Induced polarization can be used to estimate surface conductivity by assuming a universal linear relationship between the surface and quadrature conductivities of porous media. However, this assumption has not yet been justified for conditions covering a broad range of fluid conductivities. We have performed complex conductivity measurements on Portland sandstone, an illite- and kaolinite-rich sandstone, at 13 different water salinities (NaCl) over the frequency range of 0.1 Hz to 45 kHz. The conductivity of the pore water [Formula: see text] affected the complex surface conductivity mainly by changing the tortuosity of the conduction paths in the pore network from high to low salinities. As the fluid conductivity decreases, the magnitude of the surface conductivity and quadrature conductivity was observed to decrease. At relatively high salinities ([Formula: see text]), the ratio between the surface conductivity and quadrature conductivity was roughly constant. At low salinities ([Formula: see text]), the ratio decreased slightly with the decrease of the salinity. A Stern layer polarization model was combined with the differential effective medium (DEM) theory to describe this behavior. The tortuosity entering the complex surface conductivity was salinity dependent following the prediction of the DEM theory. At high salinity, it reached the value of the bulk tortuosity of the pore space given by the product of the intrinsic formation factor and the connected porosity. The relaxation time distributions were also obtained at different salinities by inverting the measured spectra using a Warburg decomposition. The mode of the relaxation time probability distribution found a small but clear dependence on the salinity. This salinity dependence can be explained by considering the ions exchange between Stern and diffuse layers during polarization of the former. The pore-size distribution obtained from the distribution of the relaxation time agreed with the pore-size distribution from nuclear magnetic resonance measurements.
In this study, we focus on the electrical tortuosity‐based permeability model k = reff2/8F (reff is an effective pore size, and F is the formation factor) and analyze its applicability to rocks experiencing mineral precipitation and dissolution. Two limiting cases of advection‐dominated water‐rock reactions are simulated, that is, the reaction‐limited and transport‐limited cases. At the pore scale, the two precipitation/dissolution patterns are simulated with a geometrical model and a phenomenological model. The fluid and electric flows in the rocks are simulated by directly solving the linear Stokes equation and Laplace equation on the representative elementary volume of the samples. The numerical results show that evolutions of k and F differ significantly in the two limiting cases. In general, the reaction‐limited precipitation/dissolution would result in a smooth variation of k and F, which can be roughly modeled with a power function of porosity ϕ with a constant exponent. In contrast, the transport‐limited precipitation/dissolution mostly occurs near the pore throats where the fluid velocity is high. This induces a sharp change in k and F despite a minor variation in ϕ. The commonly used power laws with constant exponents are not able to describe such variations. The results also reveal that the electrical tortuosity‐based permeability prediction generally works well for rocks experiencing precipitation/dissolution if reff can be appropriately estimated, for example, with the electrical field normalized pore size Λ. The associated prediction errors are mainly due to the use of electrical tortuosity, which might be considerably larger than the true hydraulic tortuosity.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.