Geophysical imaging has traditionally provided qualitative information about geologic structure; however, there is increasing interest in using petrophysical models to convert tomograms to ...quantitative estimates of hydrogeologic, mechanical, or geochemical parameters of interest (e.g., permeability, porosity, water content, and salinity). Unfortunately, petrophysical estimation based on tomograms is complicated by limited and variable image resolution, which depends on (1) measurement physics (e.g., electrical conduction or electromagnetic wave propagation), (2) parameterization and regularization, (3) measurement error, and (4) spatial variability. We present a framework to predict how core‐scale relations between geophysical properties and hydrologic parameters are altered by the inversion, which produces smoothly varying pixel‐scale estimates. We refer to this loss of information as “correlation loss.” Our approach upscales the core‐scale relation to the pixel scale using the model resolution matrix from the inversion, random field averaging, and spatial statistics of the geophysical property. Synthetic examples evaluate the utility of radar travel time tomography (RTT) and electrical‐resistivity tomography (ERT) for estimating water content. This work provides (1) a framework to assess tomograms for geologic parameter estimation and (2) insights into the different patterns of correlation loss for ERT and RTT. Whereas ERT generally performs better near boreholes, RTT performs better in the interwell region. Application of petrophysical models to the tomograms in our examples would yield misleading estimates of water content. Although the examples presented illustrate the problem of correlation loss in the context of near‐surface geophysical imaging, our results have clear implications for quantitative analysis of tomograms for diverse geoscience applications.
Understanding the subsurface structure and function in the near-surface groundwater system, including fluid flow, geomechanical, and weathering processes, requires accurate predictions of the spatial ...distribution of petrophysical properties, such as rock and fluid (air and water) volumetric fractions. These properties can be predicted from geophysical measurements, such as electrical resistivity tomography and refraction seismic data, by solving a rock physics inverse problem. A Bayesian inversion approach based on a Monte Carlo implementation of the Bayesian update problem is developed to generate multiple realizations of porosity and water saturation conditioned on geophysical data. The model realizations are generated using a geostatistical algorithm and updated according to the ensemble smoother approach, an efficient Bayesian data assimilation technique. The prior distribution includes a spatial correlation function such that the model realizations mimic the geological spatial continuity. The result of the inversion includes a set of realizations of porosity and water saturation, as well as the most likely model and its uncertainty, that are crucial to understand fluid flow, geomechanical, and weathering processes in the critical zone. The proposed approach is validated on two synthetic datasets motivated by the Southern Sierra Critical Zone Observatory and is then applied to data collected on a mountain hillslope near Laramie, Wyoming. The inverted results match the measurements, honor the spatial correlation prior model, and provide geologically realistic petrophysical models of weathered rock at Earth’s surface.
Full text
Available for:
EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
High concentrations of trace metal(loid)s exported from abandoned mine wastes and acid rock drainage pose a risk to the health of aquatic ecosystems. To determine if and when the hyporheic zone ...mediates metal(loid) export, we investigated the relationship between streamflow, groundwater–stream connectivity, and subsurface metal(loid) concentrations in two ~1-km stream reaches within the Bonita Peak Mining District, a US Environmental Protection Agency Superfund site located near Silverton, Colorado, USA. The hyporheic zones of reaches in two streams—Mineral Creek and Cement Creek—were characterized using a combination of salt-tracer injection tests, transient-storage modeling, and geochemical sampling of the shallow streambed (<0.7 m). Based on these data, we present two conceptual models for subsurface metal(loid) behavior in the hyporheic zones, including (1) well-connected systems characterized by strong hyporheic mixing of infiltrating stream water and upwelling groundwater and (2) poorly connected systems delineated by physical barriers that limit hyporheic mixing. The comparatively large hyporheic zone and high hydraulic conductivities of Mineral Creek created a connected stream–groundwater system, where mixing of oxygen-rich stream water and metal-rich groundwater facilitated the precipitation of metal colloids in the shallow subsurface. In Cement Creek, the precipitation of iron oxides at depth (~0.4 m) created a low-hydraulic-conductivity barrier between surface water and groundwater. Cemented iron oxides were an important regulator of metal(loid) concentrations in this poorly connected stream–groundwater system due to the formation of strong redox gradients induced by a relatively small hyporheic zone and high fluid residence times. A comparison of conceptual models to stream concentration–discharge relationships exhibited a clear link between geochemical processes occurring within the hyporheic zone of the well-connected system and export of particulate Al, Cu, Fe, and Mn, while the poorly connected system did not have a notable influence on metal concentration–discharge trends. Mineral Creek is an example of a hyporheic system that serves as a natural dissolved metal(loid) sink, whereas poorly connected systems such as Cement Creek may require a combination of subsurface remediation of sediments and mitigation of upstream, iron-rich mine drainages to reduce metal export.
Failure events in dams can be associated with processes in the dam body and in the foundation of the structure. If they are properly identified in early stages, corrective actions can take place, ...leading to a reduction in the risk of collapse and/or rupture of the dam. Most studies on dams are carried out on the body of the dam; however, problems associated with the foundation of the structure can also lead to loss of stability and subsequent ruptures. This study presents an analysis of the advantages and limitations of the use of seismic refraction in hydrogeological studies of fractured aquifers under pressure from large loads, specifically a dam in this case. Seismic refraction data were collected on an outcrop of fractured rock near a uranium storage dam foundation in southeastern Brazil. The results and interpretations were supported by a structural analysis performed through manual strike measurements collected with a Clark compass and an uncrewed aerial vehicle digital photogrammetry survey in an outcrop. The digital photogrammetric survey mapped the spatial distribution and orientation of the geological structures of the rock mass. Although the structural measurements performed through digital photogrammetry presented greater variability than the measurements collected from the compass, the maximum density of the fracture measurements obtained from both methods were similar and were corroborated by the regional and local fracture patterning. The integration of seismic refraction data with geotechnical and geological investigations allowed us to identify the positioning of structural lineaments in the rock mass and zones with a higher degree of rock alteration. The identification of highly fractured zones in the rock mass from such non-invasive investigations could be used to assist in decision making for structural reinforcements in the foundation of the dam to avoid the loss of stability at the foot of the dam from possible leaks or water flows from the reservoir.
Internal water storage within trees can be a critical reservoir that helps trees overcome both short- and long-duration environmental stresses. We monitored changes in internal tree water storage in ...a ponderosa pine on daily and seasonal scales using moisture probes, a dendrometer, and time-lapse electrical resistivity imaging (ERI). These data were used to investigate how patterns of in-tree water storage are affected by changes in sapflow rates, soil moisture, and meteorologic factors such as vapor pressure deficit. Measurements of xylem fluid electrical conductivity were constant in the early growing season while inverted sapwood electrical conductivity steadily increased, suggesting that increases in sapwood electrical conductivity did not result from an increase in xylem fluid electrical conductivity. Seasonal increases in stem electrical conductivity corresponded with seasonal increases in trunk diameter, suggesting that increased electrical conductivity may result from new growth. On the daily scale, changes in inverted sapwood electrical conductivity correspond to changes in sapwood moisture. Wavelet analyses indicated that lag times between inverted electrical conductivity and sapflow increased after storm events, suggesting that as soils wetted, reliance on internal water storage decreased, as did the time required to refill daily deficits in internal water storage. We found short time lags between sapflow and inverted electrical conductivity with dry conditions, when ponderosa pine are known to reduce stomatal conductance to avoid xylem cavitation. A decrease in diel amplitudes of inverted sapwood electrical conductivity during dry periods suggest that the ponderosa pine relied on internal water storage to supplement transpiration demands, but as drought conditions progressed, tree water storage contributions to transpiration decreased. Time-lapse ERI- and wavelet-analysis results highlight the important role internal tree water storage plays in supporting transpiration throughout a day and during periods of declining subsurface moisture.
We collected and analyzed Br- breakthrough curve (BTC) data to identify the parameters controlling transport from a series of soil cores and a field-scale tracer test at the Shale Hills Critical Zone ...Observatory (SH-CZO) in central Pennsylvania. The soil cores were retrieved from a continuous hole that extended through the soil profile to quantify also how solute transport behavior changes with depth and weathering. Additionally, we performed a field-scale doublet tracer test to determine transport behavior in the weathered shale bedrock. Hydraulic conductivity and porosity were as low as 10-15 m s-1 and 0.035, respectively, in the shale bedrock and upward of 10-5 m s-1 and 0.45, respectively, in the shallow soils. Bromide BTCs demonstrated significant tailing in soil cores and field tracer experiments, which does not fit classical advection-dispersion processes. To quantify the behavior, numerical simulation of solute transport was performed with both a mobile-immobile (MIM) model and a continuous-time random walk (CTRW) approach. One-dimensional MIM modeling results yielded low mass transfer rates (<1 d-1) coupled with large immobile domains (immobile/mobile porosity ratio of 1.5-2). The MIM modeling results also suggested that immobile porosity was a combination of soil texture, fractures, and porosity development on shale fragments. One-dimensional CTRW results yielded a parameter set indicative of a transport regime that is consistently non-Fickian within the soil profile and bedrock. These modeling results confirm the important role of preferential flow paths, fractures, and mass transfer between more- and less-mobile fluid domains and advance the need to incorporate a continuum of mass transfer rates to more accurately quantify transport behavior within the SH-CZO.
Full text
Available for:
FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Quantifying the spatial configuration of hydraulic conductivity (K) in heterogeneous geological environments is essential for accurate predictions of contaminant transport, but is difficult because ...of the inherent limitations in resolution and coverage associated with traditional hydrological measurements. To address this issue, we consider crosshole and surface‐based electrical resistivity geophysical measurements, collected in time during a saline tracer experiment. We use a Bayesian Markov‐chain‐Monte‐Carlo (McMC) methodology to jointly invert the dynamic resistivity data, together with borehole tracer concentration data, to generate multiple posterior realizations of K that are consistent with all available information. We do this within a coupled inversion framework, whereby the geophysical and hydrological forward models are linked through an uncertain relationship between electrical resistivity and concentration. To minimize computational expense, a facies‐based subsurface parameterization is developed. The Bayesian‐McMC methodology allows us to explore the potential benefits of including the geophysical data into the inverse problem by examining their effect on our ability to identify fast flowpaths in the subsurface, and their impact on hydrological prediction uncertainty. Using a complex, geostatistically generated, two‐dimensional numerical example representative of a fluvial environment, we demonstrate that flow model calibration is improved and prediction error is decreased when the electrical resistivity data are included. The worth of the geophysical data is found to be greatest for long spatial correlation lengths of subsurface heterogeneity with respect to wellbore separation, where flow and transport are largely controlled by highly connected flowpaths.
Full text
Available for:
BFBNIB, CEKLJ, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Rock physics attempts to relate the geophysical response of a rock to geologic properties of interest, such as porosity, lithology, and fluid content. The geophysical properties estimated by ...field‐scale surveys, however, are impacted by additional factors, such as complex averaging of heterogeneity at the scale of the survey and artifacts introduced through data inversion, that are not addressed by traditional approaches to rock physics. We account for these field‐scale factors by creating numerical analogs to geophysical surveys via Monte Carlo simulation. The analogs are used to develop field‐scale rock physics relationships that are appropriate for transforming the geophysical properties estimated from a survey into geologic properties. We demonstrate the technique using a synthetic example where radar tomography is used to estimate water content.
Full text
Available for:
FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
We present an approach to infer mass transfer parameters based on (1) an analytical model that relates the temporal moments of mobile and bulk concentration and (2) a bicontinuum modification to ...Archie's law. Whereas conventional geochemical measurements preferentially sample from the mobile domain, electrical resistivity tomography (ERT) is sensitive to bulk electrical conductivity and, thus, electrolytic solute in both the mobile and immobile domains. We demonstrate the new approach, in which temporal moments of collocated mobile domain conductivity (i.e., conventional sampling) and ERT‐estimated bulk conductivity are used to calculate heterogeneous mass transfer rate and immobile porosity fractions in a series of numerical column experiments.
Full text
Available for:
BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
PDF
