Frontiers in Energy Research (May 2022)

Prediction of Drag Reduction in Slickwater Fracturing by Two General Models

  • Pengfei Chen,
  • Honggang Chang,
  • Yongqiang Fu,
  • Yongfan Tang,
  • Xuesong Huang,
  • Weichu Yu

DOI
https://doi.org/10.3389/fenrg.2022.905187
Journal volume & issue
Vol. 10

Abstract

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Drag reduction (DR) is critical to the success of hydraulic fracturing operations with slickwater, and it is a challenge to accurately predict DR due to the problem of high injection rates. Although a practical pipe diameter model is frequently used to predict the field DR based on laboratory experimental data, there exist many limitations. This study, on account of dynamic similarity, shows two novel general models for the prediction of field DR, and such two models can give reliable predictions when the laboratory and field Reynolds numbers (Re) are the same. For general model 1, the DR can be predicted by using the laboratory volumetric flow rate, pipe diameter and pressure drop, and the field volumetric flow rate, with a deviation ranging from −10 to 10%. For general model 2, it is simpler than general model 1, and the DR can be predicted by using the laboratory pipe diameter and the field volumetric flow rate, with a deviation ranging from −6 to 6%. The two novel general models can be used for more scenarios than the existing reported ones.

Keywords