Log in

Study of Drillability Evaluation in Deep Formations Using the Kriging Interpolation Method

  • Published:
Chemistry and Technology of Fuels and Oils Aims and scope

During development of production processes in deep formations by means of wells placed in lower productive intervals, it is specifically such formations that have gradually become the major challenge in oil production. Due to the considerable depths and the combination of complex properties of the formations, in order for formulate a rational development program for the formations we need comprehensive understanding of their drillability and distribution in the specified region. In this paper; in order to provide such geological information, based on laboratory core experiments we have established the drillability of sections of the formation in a specified region by interpolation of support vectors by the kriging method.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Yi Zhang, Yinglau Mai, Tengfei Sun, and Zhaohui Cao, “Practical application of a component analysis and cluster analysis to evaluate the parameters of layered heterogeneous formations in Dagang Oil Field,” Chemistry and Technology of Fuels and Oils, 6, No. 586, 48-51 (2014).

    Google Scholar 

  2. Wangwen Wu, Yongguo Yang, and Youkuo Chen, “Kriging interpolation method optimized by LSSVM and its application in predicting coal thickness,” Coal Technology, 34. No. 5, 89-91 (2015).

    Google Scholar 

  3. M. Cellura, G Cirrincione, A. Marvuglia, and A. Miraoui, “Wind speed spatial estimation for energy planning in Sicily: A neural kriging application,” Renewable Energy, 33, 1251-1266 (2008).

    Article  Google Scholar 

  4. V. N. Vapnik, Statistical Learning Theory, Wiley, New York (1998).

    Google Scholar 

  5. Minghe Yang, Yinghu Zhai, and Yuanpu Ma, “Creating formation drillability plane based on finite element method,” Petroleum Drilling Techniques, 35, No. 5, 59-61 (2007).

    Google Scholar 

  6. Minghe Yang, Yinghu Zhai, and Hongnan **a, “Application of grey correlation analysis on development and adjustment in Gaotaizi Oil Field,” Petroleum Geology and Engineering, 22, No. 3, 83-84 (2008).

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Additional information

Translated from Khimiya i Tekhnologiya Topliv i Masel, No. 3, pp. 83 — 84, May — June, 2018.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, Y., Duan, M., Kong, X. et al. Study of Drillability Evaluation in Deep Formations Using the Kriging Interpolation Method. Chem Technol Fuels Oils 54, 382–385 (2018). https://doi.org/10.1007/s10553-018-0936-5

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10553-018-0936-5

Key words

Navigation