Stochastic study of solute transport in a nonstationary medium

A Lagrangian stochastic approach is applied to develop a method of moment for solute transport in a physically and chemically nonstationary medium. Stochastic governing equations for mean solute flux and solute covariance are analytically obtained in the first-order accuracy of log conductivity and/or chemical sorption variances and solved numerically using the finite-difference method. The developed method, the numerical method of moments (NMM), is used to predict radionuclide solute transport processes in the saturated zone below the Yucca Mountain project area. The mean, variance, and upper bound of the radionuclide mass flux through a control plane 5 km downstream of the footprint of the repository are calculated. According to their chemical sorption capacities, the various radionuclear chemicals are grouped as nonreactive, weakly sorbing, and strongly sorbing chemicals. The NMM method is used to study their transport processes and influence factors. To verify the method of moments, a Monte Carlo simulation is conducted for nonreactive chemical transport. Results indicate the results from the two methods are consistent, but the NMM method is computationally more efficient than the Monte Carlo method. This study adds to the ongoing debate in the literature on the effect of heterogeneity on solute transport prediction, especially on prediction uncertainty, by showing that the standard derivation of solute flux is larger than the mean solute flux even when the hydraulic conductivity within each geological layer is mild. This study provides a method that may become an efficient calculation tool for many environmental projects.     

Characterization of mixing and spreading in a bounded stratified medium

Matheron and de Marsily [Matheron M, de Marsily G. Is the transport in porous media always diffusive? A counter-example. Water Resour Res 1980;16:901–17] studied transport in a perfectly stratified infinite medium as an idealized aquifer model. They observed superdiffusive solute spreading quantified by anomalous increase of the apparent longitudinal dispersion coefficient with the square root of time. Here, we investigate solute transport in a vertically bounded stratified random medium. Unlike for the infinite medium at asymptotically long times, disorder-induced mixing and spreading is uniquely quantified by a constant Taylor dispersion coefficient. Using a stochastic modeling approach we study the effective mixing and spreading dynamics at pre-asymptotic times in terms of effective average transport coefficients. The latter are defined on the basis of local moments, i.e., moments of the transport Green function. We investigate the impact of the position of the initial plume and the initial plume size on the (highly anomalous) pre-asymptotic effective spreading and mixing dynamics for single realizations and in average. Effectively, the system “remembers” its initial state, the effective transport coefficients show so-called memory effects, which disappear after the solute has sampled the full vertical extent of the medium. We study the impact of the intrinsic non-ergodicity of the confined medium on the validity of the stochastic modeling approach and study in this context the transition from the finite to the infinite medium.     

A numerical method of moments for solute transport in physically and chemically nonstationary formations: linear equilibrium sorption with random K<Subscript>d</Subscript>

A Lagrangian perturbation method is applied to develop a method of moments for solute flux through a three-dimensional nonstationary flow field. The flow nonstationarity stems from medium nonstationarity and internal and external boundaries of the study domain. The solute flux is described as a space-time process where time refers to the solute flux breakthrough through a control plane (CP) at some distance downstream of the solute source and space refers to the transverse displacement distribution at the CP. The analytically derived moment equations for solute transport in a nonstationarity flow field are too complicated to solve analytically, a numerical finite difference method is implemented to obtain the solutions. This approach combines the stochastic model with the flexibility of the numerical method to boundary and initial conditions. The developed method is applied to study the effects of heterogeneity and nonstationarity of the hydraulic conductivity and chemical sorption coefficient on solute transport. The study results indicate all these factors will significantly influence the mean and variance of solute flux.     

Block-effective macrodispersion for numerical simulations of sorbing solute transport in heterogeneous porous formations

Heterogeneity is prevalent in aquifers and has an enormous impact on contaminant transport in groundwater. Numerical simulations are an effective way to deal with heterogeneity directly by assigning different hydraulic property values to each numerical grid block. Because hydraulic properties vary on different scales, but they cannot be sampled exhaustively and the number of numerical grid blocks is limited by computational considerations, the dispersive effects of unmodeled heterogeneity need to be accounted for. Dispersion tensors can be used to model the dispersion caused by unmodeled heterogeneity. The concept of block-effective macrodispersion tensors for modeling the effects of small-scale variability on solute transport introduced by Rubin et al. [Rubin Y, Sun A, Maxwell R, Bellin A. The concept of block-effective macrodispersivity and a unified approach for grid-scale- and plume-scale-dependent transport. J Fluid Mech 1999;395:161–80] is extended in this paper for use with reactive solutes. The tensors are derived for reactive solutes with spatially variable retardation factors and for solutes experiencing spatially uniform rate-limited sorption. The longitudinal block-effective macrodispersion coefficient is largest for perfect negative correlation between the log-hydraulic conductivity and the retardation factor. Because dispersion tensors, as they are usually implemented in numerical simulations, produce symmetric spreading, the applicability of the concept depends on the portion of the plume asymmetry caused by small-scale variability. The presented results show that the concept is applicable for rate-limited sorption for block sizes of one and two integral scales.     

Intra-catchment variability in solute response an east devon example

Modifications to the land use of a small catchment, including clearance, cultivation and an increase in drainage density, are shown to have influenced a number of solute characteristics. Contrasts are drawn between three source areas; an unmodified subcatchment draining an area of mixed deciduous woodland, and a tile drain system and drainage ditch receiving water from cultivated areas. Not only are the modifications identified in terms of mean solute concentrations, but it is also shown that a change in land use alters the interaction between independent hydrological and meteorological variables, and solute response. A tentative explanation is provided for long term solute behaviour in relation to a number of biological geochemical and hydrological controls.     

A numerical Eulerian method of moment for solute transport in a nonstationary dual-porosity medium

An Eulerian perturbation approach was applied to develop a method of moment for solute transport in a nonstationary, fractured medium. The conceptualized fractured medium is described through a dual-porosity model. Stochastic governing equations for mean concentration and concentration covariance were analytically derived to the first-order accuracy of log-conductivity variance and solved with a numerical method––a finite difference method. The developed method is called a numerical Eulerian method of moment (NEMM). This method was compared with the stationary transport theory [Water Resour. Res. 36(7) (2000) 1665] for predicting mean concentration and its spatial moments. The comparison indicated that the two methods matched very well in predicting first and second spatial moments. NEMM solutions were also compared with Monte Carlo simulations for solute transport in stationary fractured media. The results of the two methods were consistent for calculating small log conductivity variance. The theory was then used to study effects of various parameters and nonstationarity of the medium on flow and transport processes. Results indicated that medium nonstationarity would significantly influence the solute transport process. The nonstationary transport theory relaxes many assumptions adopted in stationary theories and paves the way for applying the NEMM to many environmental projects, especially in analyzing uncertainty of solute transport.     

Quantifying geological uncertainty for flow and transport modeling in multi-modal heterogeneous formations

In this work, we address the problem of characterizing the heterogeneity and uncertainty of hydraulic properties for complex geological settings. Hereby, we distinguish between two scales of heterogeneity, namely the hydrofacies structure and the intrafacies variability of the hydraulic properties. We employ multiple-point geostatistics to characterize the hydrofacies architecture. The multiple-point statistics are borrowed from a training image that is designed to reflect the prior geological conceptualization. The intrafacies variability of the hydraulic properties is represented using conventional two-point correlation methods, more precisely, spatial covariance models under a multi-Gaussian spatial law. We address the different levels and sources of uncertainty in characterizing the subsurface heterogeneity, and explore their effect on groundwater flow and transport predictions. Typically, uncertainty is assessed by way of many images, termed realizations, of a fixed statistical model. However, in many cases, sampling from a fixed stochastic model does not adequately represent the space of uncertainty. It neglects the uncertainty related to the selection of the stochastic model and the estimation of its input parameters. We acknowledge the uncertainty inherent in the definition of the prior conceptual model of aquifer architecture and in the estimation of global statistics, anisotropy, and correlation scales. Spatial bootstrap is used to assess the uncertainty of the unknown statistical parameters. As an illustrative example, we employ a synthetic field that represents a fluvial setting consisting of an interconnected network of channel sands embedded within finer-grained floodplain material. For this highly non-stationary setting we quantify the groundwater flow and transport model prediction uncertainty for various levels of hydrogeological uncertainty. Results indicate the importance of accurately describing the facies geometry, especially for transport predictions.     

Radar experiments in isotropic and anisotropic geological formations (granite and schists)1

In order to understand various aspects of radar wave propagation, a survey of electromagnetic wave behaviour relative to the geological characteristics of the formations prospected was undertaken. The sites chosen for the tests were a granite quarry and an underground schist working. By investigating an electrically resistive isotropic site and a conductive anisotropic site, it was demonstrated that non-conventional use of a radar system (antennae raised, various orientations of the transmitter/receiver, etc.) could improve data quality, and could allow information other than reflector depth to be collected (volume scattering intensity, isotropy, etc.). By studying wave propagation velocities, we underlined the difficulties encountered in establishing a velocity versus depth law, despite recourse to seismic data processing, such as NMO corrections. The results of field experiments, complemented by laboratory measurements of dielectric permittivities, clearly showed anisotropy effects: in the case of a path that is perpendicular to the schistosity plane, an electromagnetic wave propagates more slowly and is more attenuated than a wave parallel to the schistosity plane.     

盆地超压地层识别方法--以四川盆地通南巴构造带为例

在四川盆地通南巴构造带,首先以井芯、录井资料和钻井泥浆比重资料为约束条件,利用泥岩段声波测井资料建立区域“正常压实趋势线”;然后用精细速度处理获得的地震层速度剖面减去区域“正常压实趋势线”建立速度差值剖面,速度差值剖面上的异常低速带定性指示了地层超压范围;再采用速度一压力变换技术,建立压力系数剖面,定量分析地层超压,地层压力计算结果与实际钻井采用的泥浆比重较好吻合,说明利用地球物理资料、钻井资料及地质资料不但可以定性识别超压地层,而且可以定量预测地层压力;对不同压力封存箱的认识有助于分析地层含油气性延展方向,指导下一步勘探部署。     

Numerical method of moments for solute transport in a nonstationary flow field conditioned on hydraulic conductivity and head measurements

The unconditional stochastic studies on groundwater flow and solute transport in a nonstationary conductivity field show that the standard deviations of the hydraulic head and solute flux are very large in comparison with their mean values (Zhang et al. in Water Resour Res 36:2107–2120, 2000; Wu et al. in J Hydrol 275:208–228, 2003; Hu et al. in Adv Water Resour 26:513–531, 2003). In this study, we develop a numerical method of moments conditioning on measurements of hydraulic conductivity and head to reduce the variances of the head and the solute flux. A Lagrangian perturbation method is applied to develop the framework for solute transport in a nonstationary flow field. Since analytically derived moments equations are too complicated to solve analytically, a numerical finite difference method is implemented to obtain the solutions. Instead of using an unconditional conductivity field as an input to calculate groundwater velocity, we combine a geostatistical method and a method of moment for flow to conditionally simulate the distributions of head and velocity based on the measurements of hydraulic conductivity and head at some points. The developed theory is applied in several case studies to investigate the influences of the measurements of hydraulic conductivity and/or the hydraulic head on the variances of the predictive head and the solute flux in nonstationary flow fields. The study results show that the conditional calculation will significantly reduce the head variance. Since the hydraulic head measurement points are treated as the interior boundary (Dirichlet boundary) conditions, conditioning on both the hydraulic conductivity and the head measurements is much better than conditioning only on conductivity measurements for reduction of head variance. However, for solute flux, variance reduction by the conditional study is not so significant.     

Equivalent diffusion coefficient of clay-rich geological formations: comparison between numerical and analytical estimates

Laboratory experiments in rock samples collected from clay-rich formations indicate that the effective molecular diffusion coefficient (D) is a heterogeneous and anisotropic property. Since laboratory measurements of D are representative of a very small volume, upscaling is necessary in order to incorporate these data in large-scale numerical models of diffusive transport. In this work we address the problem of the estimating the equivalent diffusion coefficient (D _eq ), in terms of total diffusive flux, in a three-dimensional domain characterized by a heterogeneous and anisotropic spatial distribution of D. D _eq was estimated from the results of steady-state diffusive transport simulations through several realizations of the D field. The ensemble averages of D _eq from fields with different degrees of heterogeneity and anisotropy were then compared with estimates from analytical upscaling expressions based on stochastic as well as power-averaging approaches. These expressions are largely based on similar expressions developed for calculating the effective hydraulic conductivity in heterogeneous and anisotropic domains. Comparisons showed that stochastic expressions provide accurate estimates of D _eq only for fields characterized by low heterogeneity. Within the range of heterogeneity and anisotropy considered, our results showed that a power-averaging expression is very accurate in predicting D _eq especially when the parameter p _i is estimated through fitting of the numerical results. Nonetheless, the relationship between this parameter and the anisotropy ratio is linear.     

Investigating dynamic mechanisms of geological phenomena using methodology of computational geosciences: An example of equal-distant mineralization in a fault

This paper presents a research methodology associated with approximately a decade old computa- tional geosciences. To demonstrate how it can be used to investigate the dynamic mechanisms of geological phenomenon, we use as an example the equal-distant distribution of gold deposits in a three-dimensional permeable fault within the Yilgarn Craton, Western Australia. The related numerical results demonstrate that: (1) convective pore-fluid flow in fluid-saturated porous media is the control- ling dynamic mechanism leading to the equal-distant distribution of gold deposits along the fault; (2) the main characteristic of the new methodology is to change the traditionally used empirical, descrip- tive and qualitative methodology into the fundamentally scientific principles based predictive and quantitative methodology. Thus, this new methodology provides a modern scientific research tool for investigating the dynamic mechanisms associated with observed geological phenomena in nature.     

Models of sub-grid variability in numerical simulations of solute transport in heterogeneous porous formations: three-dimensional flow and effect of pore-scale dispersion

Modeling transport of contaminants in the earths subsurface relies on numerical solutions over grids with blocks larger than Darcys scale. The hydraulic conductivity is homogenized over the grid blocks and the plumes spreading is reduced as a consequence of the wiped-out variability. To compensate for this loss Rubin et al. (1999) proposed to augment mixing by block-effective dispersion coefficients, and Rubin et al. (2003) showed, by means of two dimensional simulations, how this concept can be applied in practice. In this paper, we present new solutions of the block-effective dispersion tensor for an axisymmetric exponential covariance model. In addition, we discuss the influence of pore-scale dispersion in both two- and three-dimensional applications.     

Heat flow and spreading rate in back-arc basins: the example of the Tyrrhenian Sea

The results of calculations using geothermal data, the spreading rate and the lithospheric rhickness in the Tyrrhenian Sea are given. A co-ordination of the calculations with the geological structure of the region is made.     

The exceptional magnitude and intensity of the Toba eruption,sumatra: An example of the use of deep-sea tephra layers as a geological tool

The eruption of Toba (75,000 years BP), Sumatra, is the largest magnitude eruption documented from the Quaternary. The eruption produced the largest-known caldera the dimensions of which are 100 × 30 km and which is surrounded by rhyolitic ignimbrite covering an area of over 20,000 km². The associated deep-sea tephra layer is found in piston cores in the north-eastern Indian Ocean covering a minimum area of 5 × 10⁶ km². We have investigated the thickness, grain size and texture of the Toba deep-sea tephra layer in order to demonstrate the use of deep-sea tephra layers as a volcanological tool. The exceptional magnitude and intensity of the Toba eruption is demonstrated by comparison of these data with the deep-sea tephra layers associated with the eruptions of the Campanian ignimbrite, Italy and of Santorini, Greece in Minoan time. The volume of ignimbrite and distal tephra fall deposit produced in the Toba eruption are comparable, a total of at least 1000 km³ of dense rhyolitic magma. In contrast the volume of dense magma produced by the Campanian and Santorini eruptions are approximately 70 and 13 km³ respectively. Thickness versus distance data on the three deep-sea tephra layers show that eruptions of smaller magnitude than Santorini are unlikely to be preserved as distinct tephra layers in most deep-sea cores. In proximal cores all three tephra layers show two distinct units: a lower coarse-grained unit and an upper fine-grained unit. We interpret the lower unit as a plinian deposit and the upper unit as a co-ignimbrite ash-fall deposit, indicating two major eruptive phases. The Toba tephra layer is coarser both in maximum and median grain size than the Campanian and Santorini layers at a given distance from source. These data are interpreted to indicate a very high cruption column, estimated to be at least 45 km. We have applied a method for estimating the duration of the Toba eruption from the style of graded-bedding in deep-sea tephra layers. Studies of two cores yield estimates of 9 and 14 days. The eruption column height and duration estimates both indicate an average volume discharge rate of approximately 10⁶ m³/sec. The Toba eruption therefore was not only of exceptional magnitude, but also of exceptional intensity.     

An evaluation of conditioning data for solute transport prediction

The large and diverse body of subsurface characterization data generated at a field research site near Oyster, Virginia, provides a unique opportunity to test the impact of conditioning data of various types on predictions of flow and transport. Bromide breakthrough curves (BTCs) were measured during a forced-gradient local-scale injection experiment conducted in 1999. Observed BTCs are available at 140 sampling points in a three-dimensional array within the transport domain. A detailed three-dimensional numerical model is used to simulate breakthrough curves at the same locations as the observed BTCs under varying assumptions regarding the character of hydraulic conductivity spatial distributions, and variable amounts and types of conditioning data. We present comparative results of six cases ranging from simple (deterministic homogeneous models) to complex (stochastic indicator simulation conditioned to cross-borehole geophysical observations). Quantitative measures of model goodness-of-fit are presented. The results show that conditioning to a large number of small-scale measurements does not significantly improve model predictions, and may lead to biased or overly confident predictions. However, conditioning to geophysical interpretations with larger spatial support significantly improves the accuracy and precision of model predictions. In all cases, the effects of model error appear to be significant in relation to parameter uncertainty.