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Application of Adaptive Channel Facies Modeling to Geo-Steering of Horizontal Wells

  • Wensheng Wang
  • Ji Zhang
  • Weifeng Sun
  • Yuqi Bai
Conference paper
Part of the Springer Series in Geomechanics and Geoengineering book series (SSGG)

Abstract

In view of the 2D section geo-steering technology based on the start well and the end well, the relationship between adjacent wells cannot be fully reflected, and the reservoir prediction effect is poor. Using data measurement of 10 modern braided rivers, architecture dissection of three encryption areas, and analysis of 50 horizontal well data, this paper establishes the single-layer microfacies geological database of braided river reservoir. As a constraint, taking advantage of the adaptive channel facies modeling method by the control of the body curve and 20 × 20 × 0.2 m fine grid design, the 3D facies model of multi-period stacked channels is set up, and then, after the analysis and classification of the quality-controlled models, probability prediction models is built according to different geological conditions, in order to guide horizontal well geo-steering. The results show that this method achieves better effect compared with the traditional methods, the success rate reaches 90.9%, the sandstone drilling rate is increased by 8% points, and the test yield and the production capacity are improved significantly. This method provides strong technical support for the highly economic and effective development of strong heterogeneity and tight sandstone gas reservoirs.

Keywords

Sulige gas field Tight sandstone gas reservoir Geological database Horizontal wells geo-steering Adaptive channel 

Notes

Acknowledgements

This chapter was supported by the following: (1) National Science and Technology major projects “The development demonstration project of a large low permeability lithostratigraphic hydrocarbon reservoirs in Ordos Basin” (No. 2016ZX05050).

(2) PetroChina Company Limited Science and Technology major projects “Study on stable production and enhanced oil recovery technology in Changqing gas field” (No. 2016E-0509).

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Wensheng Wang
    • 1
    • 2
  • Ji Zhang
    • 1
    • 2
  • Weifeng Sun
    • 1
    • 2
  • Yuqi Bai
    • 1
    • 2
  1. 1.Sulige Gasfield Research Center of Changqing Oilfield Company, PetroChinaXi’anChina
  2. 2.State Engineering Laboratory of Low Permeability Oil & Gas Field Exploration and DevelopmentXi’anChina

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