Using Wavelet Analysis to Identify Dominant Scales of Subsurface Flow and Transport
R. M. Neupauer, Xiaofei Qi, Z. Wengrovius · World Environmental and Water Resources Congress 2007 · 2007
Wavelet analysis involves an integral transform of, for example, a permeability data set, using wavelet as the kernel of the transform. A wavelet is a function that is non-zero only over a finite region; therefore the wavelet transform analyzes only a subset of the data set. The wavelet is shifted to analyze different subsets of the data set, and it is scaled to analyze different scales of the data set. Using wavelet analysis, dominant scales of permeability can be identified in a statistically heterogeneous porous medium. We generate sets of random permeability fields with different spatial correlation lengths, and we run numerical flow and solute transport simulations using these random fields. We show preliminary results of using wavelet analysis to analyze the dominant scales in the random permeability fields. The results of wavelet analysis will be used to identify relationships between dominant scales of heterogeneity and scales controlling the transport of contaminants.