria decision analysis with a SWING weighting method was cho- sen. After the system evaluation step, all criteria with an influence on a geothermal energy production projects were defined. This process was accomplished with the aid of a top-down ap- proach, a political-economic-social-technological-analysis and expert interviews.

After the assessment tool was established, experts weighted all criteria on their importance for the overall system, the criteria were assigned their appropriate key figure and the different countries were evaluated. To assess the plausibility of the results a sensitivity analysis was carried out.

An easy and understandable assessment tool to determine the geothermal energy potential of different countries was developed, what was proved on its functionality. The results of the tool show reasonable values, with Romania having the highest potential, as the two most interesting regions are based there.

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List of Figures

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List of Abbreviations

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1 Introduction

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1.1 Scope & Structure of Work

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2 Geothermal Energy

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2.1 Geothermal Energy Fundamentals

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2 Bertani, R (2010), p. 2

3 Cp. Kaltschmitt et al (1999), p. 9ff

(16)

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A= High Geothermal gradient B= Normal Geothermal gradient C= Low Geothermal gradient

Figure 2: Geothermal gradient in dependency on depth (=pressure) and lithology⁷

2.2 Geothermal resources

*HRWKHUPDOUHVHUYHVDUHGHILQHGDVWKHIUDFWLRQRIWKHDFFHVVLEOHUHVRXUFHEDVHRU´KHDWLQ SODFHµ ZKLFK DUH FRPPHUFLDOO\ UHFRYHUDEOH *HRWKHUPDO UHVRXUFHV LQ FRQWUDVW DUH UH VRXUFHVZKHUHYLDEOHPDUNHWVRUUHTXLUHGWHFKQRORJ\XQGHUGHYHORSPHQWVHH7DEOH ,QSULQFLSOHJHRWKHUPDOUHVRXUFHFDQEHGLYLGHGE\WKHLUYHUWLFDOSRVLWLRQLQVXUIDFHQHDU DQGGHHSUHVRXUFHVDQGE\WKHLUHQWKDOS\

5 Cp. Kaltschmitt et al (1999), p. 102

6 Cp Lundv (2007), p. 1

7 Source:.Tulane Homepage (Access 08.02.11)

8 Cp. Clauser et al (2006), p. 59

(17)

Table 1: Definition of geothermal resources and their estimated potential¹⁰

2.2.1 Definition by vertical position

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2.2.1.1 Surface-near resources

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*URXQG6RXUFH+HDW3XPSV

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2.2.1.2 Deep geothermal resources

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/LTXLGGRPLQDWHGUHVHUYRLUV

6WHDPGRPLQDWHGUHVHUYRLUV

Clauser et al (2006), p. 59

(18)

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2.2.2 Definition by enthalpy

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13 Cp. Kaltschmitt et al (1999), p. 46f

14 Source: IGA Homepage (access 08.02.11)

(19)

Table 2: Classification of geothermal resources by the definition of enthalpy (all values provided in °C)¹⁵

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2.3 Types of geothermal energy production systems

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2.3.1 Deep borehole heat exchanger

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7KLVWHFKQLTXHZLOOQRWEHGLVFXVVHGIXUWKHULQWKLVWKHVLVDVQRVSHFLDOJHRORJLFDOUHJLRQV DUHQHHGHGWRSURGXFHVXFKHQHUJ\,IWKLVWHFKQLTXHLVXVHGLQGHHSHQRXJKZHOOVHQHUJ\

FDQEHXWLOL]HGLQHYHU\FRXQWU\DOODURXQGWKHZRUOGZLWKRXWDQ\SUREOHPV 2.3.2 Hot Dry Rock

7KH +'5 WHFKQLTXH XVHV WKH VWRUHG KHDW LQ WKH IRUPDWLRQ 7KHUHIRUH WKH IRUPDWLRQ LV DUWLILFLDOO\IUDFWXUHGDQGLVWKHQXVHGDVKHDWH[FKDQJHU$QXPEHURIZHOOVDUHGULOOHGLQWR WKH URFN ZLWK D FOHDUDQFH RI VHYHUDO KXQGUHG PHWHUV DSDUW :DWHU LV FLUFXODWHG GRZQ WKH LQMHFWLRQ ZHOOV DQG WKURXJK WKH +'5 UHVHUYRLU 7KH IOXLG WKHQ UHWXUQV WR WKH VXUIDFH

15 Source: IGA Homepage (access 08.02.11)

17 Cp Werner (2009), p.63

(20)

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2.3.3 Hydrothermal energy technique

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a. Coinshaped vertical cracks

b. Network of micro-cracks, fissures and fractures c. Interconnected large-scale fractures and faults Figure 3: Different heat exchange systems for HDR techniques¹⁹

2.4 Electric power generation systems

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2.4.1 Direct steam plant

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19 Clauser et al (2006), p. 91

F

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(21)

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Figure 4: Direct steam plant²¹

2.4.2 Flash steam plant

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Figure 5: Flash steam plant²³

21 Lundv (2007), p. 5

23 Lundv (2007), p. 5

(22)

2.4.3 Binary plant

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N:

Figure 6: Binary plant²⁵

25 Lundv (2007), p. 5

(23)

3 Development of a geothermal energy assessment tool

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3.1 Geothermal Project key factors

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26 Cp GEOFAR (2009), p.9

(24)

3.1.1 Phases of a geothermal project

Figure 7: Typical project timeline and financing options²⁷

3.1.1.1 Site identification phase

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3.1.1.2 Pre-feasibility phase ± surface exploration

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27 GEOFAR (2009), p.11

28 Cp FORSEO (2008), p. 22

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29 Cp FORSEO (2008), p. 23ff

30 Cp FORSEO (2008), p. 28ff

31 Bundesministerium für Umwelt, Naturschutz und Reaktorsicherheit (2007), p. 20

32 Cp FORSEO (2008), p. 33

33 Cp FORSEO (2008), p. 34ff

34 The World Bank Group: Geothermal Energy

(26)

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Figure 8: Overview about the costs of an average geothermal energy production project in Germany³⁷

3.1.2 Project key factors

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35 Cp FORSEO (2008), p. 49ff

36 The World Bank Group: Geothermal Energy

37 Bundesministerium für Umwelt, Naturschutz und Reaktorsicherheit (2007), p. 21

(27)

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38 Source: Activatedlogic Homepage (11.02.11)

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41 Cp FORSEO (2008), p. 20

42 Cp. Bundesministerium für Umwelt, Naturschutz und Reaktorsicherheit (2007), p. 21

44 Cp. Clauser et al (2006), p. 97ff

45 Cp FORSEO (2008), p. 31ff

(30)

3 Development of a geothermal energy assessment tool

19

11: Cumulative costs vs. time and cumulative risk vs. time of two different geothermal projects (left: mal project with one well to 2750m and a 4MW power plant, right: hydrothermal project with aet to 2000m for district heating) 46

OFAR (2009), p.10

(31)

Figure 12: Capital costs and energy costs of different energy sources⁴⁷.

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48 Cp FORSEO (2008), p. 32

49 Cp FORSEO (2008), p. 44

(32)

3.1.2.4 Area specific key figures

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51 Source: Referenceforbusiness Homepage (Access: 14.02.11)

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Figure 13: MCDA framework⁵³

3.2.1 MCDA methods

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53 Source: Geoinformatics Homepage (Access: 14.02.11)

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54 Cp. Department for Communities and Local Government (2009), p. 31

55 Cp. Linkov et al (2004), p. 3ff

(35)

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Equation 1: SMART calculation equation⁵⁹

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56 Cp. Eisenführ (2003), p 111ff

57 Cp. Linkov et al (2004), p. 7ff

58 Schäfer, R., p. 1ff

59 Fülöp, J., p. 6

(36)

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Equation 2: SWING calculation equation⁶²

3.2.2.2 Outranking methods

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60 Fülöp, J., p. 6

61 Cp. Wang,J. (2009), p. 2271

62 Cp. Jia, J. (1993), p. 6

63 T´kindt (2002), p 305

(37)

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3.3.2.1 Sensitivity analysis methodology

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64 Cp. J. Bortz (2002), p. 357

65 Cp. Wang, J. (2009), p. 2270

(38)

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Figure 14: Australia map with OMV E&P licences (dark blue) and the geothermal potential areas (red cir- cles)⁶⁷

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66 Cp. Staber, S. (2010)

67 Source: OMV Homepage (Access 14.02.11)

(39)

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Figure 15: Austria map with OMV E&P licences (dark green) and the geothermal potential areas (red cir- cles)⁶⁹

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68 Cp. Goldstein B. et al (2008)

70 Source: Regioenergy Homepage (Access 14.02.11)

(40)

Figure 16: Egypt map with OMV E&P licences (dark blue) and the geothermal potential areas (red cir- cles)⁷¹

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Figure 17: Faroe Islands map with OMV E&P licences (dark blue)⁷³

72 Cp. Lashin A. et al (2010), p. 1

Development of an assessment tool to evaluate the geothermal potential of countries