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The injectivity variation prediction model for water flooding oilfields sustainable development

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  • Yang, Renfeng
  • Zhang, Jinqing
  • Chen, Han
  • Jiang, Ruizhong
  • Sun, Zhe
  • Rui, Zhenhua

Abstract

Waterflooding is the most commonly used oilfields development method, and the injectivity is the most critical factor for determining injectors count. Injectivity is usually based on actual on-field test, but lack of theoretical research. An analytical model was proposed to evaluate the water injectivity and predict the variation law. The decisive factor of the injectivity variation law was revealed through further mathematical analysis, and three mathematical conditions were also analyzed, which determine the injectivity variation characteristic. The results show that water injectivity changes continuously, quite different from the prevailing view. The most important finding from the theoretical analysis was that the injectivity presents three behaviors: 1) Injectivity increasing, 2) Injectivity decreasing and 3) Injectivity that decreasing at first and then increasing (an inflection point exsiting). The reasonability and precision of the analytical model were furtherly verified by the numerical cases study, injectivity test and actual injection practice, and could be used for injectivity forecasting. For different viscosity oil reservoirs, the variation law is different and the engineering design should be different, the development effect and economic benefit would be furtherly improved.

Suggested Citation

  • Yang, Renfeng & Zhang, Jinqing & Chen, Han & Jiang, Ruizhong & Sun, Zhe & Rui, Zhenhua, 2019. "The injectivity variation prediction model for water flooding oilfields sustainable development," Energy, Elsevier, vol. 189(C).
    • Handle: RePEc:eee:energy:v:189:y:2019:i:c:s0360544219320122
    DOI: 10.1016/j.energy.2019.116317
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    2. Libing Fu & Lun Zhao & Song Chen & Anzhu Xu & Jun Ni & Xuanran Li, 2022. "A Prediction Method for Development Indexes of Waterflooding Reservoirs Based on Modified Capacitance–Resistance Models," Energies, MDPI, vol. 15(18), pages 1-16, September.

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