IDEAS home Printed from https://ideas.repec.org/a/eee/enepol/v36y2008i11p4149-4153.html
   My bibliography  Save this article

China's oil reserve forecast and analysis based on peak oil models

Author

Listed:
  • Feng, Lianyong
  • Li, Junchen
  • Pang, Xiongqi

Abstract

In order to forecast future oil production it is necessary to know the size of the reserves and use models. In this article, we use the typical Peak Oil models, the Hu-Chen-Zhang model usually called HCZ model and the Hubbert model, which have been used commonly for forecasting in China and the world, to forecast China's oil Ultimate Recovery (URR). The former appears to give more realistic results based on an URR for China of 15.64 billion tons. The study leads to some suggestions for new policies to meet the unfolding energy situation.

Suggested Citation

  • Feng, Lianyong & Li, Junchen & Pang, Xiongqi, 2008. "China's oil reserve forecast and analysis based on peak oil models," Energy Policy, Elsevier, vol. 36(11), pages 4149-4153, November.
    • Handle: RePEc:eee:enepol:v:36:y:2008:i:11:p:4149-4153
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301-4215(08)00394-7
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ma, Linwei & Liu, Pei & Fu, Feng & Li, Zheng & Ni, Weidou, 2011. "Integrated energy strategy for the sustainable development of China," Energy, Elsevier, vol. 36(2), pages 1143-1154.
    2. Fang, Jianchun & Lau, Chi Keung Marco & Lu, Zhou & Wu, Wanshan, 2018. "Estimating Peak uranium production in China – Based on a Stella model," Energy Policy, Elsevier, vol. 120(C), pages 250-258.
    3. Wang, Guoying & Liu, Shaowei & Yang, Dong & Fu, Mengxiong, 2022. "Numerical study on the in-situ pyrolysis process of steeply dipping oil shale deposits by injecting superheated water steam: A case study on Jimsar oil shale in Xinjiang, China," Energy, Elsevier, vol. 239(PC).
    4. de Castro, Carlos & Miguel, Luis Javier & Mediavilla, Margarita, 2009. "The role of non conventional oil in the attenuation of peak oil," Energy Policy, Elsevier, vol. 37(5), pages 1825-1833, May.
    5. Northey, S. & Mohr, S. & Mudd, G.M. & Weng, Z. & Giurco, D., 2014. "Modelling future copper ore grade decline based on a detailed assessment of copper resources and mining," Resources, Conservation & Recycling, Elsevier, vol. 83(C), pages 190-201.
    6. Wang, Jianliang & Feng, Lianyong & Steve, Mohr & Tang, Xu & Gail, Tverberg E. & Mikael, Höök, 2015. "China's unconventional oil: A review of its resources and outlook for long-term production," Energy, Elsevier, vol. 82(C), pages 31-42.
    7. Xibo Wang & Mingtao Yao & Jiashuo Li & Kexue Zhang & He Zhu & Minsi Zheng, 2017. "China’s Rare Earths Production Forecasting and Sustainable Development Policy Implications," Sustainability, MDPI, vol. 9(6), pages 1-14, June.
    8. Vikström, Hanna & Davidsson, Simon & Höök, Mikael, 2013. "Lithium availability and future production outlooks," Applied Energy, Elsevier, vol. 110(C), pages 252-266.
    9. Wang, Xibo & Lei, Yalin & Ge, Jianping & Wu, Sanmang, 2015. "Production forecast of China׳s rare earths based on the Generalized Weng model and policy recommendations," Resources Policy, Elsevier, vol. 43(C), pages 11-18.
    10. Ma, Linwei & Fu, Feng & Li, Zheng & Liu, Pei, 2012. "Oil development in China: Current status and future trends," Energy Policy, Elsevier, vol. 45(C), pages 43-53.
    11. Wang, Ke & Feng, Lianyong & Wang, Jianliang & Xiong, Yi & Tverberg, Gail E., 2016. "An oil production forecast for China considering economic limits," Energy, Elsevier, vol. 113(C), pages 586-596.
    12. Juan Jin & Jiandong Liu & Weidong Jiang & Wei Cheng & Xiaowen Zhang, 2022. "Evolution of the Anisotropic Thermal Conductivity of Oil Shale with Temperature and Its Relationship with Anisotropic Pore Structure Evolution," Energies, MDPI, vol. 15(21), pages 1-16, October.
    13. Bo Xu & Lianyong Feng & William X. Wei & Yan Hu & Jianliang Wang, 2014. "A Preliminary Forecast of the Production Status of China’s Daqing Oil field from the Perspective of EROI," Sustainability, MDPI, vol. 6(11), pages 1-21, November.
    14. Ming Zhang & Qing Xia & Wenwen Wang & Min Zhou, 2014. "Study on temporal and spatial evolution of China’s oil supply and consumption," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 72(2), pages 809-825, June.
    15. Zhao, Chunfu & Chen, Bin, 2014. "China’s oil security from the supply chain perspective: A review," Applied Energy, Elsevier, vol. 136(C), pages 269-279.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:enepol:v:36:y:2008:i:11:p:4149-4153. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/enpol .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.