Applied Mathematics and Mechanics (English Edition) ›› 2020, Vol. 41 ›› Issue (3): 491-506.doi: https://doi.org/10.1007/s10483-020-2583-9

• Articles • Previous Articles     Next Articles

Stochastic and upscaled analytical modeling of fines migration in porous media induced by low-salinity water injection

Yulong YANG1, Weifeng YUAN1, Jirui HOU1, Zhenjiang YOU2, Jun LI3, Yang LIU3   

  1. 1. Unconventional Petroleum Research Institute, China University of Petroleum, Beijing 102249, China;
    2. School of Chemical Engineering, The University of Queensland, Brisbane QLD 4072, Australia;
    3. College of Petroleum Engineering, China University of Petroleum, Beijing 102249, China
  • Received:2019-09-09 Revised:2019-11-27 Online:2020-03-01 Published:2020-02-17
  • Contact: Zhenjiang YOU E-mail:zhenjiang.you@gmail.com
  • Supported by:
    Project supported by the National Natural Science Foundation of China (Nos. 51804316, 51734010, and U1762211), the National Science and Technology Major Project of China (No. 2017ZX05009), and the Science Foundation of China University of Petroleum, Beijing (No. 2462017YJRC037)

Abstract: Fines migration induced by injection of low-salinity water (LSW) into porous media can lead to severe pore plugging and consequent permeability reduction. The deepbed filtration (DBF) theory is used to model the aforementioned phenomenon, which allows us to predict the effluent concentration history and the distribution profile of entrapped particles. However, the previous models fail to consider the movement of the waterflood front. In this study, we derive a stochastic model for fines migration during LSW flooding, in which the Rankine-Hugoniot condition is used to calculate the concentration of detached particles behind and ahead of the moving water front. A downscaling procedure is developed to determine the evolution of pore-size distribution from the exact solution of a large-scale equation system. To validate the proposed model, the obtained exact solutions are used to treat the laboratory data of LSW flooding in artificial soil-packed columns. The tuning results show that the proposed model yields a considerably higher value of the coefficient of determination, compared with the previous models, indicating that the new model can successfully capture the effect of the moving water front on fines migration and precisely match the effluent history of the detached particles.

Key words: low-salinity water (LSW) flooding, fines migration, stochastic model, downscaling, porous media, waterflooding front, exact solution

2010 MSC Number: 

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