Upscaling of conductivity of heterogeneous formations: General approach and application to isotropic media

The numerical simulation of flow through heterogeneous formations requires the assignment of the conductivity value to each numerical block. The conductivity is subjected to uncertainty and is modeled as a stationary random space function. In this study a methodology is proposed to relate the statistical moments of the block conductivity to the given moments of the continuously distributed conductivity and to the size of the numerical blocks. After formulating the necessary conditions to be satisfied by the flow in the upscaled medium, it is found that they are obeyed if the mean and the two-point covariance of the space averaged energy disspation function over numerical elements in the two media, of point value and of upscaled conductivity, are identical. This general approach leads to a systematic upscaling procedure for uniform average flow in an unbounded domain. It yields the statistical moments of upscaled logconductivity that depend only on those of the original one and on the size and shape of the numerical elements.The approach is applied to formations of isotropic heterogeneity and to isotropic partition elements. After a general discussion based on dimensional analysis, the procedure is illustrated by using a first-order approximation in the logconductivity variance. The upscaled logconductivity moments (mean, two-point covariance) are computed for two and three dimensional flows, isotropic heterogeneous media and elements of circular or spherical shape. The asymptotic cases of elements of small size, which preserve the point value conductivity structure on one hand, and of large blocks for which the medium can be replaced by one of deterministic effective properties, on the other hand, are analyzed in detail. The results can be used in order to generate the conductivity of numerical elements in Monte Carlo simulations.

[1]  R. M. Srivastava,et al.  Geostatistical characterization of groundwater flow parameters in a simulated aquifer , 1991 .

[2]  Allan L. Gutjahr,et al.  Stochastic analysis of spatial variability in subsurface flows: 1. Comparison of one‐ and three‐dimensional flows , 1978 .

[3]  Yoram Rubin,et al.  A stochastic approach to the problem of upscaling of conductivity in disordered media: Theory and unconditional numerical simulations , 1990 .

[4]  Gedeon Dagan,et al.  Upscaling of permeability of anisotropic heterogeneous formations: 1. The general framework , 1993 .

[5]  G. Dagan Stochastic modeling of groundwater flow by unconditional and conditional probabilities: 1. Conditional simulation and the direct problem , 1982 .

[6]  A. Desbarats Spatial averaging of transmissivity in heterogeneous fields with flow toward a well , 1992 .

[7]  Lynn W. Gelhar,et al.  Stochastic subsurface hydrology from theory to applications , 1986 .

[8]  Eric F. Wood,et al.  Comment on “Effective groundwater model parameter values: Influence of spatial variability of hydraulic conductivity, leakance, and recharge” by J. J. Gómez‐Hernández and S. M. Gorelick , 1990 .

[9]  G. Matheron Éléments pour une théorie des milieux poreux , 1967 .

[10]  Joel Koplik,et al.  Creeping flow in two-dimensional networks , 1982, Journal of Fluid Mechanics.

[11]  C. Axness,et al.  Three‐dimensional stochastic analysis of macrodispersion in aquifers , 1983 .

[12]  G. Dagan Statistical Theory of Groundwater Flow and Transport: Pore to Laboratory, Laboratory to Formation, and Formation to Regional Scale , 1986 .

[13]  Mark J. Beran,et al.  Statistical Continuum Theories , 1968 .

[14]  Gedeon Dagan,et al.  Analysis of flow through heterogeneous random aquifers by the method of embedding matrix: 1. Steady flow , 1981 .

[15]  A. Desbarats,et al.  Numerical estimation of effective permeability in sand-shale formations , 1987 .

[16]  Numerical simulation of unstable displacement in porous media , 1979 .

[17]  H. S. Price,et al.  Flow in Heterogeneous Porous Media , 1961 .

[18]  A. Dykhne Conductivity of a Two-dimensional Two-phase System , 1971 .

[19]  R. Allan Freeze,et al.  Stochastic analysis of steady state groundwater flow in a bounded domain: 2. Two‐dimensional simulations , 1979 .

[20]  P. Indelman,et al.  Upscaling of permeability of anisotropic heterogeneous formations: 3. Applications , 1993 .

[21]  P. King The use of renormalization for calculating effective permeability , 1989 .

[22]  G. Dagan Flow and transport in porous formations , 1989 .

[23]  G. Dagan,et al.  Upscaling of permeability of anisotropic heterogeneous formations: 2. General structure and small perturbation analysis , 1993 .

[24]  Peter K. Kitanidis,et al.  Analysis of the Spatial Structure of Properties of Selected Aquifers , 1985 .

[25]  J. P. Delhomme,et al.  Spatial variability and uncertainty in groundwater flow parameters: A geostatistical approach , 1979 .

[26]  Erik H. Vanmarcke,et al.  Random Fields: Analysis and Synthesis. , 1985 .

[27]  J. R. Macmillan,et al.  Stochastic analysis of spatial variability in subsurface flows: 2. Evaluation and application , 1978 .

[28]  Steven M. Gorelick,et al.  Effective groundwater model parameter values: Influence of spatial variability of hydraulic conductivity, leakance, and recharge , 1989 .

[29]  R. Ababou,et al.  Numerical simulation of three-dimensional saturated flow in randomly heterogeneous porous media , 1989 .

[30]  R. Freeze A stochastic‐conceptual analysis of one‐dimensional groundwater flow in nonuniform homogeneous media , 1975 .