Direct geoelectrical evidence of mass transfer at the laboratory scale

Abstract

[1] Previous field-scale experimental data and numerical modeling suggest that the dual-domain mass transfer (DDMT) of electrolytic tracers has an observable geoelectrical signature. Here we present controlled laboratory experiments confirming the electrical signature of DDMT and demonstrate the use of time-lapse electrical measurements in conjunction with concentration measurements to estimate the parameters controlling DDMT, i.e., the mobile and immobile porosity and rate at which solute exchanges between mobile and immobile domains. We conducted column tracer tests on unconsolidated quartz sand and a material with a high secondary porosity: the zeolite clinoptilolite. During NaCl tracer tests we collected nearly colocated bulk direct-current electrical conductivity ( b ) and fluid conductivity ( f ) measurements. Our results for the zeolite show (1) extensive tailing and (2) a hysteretic relation between f and b , thus providing evidence of mass transfer not observed within the quartz sand. To identify bestfit parameters and evaluate parameter sensitivity, we performed over 2700 simulations of f , varying the immobile and mobile domain and mass transfer rate. We emphasized the fit to late-time tailing by minimizing the Box-Cox power transformed root-mean square error between the observed and simulated f . Low-field proton nuclear magnetic resonance (NMR) measurements provide an independent quantification of the volumes of the mobile and immobile domains. The best-fit parameters based on f match the NMR measurements of the immobile and mobile domain porosities and provide the first direct electrical evidence for DDMT. Our results underscore the potential of using electrical measurements for DDMT parameter inference.

Pore network modeling of the electrical signature of solute transport in dual‐domain media

“…In the PNM, we represent intergranular and intragranular porosity as different classes of pores, class 1 and 2, respectively. Whereas each intergranular connection occurs through a single bond between adjacent pores, intragranular connections are divided between a number ( N B ) of small bonds, consistent with CT scan visualizations of zeolite grains [ Swanson et al ., , ]. Grains are represented as regions of class 2 pores with diameters based on the α SRMT from Briggs et al [] and the formula for the diffusive length scale of a spherical grain, 0.5 cm [ Haggerty et al ., ].…”

The Dual‐Domain Porosity Apparatus: Characterizing Dual Porosity at the Sediment/Water Interface

“…These experiments are only indirectly sensitive to less-mobile porosity dynamics as fluid sampling preferentially pulls from the mobile-porosity domain. Geoelectrical measurements that are directly sensitive to conductive tracer exchange with less-mobile porosity have been demonstrated in laboratory (Swanson et al 2012) and field (Briggs et al 2013b) experiments. Geoelectrical measurements that are directly sensitive to conductive tracer exchange with less-mobile porosity have been demonstrated in laboratory (Swanson et al 2012) and field (Briggs et al 2013b) experiments.…”

Simultaneous estimation of local-scale and flow path-scale dual-domain mass transfer parameters using geoelectrical monitoring

“…Recent work at pilot field [ Singha et al ., ] and laboratory scales [ Swanson et al ., ] has demonstrated that anomalous solute transport has an observable geoelectrical signature that, in principle, can be exploited to directly determine mass transfer parameters (i.e., rate coefficient, mobile porosity, and immobile porosity) [ Day‐Lewis and Singha , ]. Whereas, fluid sampling preferentially draws from the mobile domain, electrical measurements are sensitive to solute tracer in both mobile and immobile domains.…”

“…Swanson et al . [] recently inferred mass transfer parameters using parametric sweeps for controlled homogeneous column experiments with independently evaluated immobile porosity. Forward simulations of transport were run for several thousand combinations of mass transfer parameters, and the fit to experimental data was evaluated.…”

“…Forward simulations of transport were run for several thousand combinations of mass transfer parameters, and the fit to experimental data was evaluated. The previous work detailed above relied on either (1) analysis based on temporal moments [ Day‐Lewis and Singha , ], which are subject to error in the presence of measurement noise or (2) parametric sweeps [ Swanson et al ., ], which provide limited insight into parameter sensitivity or information content.…”