SIP data reveals complexity of biogeochemical transformations during subsurface remediation
Sources: Susan Hubbard & Dan Hawkes
Recent analysis and interpretation of field-scale SIP data are beginning to reveal the complexity of biogeochemical transformations that occur during remediation in heterogeneous subsurface environments. ESD’s Michael Commer and his geophysics imaging team (Commer et al. 2011) have developed a three-dimensional SIP inversion algorithm based on the nonlinear-conjugate gradient method and finite-difference (FD) forward modeling. The hierarchical parallel architecture of the algorithm, in addition to optimal FD mesh design, allows for an economic use of today’s massively parallel computing capabilities to process large SIP data sets. The developed methodology was applied to surface SIP datasets collected over time during a uranium biostimulation experiment conducted at the Rifle, Colorado, Integrated Field-Scale Research Challenge (IFRC) site (Figure 2). Following closely on this research, Flores-Orozco and his team (in press, JGR, 2011) demonstrated the use of the Rifle, Colorado, time-lapse SIP datasets to infer biogeochemical changes accompanying stimulation of indigenous aquifer microorganisms during and after a prolonged period (100+ days) of acetate injection. The imaging results revealed spatiotemporal changes in the electrical phase, which correlated with increases in Fe(II) and precipitation of metal sulfides (e.g., FeS) shortly after the iterative stimulation of iron- and sulfate-reducing bacteria (Figure 3). The largest electrical-phase anomalies were observed hundreds of days after halting acetate injection, in conjunction with accumulation of Fe(II) in the presence of residual FeS minerals. Such findings reflect the preservation of geochemically reduced conditions within the aquifer—a pre-requisite for the prolonged stability of immobilized uranium following biostimulation activities—and indicate the potential for using time-lapse SIP datasets to provide detailed information about spatiotemporal biogeochemical changes, information that can be used to assess remediation efficacy.
Figure 2: 3D inversion of surface spectral induced polarization (Commer et al., 2011), which was applied to time-lapse data collected before, during, and after a bioremediation experiment performed at the uranium-contaminated Rifle, CO IFRC site.
Figure 3: Schematic representation of the polarization mechanisms that are interpreted to govern the observed phase response during the two years of bioremediation monitoring using surface spectral- induced-polarization data (Figure 2) collected at the Rifle, CO IFRC site. The solid black structures represent metallic minerals (such as FeS), the gray bodies represent other polarizable minerals (such as calcites and clays) and the solid circles represent electroactive ions (such as FeII) present in groundwater. Here, three possible scenarios are considered: (a) Electrode polarization as the dominating polarization process, taking place on the surface of precipitated metallic minerals and characterized by high polarization values if a critical concentration (represented by the dashed line) of electroactive ions is present in the groundwater. A modest electrical phase response will be associated with membrane polarization when (b) metallic minerals have been precipitated but concentration of electroactive ions are lower than the critical concentration (i.e., periods of dominating sulfate reduction in our experiments); and (c) in the presence of a negligible amount of metallic minerals.