Investigation of Pore-Scale CaCO3 Distributions and Their Effects on Stiffness and Permeability of Sands Treated by Microbially Induced Carbonate Precipitation (MICP)

Our paper on pore-scale distributions of CaCO3 during microbially-induced carbonate precipitation and their effects on sand permeability and stiffness has been accepted for publication in Soils and Foundations.

Citation

Lin, H., Suleiman, M.T. and Brown, D.G. 2020 (In Press). “Investigation of Pore-Scale CaCO3 Distributions and Their Effects on Stiffness and Permeability of Sands Treated by Microbially Induced Carbonate Precipitation (MICP).” Soils and Foundations.

Abstract

Physical properties of MICP-treated sands are controlled by CaCO3 distributions in pore space, which remain relatively unexplored. CaCO3 can deposit at the particles’ contact area (contact-cementing), coat sand particles (grain-coating), or create a cementation bridge between soil grains (matrix-supporting). The objectives of this paper are to determine the dominant CaCO3 distributions in pore space and investigate the effects of CaCO3 distributions on the small-strain stiffness (measured by S-and P-wave velocities) and permeability of MICP-treated sands. To achieve these objectives, cemented-sand and uncemented-sand models combined with three ideal CaCO3 distributions (contact-cementing, grain-coating, and matrix-supporting) were used to estimate the S-and P-wave velocities. In order to determine the dominant CaCO3 distributions in pore space, the calculated values from the models were then compared with experimental data. It was concluded that the dominant CaCO3 distributions were a combination of grain-coating and matrix-supporting. The effects of CaCO3 distributions at pore space on the variation of permeability were estimated using Kozeny-Carman and Panda-Lake models with three pore-scale cement distributions (pore-lining, pore-filling, and pore-bridging). The comparison between laboratory-measured and calculated permeability from the pore-filling Panda-Lake model for seven types of sands demonstrated a relatively good match with a maximum difference of one order of magnitude. The comparison suggests the pore-filling Panda-Lake model can be used for estimating the permeability of the MICP-treated sands.

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