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Conventional Natural Gas Project Investment and Decision Making under Multiple Uncertainties

Author

Listed:
  • Chi Yong

    (College of Logistics, Chengdu University of Information Technology, Chengdu 610225, China)

  • Mu Tong

    (School of Finance, Southwest University of Finance and Economics, Chengdu 611130, China)

  • Zhongyi Yang

    (School of Computing and Artificial Intelligence, Southwestern University of Finance and Economics, Chengdu 611130, China)

  • Jixian Zhou

    (School of Computing and Artificial Intelligence, Southwestern University of Finance and Economics, Chengdu 611130, China)

Abstract

Similar to many energy projects, the evaluation of investments in natural gas projects is influenced by technical and economic uncertainties. These uncertainties include natural resource characteristics, production, decline laws, prices, taxes, benchmark yield, and so on. In China, conventional natural gas is still the dominant energy source. The investors are mainly large state-owned energy companies. Therefore, it is necessary to include the technical and economic uncertainties, as well as the investment decision and optimization problems of the enterprises in a unified analytical framework. To this end, this paper innovatively constructs such a framework. Using numerical simulations of approaches, the process of investment decision optimization by companies based on technology assessment and price forecasting is visualized in detail. The results suggest that the investment decision of the enterprise needs to consider technical and economic uncertainties in an integrated manner. It also needs to combine the business strategy and social responsibility of the enterprise in order to construct the objective function. With the availability of data, the framework and its algorithms can be used for practical evaluation of investment plans and decision supports for conventional natural gas projects. The framework can also integrate the analytical perspective of the macroeconomic and political environment to bring in a more comprehensive range of uncertainties.

Suggested Citation

  • Chi Yong & Mu Tong & Zhongyi Yang & Jixian Zhou, 2023. "Conventional Natural Gas Project Investment and Decision Making under Multiple Uncertainties," Energies, MDPI, vol. 16(5), pages 1-30, February.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:5:p:2342-:d:1083840
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    References listed on IDEAS

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    1. Jianzhong Xiao & Jinhua Cheng & Jun Shen & Xiaolin Wang, 2017. "A System Dynamics Analysis of Investment, Technology and Policy that Affect Natural Gas Exploration and Exploitation in China," Energies, MDPI, vol. 10(2), pages 1-19, January.
    2. Méjean, Aurélie & Hope, Chris, 2008. "Modelling the costs of non-conventional oil: A case study of Canadian bitumen," Energy Policy, Elsevier, vol. 36(11), pages 4205-4216, November.
    3. Zhihua Chen & Hui Wang & Tongxia Li & Ieongcheng Si, 2021. "Demand for Storage and Import of Natural Gas in China until 2060: Simulation with a Dynamic Model," Sustainability, MDPI, vol. 13(15), pages 1-19, August.
    4. Welkenhuysen, Kris & Rupert, Jort & Compernolle, Tine & Ramirez, Andrea & Swennen, Rudy & Piessens, Kris, 2017. "Considering economic and geological uncertainty in the simulation of realistic investment decisions for CO2-EOR projects in the North Sea," Applied Energy, Elsevier, vol. 185(P1), pages 745-761.
    5. Maren Diane Schmeck & Stefan Schwerin, 2021. "The Effect of Mean-Reverting Processes in the Pricing of Options in the Energy Market: An Arithmetic Approach," Risks, MDPI, vol. 9(5), pages 1-19, May.
    6. Valery Salygin & Igbal Guliev & Natalia Chernysheva & Elizaveta Sokolova & Natalya Toropova & Larisa Egorova, 2019. "Global Shale Revolution: Successes, Challenges, and Prospects," Sustainability, MDPI, vol. 11(6), pages 1-18, March.
    7. Zhu, Lei & Zhang, ZhongXiang & Fan, Ying, 2015. "Overseas oil investment projects under uncertainty: How to make informed decisions?," Journal of Policy Modeling, Elsevier, vol. 37(5), pages 742-762.
    8. Méjean, Aurélie & Hope, Chris, 2013. "Supplying synthetic crude oil from Canadian oil sands: A comparative study of the costs and CO2 emissions of mining and in-situ recovery," Energy Policy, Elsevier, vol. 60(C), pages 27-40.
    9. Weiwei Xiong & Liang Yan & Teng Wang & Yuguo Gao, 2020. "Substitution Effect of Natural Gas and the Energy Consumption Structure Transition in China," Sustainability, MDPI, vol. 12(19), pages 1-20, September.
    10. Per Bjarte Solibakke, 2021. "Forecasting Stochastic Volatility Characteristics for the Financial Fossil Oil Market Densities," JRFM, MDPI, vol. 14(11), pages 1-17, October.
    11. McGlade, Christophe & Speirs, Jamie & Sorrell, Steve, 2013. "Methods of estimating shale gas resources – Comparison, evaluation and implications," Energy, Elsevier, vol. 59(C), pages 116-125.
    12. Xu, Guangyue & Dong, Haoyun & Xu, Zhenci & Bhattarai, Nishan, 2022. "China can reach carbon neutrality before 2050 by improving economic development quality," Energy, Elsevier, vol. 243(C).
    13. Julien Chaisse & Jamieson Kirkwood, 2020. "Chinese Puzzle: Anatomy Of The (Invisible) Belt And Road Investment Treaty1," Journal of International Economic Law, Oxford University Press, vol. 23(1), pages 245-269.
    14. Rui Guo & Dongkun Luo & Xu Zhao & Jianliang Wang, 2016. "Integrated Evaluation Method-Based Technical and Economic Factors for International Oil Exploration Projects," Sustainability, MDPI, vol. 8(2), pages 1-19, February.
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