Abstract
In this paper we focus on investment policy problems of unconventional oil exploitation and set up a dynamic programming model to help decision makers decide how to allocate the limited resources among a set of unconventional oil projects to maximize the total expected profits from investment horizon. Firstly, the urgency and feasibility of developing unconventional oil were introduced. Secondly, the properties of unconventional oil resources and the difficulty and complexity of exploiting them were analyzed. Thirdly, a multi-stage decision model was developed to help oil companies select an optimal investment policy given return on investment. Finally, a numerical example was provided by applying the model through backward recursion algorithm. The results demonstrate that the dynamic programming model provides an effective and efficient decision support tool for optimal investment policy of unconventional oil exploitation.
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References
Méjean, A.: Modelling the costs of non-conventional oil: A case study of Canadian Bitumen. Energy Policy 36, 4205–4216 (2008)
Bakhtiari, A.M.S.: World oil production capacity model suggests output peak by 2006–2007. Oil and Gas Journal 102(16), 18–20 (2004)
Söderbergh, B., Robelius, F., Aleklett, K.: A crash programme scenario for the Canadian oil sands industry. Energy Policy 35, 1931–1947 (2007)
Sovacool, B.K.: Solving the oil independence problem: Is it possible? Energy Policy 35, 5505–5514 (2007)
Doerr, B., Eremeev, A., Neumann, F., et al.: Evolutionary algorithms and dynamic programming. Theoretical Computer Science 412, 6020–6035 (2011)
Bellman, R.E.: Dynamic Programming-Republished 2003. Princeton University Press, Princeton (1957)
de Castro, C., Miguel, L.J., Mediavilla, M.: The role of nonconventional oil in the attenuation of peak oil. Energy Policy 37, 1825–1833 (2009)
Chen, J., Li, C., Chen, X.: Oil Supplement and Substitution. Sinopec Press, Beijing (2009)
Greene, D.L., Hopson, J.L., Li, J.: Have we run out of oil yet? Oil peaking analysis from an optimist’s perspective. Energy Policy 34, 515–531 (2006)
Dyni, J.R.: Geology and resources of some world oil-shale deposits. Oil Shale 20, 193–252 (2003)
Svensson, E., Strömberg, A.-B., Patriksson, M.: A model for optimization of process integration investments under uncertainty. Energy 36, 2733–2746 (2011)
Hubbert, M.K.: Nuclear energy and the fossil fuels. In: Drilling and Production Practice. American Petroleum Institute (1956)
Hu, X., Qian, G., Hu, Y.: A Research on the Knowledge Representation for Discrete Dynamic Programming Model and Its IBFS Algorithm. Journal of Harbin Institute of Technology 28(3), 119–126 (1996)
Kennedy, J.O.S.: Principles of dynamic optimization in resource management. Agricultural Economics 2(1), 57–72 (1988)
Salameh, M.G.: Can renewable and unconventional energy sources bridge the global energy gap in the 21st century? Applied Energy 75, 33–42 (2003)
van Asseldonk, M.A.P.M., Huirne, R.B.M., Dijkhuizen, A.A., Beulens, A.J.M., et al.: Dynamic programming to determine optimum investments in information technology on dairy farms. Agricultural Systems 62, 17–28 (1999)
Erturk, M.: Economic analysis of unconventional liquid fuel sources. Renewable and Sustainable Energy Reviews 15, 2766–2771 (2011)
Dale, M., Krumdieck, S.: Pat Bodger. Net energy yield from production of conventional oil. Energy Policy 39, 7095–7102 (2011)
Mohr, S.H., Evans, G.M.: Peak oil: testing Hubbert’s curve via theoretical modeling. Natural Resources Research 17(1), 1–11 (2008)
Owenn, N.A., Inderwildi, O.R., King, D.A.: The status of conventional world oil reserves–Hype or cause for concern. Energy Policy 38, 4743–4749 (2010)
Carraway, R.L., Schmidt, R.L.: An improved discrete dynamic programming algorithm for allocating resources among interdependent projects. Management Science 37(9), 1195–1206 (1991)
Kaufmann, R.K., Shiers, L.D.: Alternatives to conventional crude oil: When, how quickly, and market driven? Ecological Economics 67, 405–411 (2008)
Mohr, S.H., Evans, G.M.: Long term prediction of unconventional oil production. Energy Policy 38, 265–276 (2010)
Bardi, U.: Peak oil: The four stages of a new idea. Energy 34(3), 323–326 (2009)
U.S. Department of the Interior, Bureau of Reclamation Upper Colorado Region. Quality of water Colorado River Basin Progress Report No.22. U.S. Department of the Interior website (2005), http://www.usbr.gov/uc/progact/salinity/pdfs/PR22.pdf (accessed June 8, 2008)
Yan, L., Chen, J., Zhou, F., et al.: Long term strategy of supplement and substitute for conventional oil in China. Advanced Technology of Electrical Engineering and Energy 25(4), 1–7 (2006)
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Sun, J., Hu, X. (2012). A Dynamic Programming Decision-Making Model of Investment Policy for Unconventional Oil Exploitation. In: Watada, J., Watanabe, T., Phillips-Wren, G., Howlett, R., Jain, L. (eds) Intelligent Decision Technologies. Smart Innovation, Systems and Technologies, vol 15. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29977-3_34
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DOI: https://doi.org/10.1007/978-3-642-29977-3_34
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