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The Role of CO2-EOR for the Development of a CCTS Infrastructure in the North Sea Region: A Techno-Economic Model and Application

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  • Mendelevitch, Roman

Abstract

Scenarios of future energy systems attribute an important role to Carbon Capture, Transport, and Storage (CCTS) in achieving emission reductions. Using captured CO2 for enhanced oil recovery (CO2-EOR) can improve the economics of the technology. This paper examines the potential for CO2-EOR in the North Sea region. UK oil fields are found to account for 47% of the estimated additional recovery potential of 3739 Mbbl (1234 MtCO2 of storage potential). Danish and Norwegian fields add 28% and 25%, respectively. Based on a comprehensive dataset, the paper develops a unique techno-economic market equilibrium model of CO2 supply from emission sources and CO2 demand from CO2-EOR to assess implications for a future CCTS infrastructure. A detailed representation of decreasing demand for fresh CO2 for CO2-EOR operation is accomplished via an exponential storage cost function. In all scenarios of varying CO2 and crude oil price paths the assumed CO2-EOR potential is fully exploited. CO2-EOR does add value to CCTS operations but the potential is very limited and does not automatically induce long term CCTS activity. If CO2 prices stay low, little further use of CCTS can be expected after 2035.

Suggested Citation

  • Mendelevitch, Roman, 2013. "The Role of CO2-EOR for the Development of a CCTS Infrastructure in the North Sea Region: A Techno-Economic Model and Application," VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79950, Verein für Socialpolitik / German Economic Association.
    • Handle: RePEc:zbw:vfsc13:79950
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    References listed on IDEAS

    as
    1. Roman Mendelevitch & Johannes Herold & Pao-Yu Oei & Andreas Tissen, 2010. "CO2 Highways for Europe: Modeling a Carbon Capture, Transport and Storage Infrastructure for Europe," Discussion Papers of DIW Berlin 1052, DIW Berlin, German Institute for Economic Research.
    2. Ibrahim Abada & Steven Gabriel & Vincent Briat & Olivier Massol, 2013. "A Generalized Nash–Cournot Model for the Northwestern European Natural Gas Markets with a Fuel Substitution Demand Function: The GaMMES Model," Networks and Spatial Economics, Springer, vol. 13(1), pages 1-42, March.
    3. Huppmann, Daniel, 2013. "Endogenous production capacity investment in natural gas market equilibrium models," European Journal of Operational Research, Elsevier, vol. 231(2), pages 503-506.
    4. Ibrahim Abada, 2012. "A stochastic generalized Nash-Cournot model for the northwestern European natural gas markets with a fuel substitution demand function: The S-GaMMES model," Working Papers 1202, Chaire Economie du climat.
    5. Hackett Steven C., 1995. "Pollution-Controlling Innovation in Oligopolistic Industries: Some Comparisons between Patent Races and Research Joint Ventures," Journal of Environmental Economics and Management, Elsevier, vol. 29(3), pages 339-356, November.
    6. Kemp, Alexander G. & Kasim, Sola, 2012. "The Economics of CO2-EOR Cluster Developments in the UK Central North Sea/ Outer Moray Firth," SIRE Discussion Papers 2012-21, Scottish Institute for Research in Economics (SIRE).
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    Cited by:

    1. Pao-Yu Oei and Roman Mendelevitch, 2016. "European Scenarios of CO2 Infrastructure Investment until 2050," The Energy Journal, International Association for Energy Economics, vol. 0(Sustainab).
    2. Massol, Olivier & Tchung-Ming, Stéphane & Banal-Estañol, Albert, 2015. "Joining the CCS club! The economics of CO2 pipeline projects," European Journal of Operational Research, Elsevier, vol. 247(1), pages 259-275.
    3. Roman Mendelevitch & Pao-Yu Oei, 2015. "The Impact of Policy Measures on Future Power Generation Portfolio and Infrastructure: A Combined Electricity and CCTS Investment and Dispatch Model (ELCO)," Discussion Papers of DIW Berlin 1521, DIW Berlin, German Institute for Economic Research.

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    More about this item

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • L71 - Industrial Organization - - Industry Studies: Primary Products and Construction - - - Mining, Extraction, and Refining: Hydrocarbon Fuels
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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