ALBERT

Description: Field-scale lithologic applications of complex conductivity ( $${\sigma }^{*}$$ ) imaging have been hindered by the challenges of (1) acquiring reliable induced polarization (IP) measurements and (2) obtaining reliable $${\sigma }^{*}$$ images from the measurements. We performed a series of 2D time domain resistivity/IP surveys at the Hanford 300 Area (Richland, Washington) where the challenge was to image the spatial distribution of two lithologic units that control the exchange between groundwater and surface water of the Columbia River. Exploiting the equivalence between time domain and frequency domain measurements of polarization, a 2D $${\sigma }^{*}$$ inversion (real conductivity $${\sigma }^{\prime }$$ , imaginary conductivity $${\sigma }^{\prime \prime }$$ , and phase angle $$\phi $$ ) was used to image the spatial distribution of $${\sigma }^{*}$$ across the site. Synthetic studies were carried out to investigate the effects of noise on the resolution of $${\sigma }^{*}$$ images and to add confidence on the interpretation of possible paleochannels observed in the field data sets. The synthetic studies show that, with increasing representative noise levels, degradation of the resolution of lithologic structures in the parameters most controlled by the IP measurements ( $$\phi $$ and $${\sigma }^{\prime \prime }$$ ) is significantly greater than degradation of resolution of $${\sigma }^{\prime }$$ images. However, the acquisition of IP measurements, and the analysis of changes in $${\sigma }^{\prime }$$ and $${\sigma }^{\prime \prime }$$ constrains the lithological interpretation of the geoelectrical data set due to the strong dependency of $${\sigma }^{\prime \prime }$$ on lithological properties. A threshold based on $${\sigma }^{\prime \prime }$$ measurements from cores at the site was used to estimate the elevation of the contact between the two key units, which is consistent with boreholes at the site. Variation in the elevation of this contact provides evidence of a depression in the Hanford-Ringold contact connecting the aquifer and the Columbia River; this depression likely represents a paleochannel regulating flow and transport at the site.

Description: Continuing advancements in subsurface electrical resistivity tomography (ERT) are increasing its capabilities for understanding shallow subsurface properties and processes. The inability of ERT imaging data to resolve unique subsurface structures and the corresponding need to include constraining information remains one of the greatest limitations, yet provides one of the greatest opportunities for further advancing the utility of the method. We propose a new method of incorporating constraining information into an ERT imaging algorithm in the form of discontinuous boundaries, known values, and spatial covariance information. We demonstrated the approach by imaging a uranium-contaminated wellfield at the Hanford Site in southeastern Washington State, USA. We incorporate into the algorithm known boundary information and spatial covariance structures derived from the highly resolved near-borehole regions of a regularized ERT inversion. The resulting inversion provides a solution which fits the ERT data (given the estimated noise level), honors the spatial covariance structure throughout the model, and is consistent with known bulk-conductivity discontinuities. The results are validated with core-scale measurements, indicating a significant improvement in accuracy over the standard regularized inversion and revealing important subsurface structure known to influence flow and transport at the site.

Description: We examined the dependence of imaginary conductivity ( $${\sigma }^{\prime \prime }$$ ) on pore fluid conductivity ( $${\sigma }_{w}$$ ) for an extensive database of 67 samples acquired from twelve independent studies. We compared fitting of functions describing the salinity dependence of $${\sigma }^{\prime \prime }$$ for two models of the electrical double layer (EDL) polarization, both of which predict asymptotic behavior of $${\sigma }^{\prime \prime }$$ at high $${\sigma }_{w}$$ . We define these models as the diffuse layer polarization (DLP) and Stern layer polarization (SLP) models based on the physical description of the salinity dependence of the surface polarization. We also examined the database for evidence of a high salinity decrease in $${\sigma }^{\prime \prime }$$ not predicted by either model. The dependence of $${\sigma }^{\prime \prime }$$ on $${\sigma }_{w}$$ prior to the polarization plateau predicted by both models approximates a simple empirical power law with an average exponent of 0.34. The salinity dependence predicted by the DLP model adequately describes most data sets. A fitting parameter representing the high salinity $${\sigma }^{\prime \prime }$$ asymptote is strongly correlated ( $${R}^{2}=0.822$$ ) with pore normalized specific surface ( $${S}_{\mathrm{por}}$$ ). The SLP model describes well the observations when a recently proposed additive polarization term representing the contribution of the protons is included. In this case, the SLP model provides an excellent fit to the data sets, including a low salinity asymptote (in log-log conductivity space) seen in some samples. Predicted values of the fitting parameters of the SLP model generally are consistent with the values expected based on the theory; the fitting parameter describing the high salinity asymptote of the SLP model is also strongly correlated ( $${R}^{2}=0.890$$ ) with $${S}_{\mathrm{por}}$$ . The SLP and DLP models neglect a high salinity decrease in the polarization that is observed in numerous data sets from independent studies. New data acquired on a sandstone sample demonstrate that this high salinity decrease is likely not attributable to the limited phase accuracy of earlier measurements.