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Modeling the time and cost to drill an offshore well

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  • Kaiser, Mark J.

Abstract

The objective in drilling a hydrocarbon well is to make hole as quickly as possible subject to the technological, operational, quality, and safety constraints associated with the process. These objectives are frequently conflicting and depend on factors that are subject to significant private and market uncertainty. There is no way to identify all of the relevant characteristics of drilling operations, but through use of statistical analysis and empirical modeling, it is possible to develop relations that characterize and benchmark drilling performance under a suitable set of assumptions. The purpose of this paper is to develop the conceptual framework to model the time and cost to drill an offshore well and to illustrate the methodology on a test set of wells in the Gulf of Mexico. The physical characteristics of the wellbore and operational aspects of drilling, including variables such as the drilled interval, horizontal displacement, aspect ratio, number of casing strings, and mud weight, serve as the primary descriptive factors in the functional relations constructed.

Suggested Citation

  • Kaiser, Mark J., 2009. "Modeling the time and cost to drill an offshore well," Energy, Elsevier, vol. 34(9), pages 1097-1112.
    • Handle: RePEc:eee:energy:v:34:y:2009:i:9:p:1097-1112
    DOI: 10.1016/j.energy.2009.02.017
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    Citations

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    Cited by:

    1. Zhang, Zheng & Xiong, Youming & Gao, Yun & Liu, Liming & Wang, Menghao & Peng, Geng, 2018. "Wellbore temperature distribution during circulation stage when well-kick occurs in a continuous formation from the bottom-hole," Energy, Elsevier, vol. 164(C), pages 964-977.
    2. Navarre, Jeremy T. & Frazier, Jeremy A., 2022. "Econometric analysis of factors influencing commercial helicopter operators’ stock returns in the gulf of Mexico," Journal of Air Transport Management, Elsevier, vol. 99(C).
    3. Kaiser, Mark J., 2012. "Profitability assessment of Haynesville shale gas wells," Energy, Elsevier, vol. 38(1), pages 315-330.
    4. Osmundsen, Petter & Roll, Kristin Helen & Tveterås, Ragnar, 2010. "Faster Drilling with Expercience?," UiS Working Papers in Economics and Finance 2010/7, University of Stavanger.
    5. Liao, Youqiang & Sun, Xiaohui & Sun, Baojiang & Wang, Zhiyuan & Wang, Jintang & Wang, Xuerui, 2021. "Geothermal exploitation and electricity generation from multibranch U-shaped well–enhanced geothermal system," Renewable Energy, Elsevier, vol. 163(C), pages 2178-2189.
    6. Yang, Xianyu & Chen, Shuya & Shi, Yanping & Feng, Ruimin & Cai, Jihua & Jiang, Guosheng, 2019. "CFD and DEM modelling of particles plugging in shale pores," Energy, Elsevier, vol. 174(C), pages 1026-1038.
    7. Liu, Bing & Huang, Hao & Deng, Qiao, 2022. "On optimal condition based task termination policy for phased task systems," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    8. Guoshu Huang & Huolin Ma & Xiangyun Hu & Jianchao Cai & Jiabin Li & Hongqing Luo & Heping Pan, 2019. "A Coupled Model of Two-Phase Fluid Flow and Heat Transfer to Transient Temperature Distribution and Seepage Characteristics for Water-Flooding Production Well with Multiple Pay Zones," Energies, MDPI, vol. 12(10), pages 1-33, May.
    9. Osmundsen, Petter & Roll, Kristin Helen & Tveteras, Ragnar, 2012. "Drilling speed—the relevance of experience," Energy Economics, Elsevier, vol. 34(3), pages 786-794.
    10. Xu, Chengyuan & Yan, Xiaopeng & Kang, Yili & You, Lijun & You, Zhenjiang & Zhang, Hao & Zhang, Jingyi, 2019. "Friction coefficient: A significant parameter for lost circulation control and material selection in naturally fractured reservoir," Energy, Elsevier, vol. 174(C), pages 1012-1025.
    11. Osmundsen, Petter & Roll, Kristin Helen, 2013. "Concave Drilling Curves," UiS Working Papers in Economics and Finance 2013/1, University of Stavanger.

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