Anisotropy, lacunarity, and upscaled conductivity and its autocovariance in multiscale random fields with truncated power variograms

Abstract

Abstract. It has been shown by Di Fededco and Neuman [1997, 1998a, b] that observed multiscale behaviors of subsurface fluid flow and transport variables can be explained within the context of a unified stochastic framework, which views hydraulic conductivity as a random fractal characterized by a power variogram. Such a random field is statistically nonhomogeneous but possesses homogeneous spatial increments. Di Federico and Neuman [1997] have demonstrated that the power variogram and associated spectra of a statistically isotropic fractal field can be constructed as a weigh. ted integral from zero to infinity (an infinite hierarchy) of exponential or Gaussian variograms and spectra of mutually uncorrelated fields (modes) that are homogeneous and isotropic. We show in this paper that the same holds true when the field and its constituent modes are statistically anisotropic, provided the ratios between principal integral (spatial correlation) scales are the same for all modes. We then analyze the effect of filtering out (truncating) modes of low, high, and intermediate spatial frequency from this infinite hierarchy in the real and spectral domains. A low-frequency cutoff renders the truncated hierarchy homogeneous. The integral scales of the lowest-and highest-frequency cutoff modes are related to length scales of the sampling window (domain) and data support (sample volume), respectively. Taking the former to be proportional to the latter renders expressions for the integral scale and variance of the truncated field dependent on window and support scale (in a manner previously shown to be consistent with observations in the isotropic case). It also allows (in principle) bridging across scales at a specific locale, as well as among locales, by adopting either site-specific or generalized variogram parameters. The introduction of intermediate cutoffs allows us to account, in a straightforward manner, for lacunarity due to gaps in the multiscale hierarchy created by the absence of modes associated with discrete ranges of scales (for example, where textural and structural features are associated with distinct ranges of scale, such as fractures having discrete ranges of trace length and density, which dissect the rock into matrix blocks having corresponding ranges of sizes). We explore mathematically and graphically the effects that anisotropy and lacunarity have on the integral scale, variance, covariance, an d spectra of a truncated fractal field. We then develop an expression for the equivalent hydraulic conductivity of a box-shaped porous block, embedded within a multiscale log hydraulic conductivity field, under mean-uniform flow. The block is larger than the support scale of the field but is smaller than a surrounding sampling window. Consequently, its equivalent hydraulic conductivity is a random variable whose variance and spatial autocorrelation function, conditioned on a known mean value of support-scale conductivity across the window, are given explicitly by our multiscale theory.

Scaling analysis of hydraulic conductivity and porosity on a sandy medium of an unconfined aquifer reproduced in the laboratory

“…In addition to the experimental approach cited above, some authors proposed theoretical methods to generate the k variation with the scale, utilizing statistical procedures (Di Federico and Neuman, 1997;Di Federico et al, 1999) or, in other circumstances, utilizing the fractal theory (Davy et al, 2002).…”

Distribution of hydraulic conductivity in single scale anisotropy

“…However, such a large number of experiments have reported an increase in K with increasing scale [8][9][10][11][12][13][14][15][16][17][18][19][20] that it becomes necessary to find an explanation for such effects. Some researchers have sought to find theoretical explanations of such an effect [21][22][23][24]. Some of these experimental results are contested by other researchers, based on a critique of either the analysis or the experimental conditions [25][26][27].…”

Effects of intraborehole flow on groundwater age distribution

“…Estimates of regional-scale transport characteristics must incorporate smaller-scale variability into models of the system (some examples of upscaling methods include Gelhar and Axness 1983;Li et al 1994;Haggerty and Gorelick 1995;Berkowitz et al 2000;Haggerty et al 2000). Studies have shown that accurate upscaled transport modeling often requires detailed knowledge of the magnitude and the structure of small-scale heterogeneity (e.g., Goltz and Roberts 1987;Li et al 1994;Di Federico et al 1999;LaBolle and Fogg 2001;Becker and Shapiro 2001;Guswa and Freyberg 2002;Zinn and Harvey 2003;Liu et al 2004;Zinn et al 2004).…”