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Robust geothermal investment decisions under uncertainty: An exploratory financial modeling and analysis approach

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  • Adam, Samuel
  • Setiawan, Andri D.
  • Dewi, Marmelia P.

Abstract

The inherent uncertainty in geothermal projects, high upfront development costs, and insufficient incentives pose significant barriers for investors in achieving returns commensurate with the extensive risks. Therefore, addressing key uncertainties in highly risky phases of geothermal development, such as exploration and exploitation, is needed to pursue the right strategy to minimize the risk of failed investments and increase appropriateness for budget allocation. Using Indonesia's geothermal projects as a case study, this research proposes an exploratory financial modeling and analysis approach to investigating key uncertainties in geothermal projects by combining real options and exploratory modeling. Feature scoring identifies four key uncertainties in the exploration phase (electricity price, fluid dryness, exploration drilling cost, capacity factor) and three key uncertainties in the exploitation phase (production well success ratio and costs of development and injection wells). Meanwhile, dimensional stacking explores potential robust scenarios. For instance, this study reveals that when the electricity price is limited to 8.36 cents/kWh, achieving fluid dryness above 22 % and exploration drilling costs below $8.14 million are crucial for ensuring robustness. Under more unfavorable conditions, real options can loosen the robustness thresholds by incorporating managerial options into asset valuation, thereby avoiding early abandonment of the project.

Suggested Citation

  • Adam, Samuel & Setiawan, Andri D. & Dewi, Marmelia P., 2025. "Robust geothermal investment decisions under uncertainty: An exploratory financial modeling and analysis approach," Energy, Elsevier, vol. 314(C).
  • Handle: RePEc:eee:energy:v:314:y:2025:i:c:s0360544224040805
    DOI: 10.1016/j.energy.2024.134302
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    References listed on IDEAS

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    1. Bruce Kogut & Nalin Kulatilaka, 2001. "Capabilities as Real Options," Organization Science, INFORMS, vol. 12(6), pages 744-758, December.
    2. Kwakkel, Jan H. & Auping, Willem L. & Pruyt, Erik, 2013. "Dynamic scenario discovery under deep uncertainty: The future of copper," Technological Forecasting and Social Change, Elsevier, vol. 80(4), pages 789-800.
    3. Lee, Ungki & Kang, Namwoo & Lee, Ikjin, 2020. "Choice data generation using usage scenarios and discounted cash flow analysis," Journal of choice modelling, Elsevier, vol. 37(C).
    4. Steve Bankes, 1993. "Exploratory Modeling for Policy Analysis," Operations Research, INFORMS, vol. 41(3), pages 435-449, June.
    5. Kwakkel, Jan H. & Pruyt, Erik, 2013. "Exploratory Modeling and Analysis, an approach for model-based foresight under deep uncertainty," Technological Forecasting and Social Change, Elsevier, vol. 80(3), pages 419-431.
    6. Spyridon Karytsas & Dimitrios Mendrinos & Theoni I. Oikonomou & Ioannis Choropanitis & Attila Kujbus & Constantine Karytsas, 2022. "Examining the Development of a Geothermal Risk Mitigation Scheme in Greece," Clean Technol., MDPI, vol. 4(2), pages 1-21, May.
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