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4 Conceptual and Numerical Model Development
Pages 46-67

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From page 46...
... This report will refer to such conceptual models as hydrostructural models. A site conceptual model developed early in site management and engineering can guide characterization, design, and choice of detailed numerical modeling approach appropriate for a given site, project goals, and available resources.
From page 47...
... Hydrostructural models are not constrained by the same assumptions as specific numerical models (e.g., gridding and grid resolution, equivalent continuum concepts, or simplified porosities)
From page 48...
... are relevant to transport or storage, and therefore whether they should be conceptualized as part of the effective rock matrix or fractures. The full range of storage and flow porosities needs to be considered and assigned in light of the information needed for forecast of contaminant transport and design of a remediation process.
From page 49...
... Similar to fractured carbonates, with both bed-local coordinate system fractures, and superposed tectonic and structural fractures. Rock matrix permeability is generally low enough to inhibit flow such that smaller fractures may form a major portion of the rock mass permeability and porosity.
From page 50...
... • Significant conductive and flow barrier features defined explicitly to describe flow path ways and rock matrix storage. The fault itself can be modeled as a fault core and a damage zone.
From page 51...
... rock matrix blocks. FIGURE Microstructural model approach showing progressively more detailed structures and eventually the predomi nant flow path and transport and storage processes at micro scale.
From page 52...
... and multiple-porosity fractured rock. Blocks of rock matrix may be of different porosity than the fractures surrounding them, and the shape and size of the matrix blocks affect diffusive, advective, geochemical, and other types of exchanges between fracture and matrix.
From page 53...
... Table 4.2 lists the types of data that could be integrated to determine various hydrostructural elements associated with fractures and rock matrix. Hydrostructural elements related to boundary conditions do not appear on the table because boundary conditions do not conveniently fit into a table of this type.
From page 54...
... Functional relationships between hydrodynamic property and geometric properties Geomechanical Strength Strength Shear and normal stiffness Deformability In situ stress In situ stress Thermal Thermal deformability Thermal deformability Functional relationships between Functional relationships hydrodynamic properties and temperature between hydrodynamic Heat capacity property and temperature Heat capacity Geochemical Porosity measures Porosity measures Diffusion measures Diffusion measures Sorption/retention measures Sorption/retention measures Fluid/rock interactions: dissolution/precipitation reactions Fracture Parameterization Fracture parameterization within hydrostructural models is most useful for many applications if based on site microstructural models, spatial patterns, hydrodynamic properties, and geochemical and biologic properties (e.g., retention, natural attenuation, and those related to mitigation)
From page 55...
... Fracture Roughness and Infilling Fracture roughness and infilling are often neglected fracture characteristics. Under any given set of boundary conditions, contaminant travel time, retention, and reactive surface areas depend on whether flow is effectively one dimensional (e.g., a pipe)
From page 56...
... Boundary Condition Parameterization Hydrostructural model boundary conditions describe hydrogeologic features such as water levels, faults, end of aquifers, and recharge or discharge zones that affect local hydraulic conditions. Boundary conditions describe the characteristics assigned to the boundaries or edges of a numerical model that represent regional hydraulic behaviors, as well as the parameters assigned at the beginning of a numerical model test to represent background conditions.
From page 57...
... A good analysis approach is to determine first the questions to answer, then to develop efficient and effective ways to answer them using the site hydrostructural model and knowledge about available simple and complex analysis tools. Simplified analyses can determine the most sensitive assumptions and parameters in the system so that the most resources can be devoted to quantify them.
From page 58...
... . Solute transport calculation tools should include the ability to analyze matrix diffusion processes, surface sorption, and rock matrix sorption without representing fractured rock as a single porosity system.
From page 59...
... Immobile Zone Interactions Mass transfer rates and storage volumes for mobile and immobile porosities can be estimated with one-dimensional approximate calculation approaches. The approaches can therefore be used to better estimate where contaminants are likely stored, to estimate the timescales of various remediation processes, and to assess whether more complex and resource-intensive modeling and analysis is warranted (e.g., single porosity/single permeability, single permeability/dual porosity, dual porosity/dual permeability, or discrete fracture network [DFN]
From page 60...
... are powerful and underused tools. They can be used to examine fracture network connectivity and boundary condition issues that, in turn, control the flow system, interaction between mobile and immobile porosities, and boundary conditions such as flow barrier faults and connected high-porosity aquifers.
From page 61...
... DFN models are available through commercial, government, and academic sources, but are not used as commonly as continuum models even though they offer advantages for modeling fractured rock system. There is considerable room to improve the ability of even state-of-the-art numerical models to explicitly describe flow and transport in fractured low permeability systems.
From page 62...
... A DFN approach in which 1D elements are used to implement the Moreno and fracture geometry. The rock matrix may be implemented as a CN model Neretnieks, 1993 or using an EPM approach.
From page 63...
... By upscaling some properties, numerical models can focus on other hydraulically important hydrostructural properties and features. When using an EPM, consideration must be given to how the selected parameters relate to the geometric and hydrodynamic properties of the underlying fractures and rock matrix, and how simplification to a single-porosity EPM model might avoid misleading results.
From page 64...
... Formal numerical model analysis applied to fractured rock systems quantitatively relates the hydrostructural conceptualization, the equations used to represent the conceptualization, the algorithms used to solve the equations in a numerical model, the model input parameters, and model outputs. It is important not only that numerical models adequately solve the equations that represent the hydrostructural conceptualization, but also that tools that quantify model uncertainties are applied so that decisions informed by numerical models can be informed by quantified uncertainties.
From page 65...
... This provides a quantitative measure of sensitivity of output to input. However, complex numerical models with large numbers of degrees of freedom often make it impractical to carry out an analysis of each of the systematic changes made to model input.
From page 66...
... Quantifying these errors and uncertainties ensures appropriate application of numerical models and the conclusions drawn from them. Just as examining the sensitivity of a model to input parameters can guide subsequent model development, quantifying the uncertainties that arise during the modeling process can guide interpretation of model output.
From page 67...
... The use of oversimplified or inappropriate numerical models, however, can lead to inadequate or incorrect results. Hydrogeologists that receive proper training that allows them to develop appropriate conceptual models and then apply inexpensive initial scoping calculations to bound system behavior will be able to make more informed decisions regarding data needs and more complex modeling.


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