Tracer Concentration Data Research Articles

Harvesting Earth's heat: A deep learning Odyssey for reservoir characterization and sustainable geothermal energy management

Characterizing and predicting reservoir behavior pose significant challenges in geothermal reservoir engineering. For sustainable geothermal field management, the potential occurrence of thermal breakthroughs in producers during the injection of cold water necessitates a profound understanding of how production is influenced by the injection philosophy. The fractured nature of geothermal reservoirs adds complexity and nonlinearity to the relationship between production and injection wells. In this study, we explore alternative models to simulate reservoir behavior as substitutes for full reservoir simulations. Utilizing deep learning algorithms, we investigate two different architectures, namely the standard Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU). These models map injection flow rates at the injectors to tracer concentration data at the producers through layers, nodes, and activation functions. Training these models on a synthetic geothermal reservoir, Notably, the GRU architecture consistently demonstrates superior predictive capabilities across various scenarios for all three producers. Specifically, in configurations involving a target feed, the GRU model yields higher R2 values compared to its LSTM counterpart, indicating its effectiveness in capturing inter-well relationships. Furthermore, when considering all producers collectively, the GRU model exhibits a trend of lower test errors and higher R2 values, reaffirming its proficiency in modeling complex reservoir dynamics. These findings underscore the significance of GRU as a preferred choice for accurate reservoir behavior prediction. In addition to the aforementioned insights, our study contributes novel approaches to reservoir behavior prediction in the field of geothermal reservoir engineering. By leveraging deep learning algorithms, specifically the GRU and LSTM architectures, we introduce innovative methodologies for simulating reservoir behavior as alternatives to full reservoir simulations. Through comprehensive analysis, we demonstrate the superior predictive capabilities of the GRU model, particularly in capturing inter-well relationships and modeling complex reservoir dynamics.

Averaging equation of three-dimensional tracer transport by a dual approach

The conventional method for calculating averaged tracer concentration in three-dimensional tracer transport equation relies on classical averaging, which averages tracer concentration data obtained from the tracer transport equation in turbulent flow. However, the averaging tracer concentration quantity calculated by this method is not precisely the same as the one obtained by the dual approach. To address this issue, the author proposes a more intricate dual approach for averaging the three-dimensional tracer transport equation in turbulent flow. This paper describes how the author performs two integrations: one from time t to t + r (where r < T, T being the repeated period of fluctuating concentration), and another from time t to time t + T. The fluctuating concentration quantity in turbulent flow is modeled using the trigonometric Fourier series. The resulting three-dimensional mathematical model of tracer transport obtained by this dual approach is more comprehensive than the one obtained by the classical method.

Field study to estimate exposure to vehicle exhaust during idling and starting

Several studies indicate that exposure to pollutants emitted by vehicles is linked to several adverse health effects. There are few measurements that can be used to examine exposure to emissions from idling or slowly moving vehicles exposed to atmospheric flow and turbulence; such situations occur when people are waiting to be picked up by public or private vehicles. We report on a field study that collected tracer concentration data at distances of a few meters from the tailpipe of a vehicle when the accelerator pedal was controlled to simulate idling and starting conditions. Analysis of the data shows that the measurements are within a factor of two of results from a dispersion model that uses micrometeorological variables as inputs and includes plume rise associated with the buoyancy of the exhaust plume. The data suggest that people situated a few meters from an idling vehicle are likely to be exposed to levels of NO2 that are above the 1-h standard of 100 ppb.

RTD Measurement, Modeling, and Analysis of Liquid Phase of Three-Tube Industrial Pulp Digester

Abstract Residence-time distribution (RTD) experiments were performed to analyze an industrial scale three-tube series continuous pulping digester’s hydrodynamic performance. An impulse of radiotracer 82Br (γ energy source) was introduced at the inlet of the first tube. The radiotracer concentration in the liquid phase was traced at the outlet of each tube. The input behavior of the radiotracer converted to a non-ideal pulse tracer input for the second and third tubes of the digester. Numerical convolution is adopted to deal with the non-ideal pulse input of the radiotracer. A modeling procedure for determining the RTD from the outlet tracer concentration data is proposed. A plug flow component followed by axial dispersion model is considered, and is adjusted after its convolution with the inlet tracer concentration data to obtain the RTD of the individual tubes. The obtained RTD data are analyzed to explain the flow behavior, degree of dispersion, and flow abnormalities existing in the digester. The mean residence-time (MRT), and dispersion number are estimated for the model components for the three tubes. The vessel dispersion number is found to decrease from tube 1 to tube 3. Overall, the conversion of the highly dispersed flow regime into the plug-flow regime is observed in the whole digester.

Regional-scale analysis of karst underground flow deduced from tracing experiments: examples from carbonate aquifers in Malaga province, southern Spain

Tracer concentration data from field experiments conducted in several carbonate aquifers (Malaga province, southern Spain) were analyzed following a dual approach based on the graphical evaluation method (GEM) and solute transport modeling to decipher flow mechanisms in karst systems at regional scale. The results show that conduit system geometry and flow conditions are the principal factors influencing tracer migration through the examined karst flow routes. Solute transport is mainly controlled by longitudinal advection and dispersion throughout the conduit length, but also by flow partitioning between mobile and immobile fluid phases, while the matrix diffusion process appears to be less relevant. The simulation of tracer breakthrough curves (BTCs) suggests that diffuse and concentrated flow through the unsaturated zone can have equivalent transport properties under extreme recharge, with high flow velocities and efficient mixing due to the high hydraulic gradients generated. Tracer mobilization within the saturated zone under low flow conditions mainly depends on the hydrodynamics (rather than on the karst conduit development), which promote a lower longitudinal advection and retardation in the tracer migration, resulting in a marked tailing effect of BTCs. The analytical advection-dispersion equation better approximates the effective flow velocity and longitudinal dispersion estimations provided by the GEM, while the non-equilibrium transport model achieves a better adjustment of most asymmetric and long-tailed BTCs. The assessment of karst underground flow properties from tracing tests at regional scale can aid design of groundwater management and protection strategies, particularly in large hydrogeological systems (i.e. transboundary carbonate aquifers) and/or in poorly investigated ones.

Simultaneous local determination of mass transfer and residence time distributions in organic multiphase systems

A new method for simultaneous local determination of mass transfer coefficients and residence time distributions in continuously operated bubble columns has been developed. Since for organic liquids not many experimental data sets are available in respect to mass transfer, measurements were carried out with the organic gas/liquid multiphase system consisting of cumene (1-methylethylbenzene) and carbon dioxide. The concentration of carbon dioxide in the gas phase was adjusted by mixing with nitrogen. To measure concentrations of compounds in the liquid phase, attenuated total reflectance Fourier transform infrared spectroscopy (ATR FTIR) was applied: five ATR probes integrating silver-halide optical fibers with a length of 1.5m were integrated in a bubble column of 128.5cm height and a diameter of 10cm. The probes were distributed over the height of the reactor and could be shifted within the reactor to measure radial profiles of the mass transfer coefficients in steady state operation mode at different positions. The superficial liquid velocity of the system was adjusted in the range of 0.7–1.4cms−1. The used superficial gas velocities were between 1.5cms−1 and 2.1cms−1 to ensure a homogeneous flow regime. Furthermore, tracer experiments with benzaldehyde for the investigation of the residence time distributions were performed. From the FTIR spectral data, CO2 and benzaldehyde tracer concentration data were determined simultaneously by conducting multivariate chemometric models. The corresponding mass transfer coefficients were calculated using a compartmental method for stationary flow. The residence time distributions were calculated from the benzoic aldehyde concentration data. Both parameters could be determined successfully. For the mass transfer coefficient of carbon dioxide into cumene, an interesting profile could be observed, which arose from several influences like areas of different bubble densities, caused by bubble breakage and coalescence, superficial velocities of gas and liquid as well as the applied type of sparger.

Fluoride tracer test for the performance analysis of a basin used as a lagooning pre-treatment facility in a WTP.

The water treatment plant (WTP) of the city of Torino (NW Italy), which treats about 40 · 10(6)m(3)/year of raw water from Po river, has a 15-ha basin used as a lagooning pre-treatment facility. Since the efficiency of the lagooning process in the removal of pollutants from raw water depends on the internal hydrodynamics of the basin, the hydraulic performance of the basin was studied by combining the results of a stimulus-response tracer test with the monitoring of the tracer (fluoride) concentration throughout the basin at different times. The outcomes of the test demonstrated that the system was efficiently mixed and could be assimilated to a continuous stirred reactor presenting no flow anomalies, with an actual mean residence time (RT) of 12.7days, compared with a nominal RT of 18days. This assured that dissolved contaminants (such as fluoride) coming from the river were efficiently diluted before entering the WTP. The axial dispersion coefficient calculated from the RT distribution was approximately 47,300m(2)/day. Three of the most popular formulae developed for the calculation of the axial dispersion coefficient provided results spreading over three orders of magnitude, thus showing their limitations. Finally, because of the width extent of the basin and the characteristics of its inflow, the 1-D advection-dispersion model failed in predicting the tracer concentration values in time at the outlet channel. On the contrary, the analytical solution of the 2-D advection-dispersion model proved to be suitable to fit the tracer concentration data over time at the outlet channel but it failed in describing the tracer distribution throughout the basin on the monitoring dates.

An experimental study of stratified–dispersed flow in horizontal pipes

The tracer method has been adopted to study stratified–dispersed flow in a horizontal pipe, 80mm in diameter and 50m long, operating at 5Bar with nitrogen–water mixtures. The use of the tracer method in a horizontal pipe required the development of a specially designed test section, the related electronics and a data acquisition system. It has also been necessary to develop a tracer injection system, which has been designed in order to obtain uniform tracer concentration in the liquid film immediately after its injection. The main flow parameters which can be measured with the present experimental set-up are the circumferential distribution of the film height, flow rate and tracer concentration, the rates of droplet entrainment and deposition and the split of the liquid phase between the wall layer and the entrained droplets. The average tracer concentration data have been interpreted with a new three-field model of the liquid phase in the stratified–dispersed flow pattern. In the present formulation, the model holds for steady, fully developed flow conditions and is based on a one-dimensional description of the flow system. The data cover a limited number of flow conditions.

Nonparametric estimation of groundwater residence time distributions: What can environmental tracer data tell us about groundwater residence time?

AbstractResidence time distributions (RTDs) have been used extensively for quantifying flow and transport in subsurface hydrology. In geochemical approaches, environmental tracer concentrations are used in conjunction with simple lumped parameter models (LPMs). Conversely, numerical simulation techniques require large amounts of parameterization and estimated RTDs are certainly limited by associated uncertainties. In this study, we apply a nonparametric deconvolution approach to estimate RTDs using environmental tracer concentrations. The model is based only on the assumption that flow is steady enough that the observed concentrations are well approximated by linear superposition of the input concentrations with the RTD; that is, the convolution integral holds. Even with large amounts of environmental tracer concentration data, the entire shape of an RTD remains highly nonunique. However, accurate estimates of mean ages and in some cases prediction of young portions of the RTD may be possible. The most useful type of data was found to be the use of a time series of tritium. This was due to the sharp variations in atmospheric concentrations and a short half‐life. Conversely, the use of CFC compounds with smoothly varying atmospheric concentrations was more prone to nonuniqueness. This work highlights the benefits and limitations of using environmental tracer data to estimate whole RTDs with either LPMs or through numerical simulation. However, the ability of the nonparametric approach developed here to correct for mixing biases in mean ages appears promising.

Intelligent Inflow Tracers Obtain Information With Less Risk, Cost

Young Technology Showcase Today’s field developments are increasingly characterized by complex wells in demanding and costly operating environments. Not only are individual wells challenging, but most are part of a complex reservoir network that must be managed over an extended period. The high cost and risk of acquiring reservoir surveillance information using conventional technology, such as production logging tools, is forcing operators to manage these fields without knowledge of the inflow distribution across the reservoir interval. In addition, permanent reservoir surveillance solutions based on optical or electronic sensors require major modifications of the completion design and installation procedure. Consequently, a significant amount of complexity and risk are added to the project, making the use of such technologies prohibitive. Intelligent chemically based inflow tracer systems are an emerging technology that consist of engineered polymers and chemical compounds combined into a product that resembles strips of plastic. The tracer system is designed to react to either oil or water. For example, when a water-sensitive tracer system is contacted by water, the tracer system releases its unique chemical identification (inflow tracer) at a prescribed release rate, irrespective of the flowing conditions. The water-sensitive tracer system is dormant when contacted by oil, gas, or air. The oil-sensitive tracer system behaves similarly as the tracer is released only when it comes in contact with oil. Strips of the tracer system are readily integrated into almost any completion configuration including conventional sand screens, inflow control device (ICD) sand screens, multistage fracturing systems, pup joints, and intelligent completions. Additionally, the tracer system can be cemented behind casing and perforated through, providing contact between reservoir fluids and the intelligent tracer strips. In summary, the intelligent tracer strips can be deployed in almost any well type without affecting the installation process. Samples of produced fluid are analyzed for the concentration of each intelligent tracer. Tracer concentration data, combined with model-based interpretation techniques, enables the operator to understand where oil is entering the well, where water influx is occurring, and relative oil contributions of monitored zones.

Computational Fluid Dynamics Modeling of Corrugated Static Mixers for Turbulent Applications

This work is aimed at investigating the capability of a fully predictive computational fluid dynamics (CFD) approach to catch the main features of the liquid flow in pipelines equipped with corrugated static mixer inserts. The simulations are based on the numerical solution of the Reynolds averaged Navier–Stokes equations on the three-dimensional domain closely representing the static mixer geometry. As a benchmark, literature experiments on a laboratory scale SMV mixer were considered and the simulation results obtained at different locations were compared with relevant velocity and tracer concentration data. The effect of the turbulence modeling, the near-wall treatment, and the numerical approximations on the accuracy of the results is discussed. The results analysis demonstrated that the selected CFD model can be reliably adopted to evaluate the velocity field and the mixing performances of turbulent flows in static mixers for design and optimization purposes. On the other hand, the application of the...

Evaluation of a Voxelized Model Based on DCE-MRI for Tracer Transport in Tumor

Recent advances in the treatment of cancer involving therapeutic agents have shown promising results. However, treatment efficacy can be limited due to inadequate and uneven uptake in solid tumors, thereby making the prediction of drug transport important for developing effective therapeutic strategies. In this study, a patient-specific computational porous media model (voxelized model) was developed for predicting the interstitial flow field and distribution of a systemically delivered magnetic resonance (MR) visible tracer in a tumor. The benefits of a voxel approach include less labor and less computational time (approximately an order of magnitude reduction compared to the traditional computational fluid dynamics (CFD) approach developed earlier by our group). The model results were compared with that obtained from a previous approach based on unstructured meshes along with MR-measured tracer concentration data within tumors, using statistical analysis and qualitative representations. The statistical analysis indicated the similarity between the structured and unstructured models' results with a low root mean square error (RMS) and a high correlation coefficient. The voxelized model captured features of the flow field and tracer distribution such as high interstitial fluid pressure inside the tumor and the heterogeneous distribution of the tracer. Predictions of tracer distribution by the voxelized approach also resulted in low RMS error when compared with MR-measured data over a 1 h time course. The similarity in the voxelized model results with experiment and the nonvoxelized model predictions were maintained across three different tumors. Overall, the voxelized model serves as a reliable and swift alternative to approaches using unstructured meshes in predicting extracellular transport within tumors.

Evaluation of transverse dispersion effects in tank experiments by numerical modeling: Parameter estimation, sensitivity analysis and revision of experimental design

Transverse dispersion represents an important mixing process for transport of contaminants in groundwater and constitutes an essential prerequisite for geochemical and biodegradation reactions. Within this context, this work describes the detailed numerical simulation of highly controlled laboratory experiments using uranine, bromide and oxygen depleted water as conservative tracers for the quantification of transverse mixing in porous media. Synthetic numerical experiments reproducing an existing laboratory experimental set-up of quasi two-dimensional flow through tank were performed to assess the applicability of an analytical solution of the 2D advection-dispersion equation for the estimation of transverse dispersivity as fitting parameter. The fitted dispersivities were compared to the “true” values introduced in the numerical simulations and the associated error could be precisely estimated. A sensitivity analysis was performed on the experimental set-up in order to evaluate the sensitivities of the measurements taken at the tank experiment on the individual hydraulic and transport parameters. From the results, an improved experimental set-up as well as a numerical evaluation procedure could be developed, which allow for a precise and reliable determination of dispersivities. The improved tank set-up was used for new laboratory experiments, performed at advective velocities of 4.9m d−1 and 10.5m d−1. Numerical evaluation of these experiments yielded a unique and reliable parameter set, which closely fits the measured tracer concentration data. For the porous medium with a grain size of 0.25–0.30mm, the fitted longitudinal and transverse dispersivities were 3.49×10−4m and 1.48×10−5m, respectively. The procedures developed in this paper for the synthetic and rigorous design and evaluation of the experiments can be generalized and transferred to comparable applications.

Stochastic inversion of tracer test and electrical geophysical data to estimate hydraulic conductivities

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.

A STUDY OF HYDRAULIC PROPERTIES IN A SINGLE FRACTURE WITH IN-PLANE HETEROGENEITY: AN EVALUATION USING OPTICAL MEASUREMENTS OF A TRANSPARENT REPLICA

Experimental examinations for evaluating fracutres were conducted by using transparent replicas of a single fracture in order to obtain the fracture data to contribute to the methodlogy on how to improve the definitaion of representative parameter values used for a parallel plate fracture model. Quantitative aperture distribution and quantitative tracer concentration data at each point in time were obtained by measuring the attenuation of transmitted light through the fracture in high spatial resolution. the representative aperture values evaluated from the multiple different measurement methods, such as arithmetic mean of aperture distribution measured by the optical method, transport aperture evaluated from the tracer test, and average aperture evaluated from the fracture void volume measurement converged to a unique value that indicates the accuracy of this experimental study. The aperture data was employed for verifying the numerical simulation under the assuption of Local Cubic Law and showed that the calculated flow rate through the fracture is 10%-100% larger than hydraulic test results. The quantitative tracer concentration data is also very valuable for validating existing numerical code for advection dispersion transport in-plane heterogeneous fractures.

Analysis of tracer tomography using temporal moments of tracer breakthrough curves

Hydraulic/partitioning tracer tomography (HPTT) was recently developed by Yeh and Zhu [Yeh T-CJ, Zhu J. Hydraulic/partitioning tracer tomography for characterization of dense nonaqueous phase liquid source zones, Water Resour Res 2007;43:W06435. doi:10.1029/2006WR004877.] for estimating spatial distribution of dense nonaqueous phase liquids (DNAPLs) in the subsurface. Since discrete tracer concentration data are directly utilized for the estimation of DNAPLs, this approach solves the hyperbolic convection–dispersion equation. Solution to the convection–dispersion equation however demands fine temporal and spatial discretization, resulting in high computational cost for an HPTT analysis. In this work, we use temporal moments of tracer breakthrough curves instead of discrete concentration data to estimate DNAPL distribution. This approach solves time independent partial differential equations of the temporal moments, and therefore avoids solving the convection–dispersion equation using a time marching scheme, resulting in a dramatic reduction of computational cost. To reduce numerical oscillations associated with convection dominated transport problems such as in inter-well tracer tests, the approach uses a finite element solver adopting the streamline upwind Petrov–Galerkin method to calculate moments and sensitivities. We test the temporal moment approach through numerical simulations. Comparing the computational costs between utilizing moments and discrete concentrations, we find that temporal moments significantly reduce the computation time. We also find that tracer moment data collected through a tomographic survey alone are able to yield reasonable estimates of hydraulic conductivity, as indicated by a correlation of 0.588 between estimated and true hydraulic conductivity fields in the synthetic case study.

Mixing of shallow and deep groundwater as indicated by the chemistry and age of karstic springs

Large karstic springs in east-central Florida, USA were studied using multi-tracer and geochemical modeling techniques to better understand groundwater flow paths and mixing of shallow and deep groundwater. Spring water types included Ca–HCO3 (six), Na–Cl (four), and mixed (one). The evolution of water chemistry for Ca–HCO3 spring waters was modeled by reactions of rainwater with soil organic matter, calcite, and dolomite under oxic conditions. The Na–Cl and mixed-type springs were modeled by reactions of either rainwater or Upper Floridan aquifer water with soil organic matter, calcite, and dolomite under oxic conditions and mixed with varying proportions of saline Lower Floridan aquifer water, which represented 4–53% of the total spring discharge. Multiple-tracer data—chlorofluorocarbon CFC-113, tritium (3H), helium-3 (3Hetrit), sulfur hexafluoride (SF6)—for four Ca–HCO3 spring waters were consistent with binary mixing curves representing water recharged during 1980 or 1990 mixing with an older (recharged before 1940) tracer-free component. Young-water mixing fractions ranged from 0.3 to 0.7. Tracer concentration data for two Na–Cl spring waters appear to be consistent with binary mixtures of 1990 water with older water recharged in 1965 or 1975. Nitrate-N concentrations are inversely related to apparent ages of spring waters, which indicated that elevated nitrate-N concentrations were likely contributed from recent recharge.

Mixing of shallow and deep groundwater as indicated by the chemistry and age of karstic springs

Large karstic springs in east-central Florida, USA were studied using multi-tracer and geochemical modeling techniques to better understand groundwater flow paths and mixing of shallow and deep groundwater. Spring water types included Ca–HCO3 (six), Na–Cl (four), and mixed (one). The evolution of water chemistry for Ca–HCO3 spring waters was modeled by reactions of rainwater with soil organic matter, calcite, and dolomite under oxic conditions. The Na–Cl and mixed-type springs were modeled by reactions of either rainwater or Upper Floridan aquifer water with soil organic matter, calcite, and dolomite under oxic conditions and mixed with varying proportions of saline Lower Floridan aquifer water, which represented 4–53% of the total spring discharge. Multiple-tracer data—chlorofluorocarbon CFC-113, tritium (3H), helium-3 (3Hetrit), sulfur hexafluoride (SF6)—for four Ca–HCO3 spring waters were consistent with binary mixing curves representing water recharged during 1980 or 1990 mixing with an older (recharged before 1940) tracer-free component. Young-water mixing fractions ranged from 0.3 to 0.7. Tracer concentration data for two Na–Cl spring waters appear to be consistent with binary mixtures of 1990 water with older water recharged in 1965 or 1975. Nitrate-N concentrations are inversely related to apparent ages of spring waters, which indicated that elevated nitrate-N concentrations were likely contributed from recent recharge.

Collection of Unsaturated‐Zone Water Samples for Tracer Analysis: Evaluation of an Inverting Membrane Technique

AbstractAs part of the site characterization efforts at Yucca Mountain, Nevada, a series of unsaturated zone tracer tests has been performed at nearby Busted Butte. The phase 2 tracer test was conducted within an instrumented 10 m by 10 m by 7 m in situ block of vitric tuff. A complex tracer solution containing both reactive and nonreactive tracers was pumped into the block during a period of 27 months. Throughout the test, thousands of unsaturated zone pore water samples were collected on sorptive pads attached to inverting membranes and then analyzed for tracer concentration. Partway through the experiment, three new boreholes were drilled into the block, and two intercepted the tracer plume. The rock core was removed for pore water extraction and analysis, and the boreholes were then instrumented with inverting membranes and sorptive pads. The initial set of pore water‐soaked pads was removed from the boreholes a week after they were emplaced, and the pore water was extracted and analyzed. This paper compares the tracer concentration data from the rock cores and the pads to evaluate the effectiveness of the inverting membrane collection technique for a variety of tracers. While the sorptive pads sample only dissolved tracers, rock cores contain both dissolved and sorbed tracer. For nonreactive tracers, such as halides (bromide and iodide) and fluorinated benzoic acids (FBAs), this distinction is immaterial, and the rock and pad data agree quantitatively for the halide tracers, and qualitatively for the FBAs. For reactive tracers, such as lithium, the dissolved tracer concentrations can be estimated from rock analyses by dividing by the tracer's retardation factor; when this correction is applied, the rock and pad lithium data are also in reasonable agreement.

Field investigation into unsaturated flow and transport in a fault: model analyses

Results of a fault test performed in the unsaturated zone of Yucca Mountain, Nevada, were analyzed using a three-dimensional numerical model. The fault was explicitly represented as a discrete feature and the surrounding rock was treated as a dual-continuum (fracture–matrix) system. Model calibration against seepage and water-travel-velocity data suggests that lithophysal cavities connected to fractures can considerably enhance the effective fracture porosity and therefore retard water flow in fractures. Comparisons between simulation results and tracer concentration data also indicate that matrix diffusion is an important mechanism for solute transport in unsaturated fractured rock. We found that an increased fault–matrix and fracture–matrix interface areas were needed to match the observed tracer data, which is consistent with previous studies. The study results suggest that the current site-scale model for the unsaturated zone of Yucca Mountain may underestimate radionuclide transport time within the unsaturated zone, because an increased fracture–matrix interface area and the increased effective fracture porosity arising from lithophysal cavities are not considered in the current site-scale model.