Spatiotemporal Distribution of Precipitates and Mineral Phase Transition During Biomineralization Affect Porosity–Permeability Relationships

Abstract

Enzymatically induced calcium carbonate precipitation is a promising geotechnique with the potential, for example, to seal leakage pathways in the subsurface or to stabilize soils. Precipitation of calcium carbonate in a porous medium reduces the porosity and, consequently, the permeability. With pseudo-2D microfluidic experiments, including pressure monitoring and, for visualization, optical microscopy and X-ray computed tomography, pore-space alterations were reliably related to corresponding hydraulic responses. The study comprises six experiments with two different pore structures, a simple, quasi-1D structure, and a 2D structure. Using a continuous injection strategy with either constant or step-wise reduced flow rates, we identified key mechanisms that significantly influence the relationship between porosity and permeability. In the quasi-1D structure, the location of precipitates is more relevant to the hydraulic response (pressure gradients) than the overall porosity change. In the quasi-2D structure, this is different, because flow can bypass locally clogged regions, thus leading to steadier porosity–permeability relationships. Moreover, in quasi-2D systems, during continuous injection, preferential flow paths can evolve and remain open. Classical porosity–permeability power-law relationships with constant exponents cannot adequately describe this phenomenon. We furthermore observed coexistence and transformation of different polymorphs of calcium carbonate, namely amorphous calcium carbonate, vaterite, and calcite and discuss their influence on the observed development of preferential flow paths. This has so far not been accounted for in the state-of-the-art approaches for porosity–permeability relationships during calcium carbonate precipitation in porous media.

Microfluidic study in a meter-long reactive path reveals how the medium’s structural heterogeneity shapes MICP-induced biocementation

“…Assuming a spherical shape of the crystals 30 , 37 , their equivalent diameter D was defined as the average of their minor and major axes (single or aggregate); thus, their equivalent volume is . The total mass of precipitated CaCO 3 at each sampled position was calculated: where ρ = 2.71 g/cm 3 is the density of calcite and n is the number of detected minerals (which can be both single crystals and crystal aggregates).…”

“…Estimation of the chemical reaction efficiency of MICP. Assuming a spherical shape of the crystals 30,37 , their equivalent diameter D was defined as the average of their minor and major axes (single or aggregate); thus, their equivalent volume is…”

“…Since microfluidics enables only 2D imaging, assumptions had to be made regarding the shape of the crystals (spherical and semispherical) to evaluate the crystal growth in three dimensions. Weinhardt et al 31 , 37 presented an experimental setup for the robust measurement of pressure in PDMS microfluidic channels of quasi 1D and quasi 2D pore structure geometries and few mm length during CaCO 3 precipitation via EICP and observed the influence of the geometry on porosity–permeability relationship. Using X-ray microcomputed tomography (XRCT), which resolves the third dimension of the CaCO 3 precipitates after the end of the EICP treatment, suggested that the spheroidal and frustum shapes can be used to calculate the volume of precipitated CaCO 3 from 2D projections.…”

Comparing methods for permeability computation of porous materials and their limitations

“…We investigate for the following use case a domain in which a chemically induced precipitation process clogs the pore space over time. Experimental data that are available online [16] is used and acquisition and experimental setup is described in [15].…”

Mineral Precipitation and Geometry Alteration in Porous Structures: How to Upscale Variations in Permeability–Porosity Relationship?

“…Essentially, mineral nucleation is a critical factor in controlling the distribution of minerals over time and space. ,,− The interplay between solute transport, nucleation, growth, and porous media structure is intricate. Several experimental and numerical studies have shown that the same amount of porosity reduction due to mineral precipitation might result in different permeability reductions. ,,− ,,,,− Furthermore, arbitrary selection of clogging models in RTMs may lead to considerable errors in predicted permeability for the same amount of porosity loss. , Despite all the mentioned variations and uncertainties, the permeability–porosity evolution during RTM in the continuum scale is usually oversimplified and handled with a single equation with a constant variable. Therefore, a process-based approach is necessary when analyzing permeability–porosity evolution.…”