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Nanoparticle plugging prediction of shale pores: A numerical and experimental study

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  • Yang, Xianyu
  • Cai, Jihua
  • Jiang, Guosheng
  • Xie, Jingyu
  • Shi, Yanping
  • Chen, Shuya
  • Yue, Ye
  • Yu, Lang
  • He, Yichao
  • Xie, Kunzhi

Abstract

The combination of energy modeling and nanotechnology has been receiving increasing attention. Researchers have discovered that nanoparticles can plug shale pores. However, currently, information about the blocking effect of nanoparticles on shale pores is largely limited to physical experimental data. The migration, dynamic accumulation, and blocking mechanism of nanoparticles in a drilling fluid after intrusion into shale pores remain unclear. In this study, a CFD-DEM model was used to dynamically predict the quantitative relationship between nanoparticle parameters, fluid properties, and the shale pore plugging efficiency. To ensure rationality, UDF codes were written to correlate the standard drag curve. The results indicate that increasing the viscosity to 5 mPa·s is a highly effective method for improving the plugging efficiency at 1 wt% particle concentration. In addition, the effects of particle size, concentration, and fluid viscosity on the plugging effect are observed to be positively correlated. The plugging efficiency of a solution with 5 mPa·s viscosity was improved by 8.6%, 18.81%, and 18.77% compared with that of a solution with 1 mPa·s viscosity at particle sizes of 1/5, 1/3, and 1/2, respectively. Moreover, a pore roughness of 3% and a fluid viscosity of 5 mPa·s were determined to be the thresholds for improving the particle plugging efficiency. In addition, the simulation results were validated based on the results of a pressure transfer experiment. The findings of this study can serve as a reference for future research on nanoscale pore plugging with viscous flow.

Suggested Citation

  • Yang, Xianyu & Cai, Jihua & Jiang, Guosheng & Xie, Jingyu & Shi, Yanping & Chen, Shuya & Yue, Ye & Yu, Lang & He, Yichao & Xie, Kunzhi, 2020. "Nanoparticle plugging prediction of shale pores: A numerical and experimental study," Energy, Elsevier, vol. 208(C).
    • Handle: RePEc:eee:energy:v:208:y:2020:i:c:s0360544220314444
    DOI: 10.1016/j.energy.2020.118337
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