Unsaturated Fractured Tuff Research Articles

The role of international collaboration in the United States geologic disposal research program

Abstract. More than a decade ago, the United States disposal program discontinued all research activities focused on the unsaturated fractured tuff formation at Yucca Mountain as the geologic disposal site for spent fuel and high-level radioactive waste. A new research and development (R&D) program was initiated to provide a sound technical basis for alternative disposal options across clay, crystalline, and salt rocks. The goals of this broad program were (and still are) to (1) increase confidence in the robustness of generic disposal concepts, (2) develop the science and engineering tools needed to support disposal concept implementation, and (3) conduct R&D on the direct disposal of existing dual-purpose (storage and transportation) canisters. Recognizing the benefits of international collaboration toward the common goal of safely and efficiently managing the back end of the nuclear fuel cycle, the program emphasized international cooperation as an effective strategy for sharing information and knowledge. In a multi-laboratory effort coordinated by Lawrence Berkeley National Laboratory, the United States Department of Energy (DOE) program established formal and informal cooperation partnerships with several international initiatives and institutions and developed a number of collaborative R&D activities in important research areas, such as engineered barrier integrity, near-field perturbations, radionuclide transport, performance assessment, and methods for characterization and monitoring of engineered and natural barriers. This presentation gives an overview of these R&D activities, with a specific focus on activities that improve our current understanding of the coupled thermal–hydrological–mechanical–chemical (THMC) processes occurring in engineered and natural barriers. We start with a brief review of selected international collaboration initiatives and then describe a few specific collaboration projects. We focus specifically on such studies that use experimental data sets provided by international research cooperation for joint modeling work to increase confidence in performance-relevant predictions of coupled processes. Overall, the focus on international collaboration has allowed deep engagement of US researchers with the international waste management R&D community in terms of best practices, new scientific advances, state-of-the-art simulation tools, new monitoring and performance confirmation approaches, and lessons learned. The joint R&D with international researchers, worldwide sharing of knowledge and experience, and access to relevant data and experiments from a variety of host rocks have helped our researchers to significantly improve their understanding of the current technical basis for disposal in a range of potential host rock environments. International collaboration also provides ample opportunity for training and educating junior staff that are well suited to move the United States disposal research program forward into the next decades, a promising avenue for developing a next-generation workforce of disposal scientists.

Extended power-law scaling of heavy-tailed random air-permeability fields in fractured and sedimentary rocks

Abstract. We analyze the scaling behaviors of two field-scale log permeability data sets showing heavy-tailed frequency distributions in three and two spatial dimensions, respectively. One set consists of 1-m scale pneumatic packer test data from six vertical and inclined boreholes spanning a decameters scale block of unsaturated fractured tuffs near Superior, Arizona, the other of pneumatic minipermeameter data measured at a spacing of 15 cm along three horizontal transects on a 21 m long and 6 m high outcrop of the Upper Cretaceous Straight Cliffs Formation, including lower-shoreface bioturbated and cross-bedded sandstone near Escalante, Utah. Order q sample structure functions of each data set scale as a power ξ(q) of separation scale or lag, s, over limited ranges of s. A procedure known as extended self-similarity (ESS) extends this range to all lags and yields a nonlinear (concave) functional relationship between ξ(q) and q. Whereas the literature tends to associate extended and nonlinear power-law scaling with multifractals or fractional Laplace motions, we have shown elsewhere that (a) ESS of data having a normal frequency distribution is theoretically consistent with (Gaussian) truncated (additive, self-affine, monofractal) fractional Brownian motion (tfBm), the latter being unique in predicting a breakdown in power-law scaling at small and large lags, and (b) nonlinear power-law scaling of data having either normal or heavy-tailed frequency distributions is consistent with samples from sub-Gaussian random fields or processes subordinated to tfBm or truncated fractional Gaussian noise (tfGn), stemming from lack of ergodicity which causes sample moments to scale differently than do their ensemble counterparts. Here we (i) demonstrate that the above two data sets are consistent with sub-Gaussian random fields subordinated to tfBm or tfGn and (ii) provide maximum likelihood estimates of parameters characterizing the corresponding Lévy stable subordinators and tfBm or tfGn functions.

Sub-Gaussian model of processes with heavy-tailed distributions applied to air permeabilities of fractured tuff

Earth and environmental variables are commonly taken to have multivariate Gaussian or heavy-tailed distributions in space and/or time. This is based on the observation that univariate frequency distributions of corresponding samples appear to be Gaussian or heavy-tailed. Of particular interest to us is the well-documented but heretofore little noticed and unexplained phenomenon that whereas the frequency distribution of log permeability data often seems to be Gaussian, that of corresponding increments tends to exhibit heavy tails. The tails decay as powers of −\( \alpha \) where 1 < \( \alpha \) < 2 is either constant or grows monotonically toward an asymptote with increasing separation distance or lag. We illustrate the latter phenomenon on 1-m scale log air permeabilities from pneumatic tests in 6 vertical and inclined boreholes completed in unsaturated fractured tuff near Superior, Arizona. We then show theoretically and demonstrate numerically, on synthetically generated signals, that whereas the case of constant \( \alpha \) is consistent with a collection of samples from truncated sub-Gaussian fractional Levy noise, a random field (or process) subordinated to truncated fractional Gaussian noise, the case of variable \( \alpha \) is consistent with a collection of samples from truncated sub-Gaussian fractional Levy motion (tfLm), a random field subordinated to truncated fractional Brownian motion. Whereas the first type of signal is relatively regular and characterized by Levy index \( \alpha \), the second is highly irregular (punctuated by spurious spikes) and characterized by the asymptote of \( \alpha \) values associated with its increments. We describe a procedure to estimate the parameters of univariate distributions characterizing such signals and apply it to our log air permeability data. The latter are found to be consistent with a collection of samples from tfLm with \( \alpha \) slightly smaller than 2, which is easily confused with a Gaussian field (characterized by constant \( \alpha \) = 2). The irregular (spiky) nature of this signal is typical of observed fractured rock properties. We propose that distributions of earth and environmental variable be inferred jointly from measured values and their increments in a way that insures consistency between these two sets of data.

Multimodel Bayesian analysis of data-worth applied to unsaturated fractured tuffs

To manage water resource and environmental systems effectively requires suitable data. The worth of collecting such data depends on their potential benefit and cost, including the expected cost (risk) of failing to take an appropriate decision. Evaluating this risk calls for a probabilistic approach to data-worth assessment. Recently we [39] developed a multimodel approach to optimum value-of-information or data-worth analysis based on model averaging within a maximum likelihood Bayesian framework. Adopting a two-dimensional synthetic example, we implemented our approach using Monte Carlo (MC) simulations with and without lead order approximations, finding that the former approach was almost equally accurate but computationally more efficient. Here we apply our methodology to pneumatic permeability data from vertical and inclined boreholes drilled into unsaturated fractured tuff near Superior, Arizona. In an attempt to improve computational efficiency, we introduce three new approximations that require less computational effort and compare results with those obtained by the original Monte Carlo method. The first approximation disregards uncertainty in model parameter estimates, the second does so for estimates of potential new data, and the third disregards both uncertainties. We find that only the first approximation yields reliable quantitative assessments of reductions in predictive uncertainty brought about by the collection of new data. We conclude that, whereas parameter uncertainty may sometimes be disregarded for purposes of analyzing data worth, the same does not generally apply to uncertainty in estimates of potential new data.

Maximum likelihood Bayesian averaging of airflow models in unsaturated fractured tuff using Occam and variance windows

We use log permeability and porosity data obtained from single-hole pneumatic packer tests in six boreholes drilled into unsaturated fractured tuff near Superior, Arizona, to postulate, calibrate and compare five alternative variogram models (exponential, exponential with linear drift, power, truncated power based on exponential modes, and truncated power based on Gaussian modes) of these parameters based on four model selection criteria (AIC, AICc, BIC and KIC). Relying primarily on KIC and cross-validation we select the first three of these variogram models and use them to parameterize log air permeability and porosity across the site via kriging in terms of their values at selected pilot points and at some single-hole measurement locations. For each of the three variogram models we estimate log air permeabilities and porosities at the pilot points by calibrating a finite volume pressure simulator against two cross-hole pressure data sets from sixteen boreholes at the site. The traditional Occam’s window approach in conjunction with AIC, AICc, BIC and KIC assigns a posterior probability of nearly 1 to the power model. A recently proposed variance window approach does the same when applied in conjunction with AIC, AICc, BIC but spreads the posterior probability more evenly among the three models when used in conjunction with KIC. We compare the abilities of individual models and MLBMA, based on both Occam and variance windows, to predict space–time pressure variations observed during two cross-hole tests other than those employed for calibration. Individual models with the largest posterior probabilities turned out to be the worst or second worst predictors of pressure in both validation cases. Some individual models predicted pressures more accurately than did MLBMA. MLBMA was far superior to any of the individual models in one validation test and second to last in the other validation test in terms of predictive coverage and log scores.

Dual-Permeability Modeling of Capillary Diversion and Drift Shadow Effects in Unsaturated Fractured Rock

The drift-shadow effect describes capillary diversion of water flow around a drift or cavity in porous or fractured rock, resulting in lower water flux directly beneath the cavity. This paper presents computational simulations of drift-shadow experiments using dual-permeability models, similar to the models used for performance assessment analyses of flow and seepage in unsaturated fractured tuff at Yucca Mountain. Comparisons were made between the simulations and experimental data from small-scale drift-shadow tests. Results showed that the dual-permeability models captured the salient trends and behavior observed in the experiments, but constitutive relations (e.g., fracture capillary-pressure curves) can significantly affect the simulated results. Lower water flux beneath the drift was observed in both the simulations and tests, and fingerlike flow patterns were seen to exist with lower simulated capillary pressures. The dual-permeability models used in this analysis were capable of simulating these processes. However, features such as irregularities along the top of the drift (e.g., from roof collapse) and heterogeneities in the fracture network may reduce the impact of capillary diversion and drift shadow. An evaluation of different meshes showed that at the grid refinement used, a comparison between orthogonal and unstructured meshes did not result in large differences.

Analyzing unsaturated flow patterns in fractured rock using an integrated modeling approach

Characterizing percolation patterns in unsaturated fractured rock has posed a greater challenge to modeling investigations than comparable saturated zone studies, because of the heterogeneous nature of unsaturated media and the great number of variables impacting unsaturated flow. This paper presents an integrated modeling methodology for quantitatively characterizing percolation patterns in the unsaturated zone of Yucca Mountain, Nevada, a proposed underground repository site for storing high-level radioactive waste. The modeling approach integrates a wide variety of moisture, pneumatic, thermal, and isotopic geochemical field data into a comprehensive three-dimensional numerical model for modeling analyses. It takes into account the coupled processes of fluid and heat flow and chemical isotopic transport in Yucca Mountain's highly heterogeneous, unsaturated fractured tuffs. Modeling results are examined against different types of field-measured data and then used to evaluate different hydrogeological conceptualizations and their results of flow patterns in the unsaturated zone. In particular, this model provides a much clearer understanding of percolation patterns and flow behavior through the unsaturated zone, both crucial issues in assessing repository performance. The integrated approach for quantifying Yucca Mountain's flow system is demonstrated to provide a practical modeling tool for characterizing flow and transport processes in complex subsurface systems.

Sensitivity analysis and assessment of prior model probabilities in MLBMA with application to unsaturated fractured tuff

Previous application of maximum likelihood Bayesian model averaging (MLBMA, Neuman (2002, 2003)) to alternative variogram models of log air permeability data in fractured tuff has demonstrated its effectiveness in quantifying conceptual model uncertainty and enhancing predictive capability (Ye et al., 2004). A question remained how best to ascribe prior probabilities to competing models. In this paper we examine the extent to which lead statistics of posterior log permeability predictions are sensitive to prior probabilities of seven corresponding variogram models. We then explore the feasibility of quantifying prior model probabilities by (1) maximizing Shannon's entropy H (Shannon, 1948) subject to constraints reflecting a single analyst's (or a group of analysts') prior perception about how plausible each alternative model (or a group of models) is relative to others, and (2) selecting a posteriori the most likely among such maxima corresponding to alternative prior perceptions of various analysts or groups of analysts. Another way to select among alternative prior model probability sets, which, however, is not guaranteed to yield optimum predictive performance (though it did so in our example) and would therefore not be our preferred option, is a minimum‐maximum approach according to which one selects a priori the set corresponding to the smallest value of maximum entropy. Whereas maximizing H subject to the prior perception of a single analyst (or group) maximizes the potential for further information gain through conditioning, selecting the smallest among such maxima gives preference to the most informed prior perception among those of several analysts (or groups). We use the same variogram models and log permeability data as Ye et al. (2004) to demonstrate that our proposed approach yields the least amount of posterior entropy (residual uncertainty after conditioning) and enhances predictive model performance as compared to (1) the noninformative neutral case in which all prior model probabilities are set equal to each other and (2) an informed case that nevertheless violates the principle of parsimony.

Strong field evidence of directional permeability scale effect in fractured rock

Permeability is a key parameter that controls mass and energy transport in geologic media. Its spatial variation is generally agreed within the research community, while the scale effect in permeability is still under considerable debate. This debate is mainly due to the lack of consistent measurement and interpretation of site data. Here, we show a strong field evidence of directional permeability scale effect from cross-hole pneumatic injection tests conducted in unsaturated fractured tuff at a field site in central Arizona, USA. The analysis reveals that permeability increases with the radial distance measured between the centroids of injection and monitoring locations of the test, which we consider to be the measurement scale. These results are compared to previously analyzed single-hole tests conducted at multiple measurement scales. We hypothesize that the permeability scale effect is controlled by the connectivity of fluid conducting fractures, which also increases with scale. This observation and hypothesis is consistent with existing scaling theories in fracture connectivity, although subsurface fracture connectivity cannot be measured directly with present technology. These results suggest the need to obtain permeability estimates that are commensurate with the scale of intended use.

Asymptotic analysis of cross-hole pneumatic injection tests in unsaturated fractured tuff

We present a new method to interpret three-dimensional pressure interference tests, which is based on an asymptotic analysis of late time pressure transient data. The approach yields reliable estimates of equivalent permeability and porosity without resorting to type-curve fitting or numerical inverse models. This is accomplished by analyzing the late-time behavior of type-curve solutions for pressure interference tests. We use our approach to infer the permeability and porosity of fractured tuff from cross-hole pneumatic injection test data. Their values are found to be in good agreement with those inferred from more complicated methods of data analysis. We analyze the statistical properties of the estimated equivalent permeability and porosity and observe a weak correlation between the two.

Type curve analyses of pneumatic single‐hole tests in unsaturated fractured tuff: Direct evidence for a porosity scale effect

A large number of single‐ and cross‐hole pneumatic injection tests have been conducted in shallow vertical and inclined boreholes in unsaturated fractured tuff at the Apache Leap Research Site (ALRS) near Superior, Arizona. Previously, direct and indirect evidence for a permeability scale effect was provided through the analysis of these tests. Direct evidence was based on the comparison of small‐scale single‐hole and larger‐scale cross‐hole test results obtained through the type curve and steady state analysis of these data separately. Indirect evidence was provided by comparing cross‐hole test analyses conducted at fine and coarse scales of resolution by means of a three‐dimensional numerical inverse model. The latter study also provided indirect evidence for a porosity scale effect. However, there were no small‐scale porosity data from single‐hole tests to directly verify this indirect evidence. This paper presents such data generated through the type curve interpretation of the recovery phase of the single‐hole tests conducted at a nominal 1‐m scale providing direct evidence for a porosity scale effect at the site. Statistical analysis of results revealed a strong porosity scale effect confirming an earlier finding obtained indirectly. These results also showed that (1) the injection phase of the pneumatic single‐hole tests do not yield reliable estimates of porosity but the recovery phase are amenable to type curve interpretation, (2) flow dimensionality of single‐hole tests at 1‐m scale are three‐dimensional across the site except for a few tests which exhibited two‐dimensional and fracture flow behavior, (3) there is a very weak correlation between permeability and porosity, and (4) there is a lack of correlation between fracture density and both permeability and porosity.

Asymptotic analysis of three‐dimensional pressure interference tests: A point source solution

Well test analyses conducted in steady state and transient flow regimes have complementary strengths and drawbacks. While steady state analyses are easy to interpret, they are useful only on a late‐time portion of the data collected during pressure interference tests and do not provide estimates of porosity. Transient type curve and numerical inverse approaches overcome these shortcomings but are harder to analyze, and their reliability can be affected by changing external forcings. We develop a new approach to estimate permeability and porosity from well tests, which is based on an asymptotic analysis of pressure transients during three‐dimensional pressure interference tests. Our approach results in a straight line data fitting, rendering the data interpretation straightforward. It also allows one to use intermediate‐to‐late time pressure data. To illustrate the advantages of the proposed technique, we use it to analyze data from several cross‐hole pneumatic injection tests conducted in unsaturated fractured tuff. We demonstrate that the equivalent permeabilities and porosities obtained from our analysis compare well with their counterparts inferred from more complicated approaches, such as type curve and numerical inverse analyses as well as from a steady state analysis.

Interpretation of pressure recovery data from packer inflation

A packer test conducted in porous or fractured medium includes a stage prior to the actual test in which packers are inflated. If the packers are inflated quickly, the pressure within the injection interval rises in a near‐instantaneous fashion and decays with time as it comes into equilibrium with the surrounding formation. These pressure recovery data are commonly not collected and never analyzed. However, the pressure transient resulting from packer inflation is akin to a pressurized slug test conducted within a packed off interval. Here we interpret 18 records of such pressure recovery data obtained prior to a cross‐hole pneumatic injection test conducted in unsaturated fractured tuff at the Apache Leap Research Site (ALRS) in central Arizona. We analyze these records by modifying the M. J. Hvorslev's method to account for airflow. Results from the analysis are compared against permeability (k) estimates obtained from a pneumatic slug test as well as several single‐ and cross‐hole pneumatic injection tests at the ALRS. This comparison shows that the k determined from the pressure recovery compares well with the result from the pneumatic slug test, but the estimates are noticeably smaller than the values determined from single‐ and cross‐hole tests, suggesting a k scale effect. In addition, the basic time lag (tB) obtained from the analysis of the pressure recovery data using M. J. Hvorslev's method is smaller than what was previously determined from the type curve interpretation of a cross‐hole pneumatic injection test. These results collectively suggest that the pressure transients from single‐ and cross‐hole tests conducted over a longer period at higher flow rates sample a much larger volume of the rock compared to the pressure recovery data from packer inflation at the ALRS.

Maximum likelihood Bayesian averaging of spatial variability models in unsaturated fractured tuff

Hydrologic analyses typically rely on a single conceptual‐mathematical model. Yet hydrologic environments are open and complex, rendering them prone to multiple interpretations and mathematical descriptions. Adopting only one of these may lead to statistical bias and underestimation of uncertainty. Bayesian model averaging (BMA) [Hoeting et al., 1999] provides an optimal way to combine the predictions of several competing models and to assess their joint predictive uncertainty. However, it tends to be computationally demanding and relies heavily on prior information about model parameters. Neuman [2002, 2003] proposed a maximum likelihood version (MLBMA) of BMA to render it computationally feasible and to allow dealing with cases where reliable prior information is lacking. We apply MLBMA to seven alternative variogram models of log air permeability data from single‐hole pneumatic injection tests in six boreholes at the Apache Leap Research Site (ALRS) in central Arizona. Unbiased ML estimates of variogram and drift parameters are obtained using adjoint state maximum likelihood cross validation [Samper and Neuman, 1989a] in conjunction with universal kriging and generalized least squares. Standard information criteria provide an ambiguous ranking of the models, which does not justify selecting one of them and discarding all others as is commonly done in practice. Instead, we eliminate some of the models based on their negligibly small posterior probabilities and use the rest to project the measured log permeabilities by kriging onto a rock volume containing the six boreholes. We then average these four projections and associated kriging variances, using the posterior probability of each model as weight. Finally, we cross validate the results by eliminating from consideration all data from one borehole at a time, repeating the above process and comparing the predictive capability of MLBMA with that of each individual model. We find that MLBMA is superior to any individual geostatistical model of log permeability among those we consider at the ALRS.

Analysis of permeability scaling within single boreholes

A pronounced permeability (k) scale effect has been previously observed through the analyses of single‐and cross‐hole pneumatic injection tests in unsaturated fractured tuff at the Apache Leap Research Site (ALRS) [Illman and Neuman, 2001, 2003; Vesselinov et al., 2001a, 2001b]. Here, we investigate whether such an effect is seen at the ALRS when one examines k data collected at multiple measurement scales within a single borehole. Results from single‐hole tests in 3 of 4 boreholes show that k increases with scale. However, this increase is considerably smaller than what has been previously surmised at the site. Data analysis reveals that flow is predominantly two‐dimensional (2D) for the single‐hole tests examined, and upscaling can be accomplished best by calculating a weighted arithmetic mean of individual measurements. The suppression of k scale effect within a single borehole is due to limited fracture connectivity near the injection interval which manifests as 2D flow. In contrast, flow during a cross‐hole test takes place through a highly connective fracture network which manifests as three‐dimensional (3D) flow.

Tracer migration experiments in unsaturated fractured tuff

Field tracer experiments were conducted at an underground tunnel—the Exploratory Studies Facility (ESF)—at Yucca Mountain, Nevada, to investigate the localized preferential flow and transport resulting from multiple episodic liquid-release tests in unsaturated fractured tuff. Liquid was released into an isolated test interval (0.30 m long) within a borehole drilled along ESF. Out of 60 liquid-release tests, 36 contained tracers (mostly food and fluorescent dyes) to help us to elucidate the flow paths in unsaturated tuff. After the tracer-migration test, an array of 12 boreholes was drilled into the test area to collect rock samples. These samples were then analyzed to delineate the extent of tracer migration. Complementary laboratory column transport studies using crushed rock showed that the dye tracers were—at most—very weakly sorbed to the tuff matrix. We found that the tracer-migration test, with a limited release volume of 1.5 L, resulted in a localized distribution of tracers, most likely confined to a 1.0 × 1.6-m area directly below the test interval (over a vertical experimental length of about 0.65 m). This conclusion was corroborated by detecting dyes that had been introduced during previous liquid-release seepage tests either before or after niche excavation; the spatial distribution of all dyes was near their individual release intervals. Limited lateral spreading of the dyes occurred, even when several non-dye-containing seepage tests were intermittently conducted following dye release. This work also demonstrates the utility of applying multiple tracers (including food and fluorescent dyes) to help delineate transport characteristics in unsaturated fractured rock.

Steady-state analysis of cross-hole pneumatic injection tests in unsaturated fractured tuff

Numerous single-hole and cross-hole pneumatic injection tests have been conducted in unsaturated fractured tuff at the Apache Leap Research Site (ALRS) near Superior, Arizona. Steady-state analyses of single-hole tests conducted by Guzman et al. [Summary of Air Permeability Data From Single-Hole Injection Tests in Unsaturated Fractured Tuffs at the Apache Leap Research Site: Results of Steady-State Test Interpretation (1996)] have yielded values of air permeability at various locations throughout the tested rock volume on nominal scales from 0.5 to 3.0 m. Analyses of transient data from single-hole and larger-scale cross-hole tests were performed by Illman and Neuman [Ground Water 38 (2000) 899; Water Resour. Res. 37 (2001) 583] using type-curves and by Vesselinov and Neuman [Ground Water 39 (2001) 685] and Vesselinov et al. [Water Resour. Res. 37 (2001a) 3001; Water Resour. Res. 37 (2001b) 3041] using numerical inversion. These have yielded bulk fracture permeabilities and porosities on scales ranging from a few meters to several tens of meters. We complement the latter results by steady-state analysis of a relatively large set of cross-hole tests. Steady-state analysis (a) allows interpreting cross-hole tests that were not interpreted using type-curves due to weak or noisy signals, (b) is relatively easy to perform, and (c) yields results comparable with those obtained from transient analyses. We analyze the results statistically and discuss their implications vis-a-vis the pneumatic properties of unsaturated fractured tuff at the ALRS. Our results strengthen the evidence for a previously surmised permeability scale effect at the site.

Uncertainties in coupled thermal–hydrological processes associated with the Drift Scale Test at Yucca Mountain, Nevada

Understanding thermally driven coupled hydrological, mechanical, and chemical processes in unsaturated fractured tuff is essential for evaluating the performance of the potential radioactive waste repository at Yucca Mountain, Nevada. The Drift Scale Test (DST), intended for acquiring such an understanding of these processes, has generated a huge volume of temperature and moisture redistribution data. Sophisticated thermal–hydrological (TH) conceptual models have yielded a good fit between simulation results and those measured data. However, some uncertainties in understanding the TH processes associated with the DST still exist. This paper evaluates these uncertainties and provides quantitative estimates of the range of these uncertainties. Of particular interest for the DST are the uncertainties resulting from the unmonitored loss of vapor through an open bulkhead of the test. There was concern that the outcome from the test might have been significantly altered by these losses. Using alternative conceptual models, we illustrate that predicted mean temperatures from the DST are within 1 °C of the measured mean temperatures through the first 2 years of heating. The simulated spatial and temporal evolution of drying and condensation fronts is found to be qualitatively consistent with measured saturation data. Energy and mass balance computation shows that no more than 13% of the input energy is lost because of vapor leaving the test domain through the bulkhead. The change in average saturation in fractures is also relatively small. For a hypothetical situation in which no vapor is allowed to exit through the bulkhead, the simulated average fracture saturation is not qualitatively different enough to be discerned by measured moisture redistribution data. This leads us to conclude that the DST, despite the uncertainties associated with open field testing, has provided an excellent understanding of the TH processes.

Theoretical interpretation of a pronounced permeability scale effect in unsaturated fractured tuff

Numerous single‐hole and cross‐hole pneumatic injection tests have been conducted in unsaturated fractured tuff at the Apache Leap Research Site (ALRS) near Superior, Arizona. Single‐hole tests have yielded values of air permeability at various locations throughout the tested rock volume on a nominal scale of ∼1 m. Cross‐hole tests have yielded equivalent air permeabilities (and air‐filled porosities) for a rock volume characterized by a length scale of several tens of meters. Cross‐hole tests have also provided high‐resolution tomographic estimates of how air permeability (and air‐filled porosity), defined over grid blocks having a length scale of 1 m, vary throughout a similar rock volume. The results have revealed a highly pronounced scale effect in permeability (and porosity) at the ALRS. We examine the extent to which the permeability scale effect is amenable to interpretation by a recent stochastic scaling theory, which treats the rock as a truncated random fractal.

Migration of a water pulse through fractured porous media

Contaminant transport from waste-disposal sites is strongly affected by the presence of fractures and the degree of fracture–matrix interaction. Characterization of potential contaminant plumes at such sites is difficult, both experimentally and numerically. Simulations of water flow through fractured rock were performed to examine the penetration depth of a large pulse of water entering such a system. Construction water traced with lithium bromide was released during the excavation of a tunnel at Yucca Mountain, Nevada, which is located in an unsaturated fractured tuff formation. Modeling of construction-water migration is qualitatively compared with bromide-to-chloride ratio (Br/Cl) data for pore-water salts extracted from drillcores. The influences of local heterogeneities in the fracture network and variations in hydrogeologic parameters were examined by sensitivity analyses and Monte Carlo simulations. The simulation results are qualitatively consistent with the observed Br/Cl signals, although these data may only indicate a minimum penetration depth, and water may have migrated farther through the fracture network.