An evaluation of interpolation methodologies for generating three-dimensional hydraulic property distributions from measured data

The process of attempting to model ground-water systems requires a good understanding of the spatial variation of aquifer hydraulic properties. The capabilities of the more recent innovative flowmeters such as the electromagnetic and heat pulse flowmeters provide the sensitivity to measure ambient flows and pump-induced flows. These flowmeters provide the measurements of pump-induced vertical flows which are analyzed to obtain vertical variations in horizontal hydraulic conductivity, K(z). With discrete areal K-values, K(x, y), and vertical profiles of K, provided by multiwell testing, the essential elements are present to produce a three-dimensional hydraulic conductivity field. The advent of these new flow measuring devices has contributed much to the motivation behind this paper. This paper presents the results of applying deterministic and stochastic methodology to the three-dimensional interpolation of hydraulic properties, specifically, hydraulic conductivity, K. Three of the approaches applied in this paper are deterministic in nature, inverse-distance weighting, inverse-distance-squared weighting, and ordinary kriging, while the fourth is a stochastic approach based on self-affine fractals. All of the methods are applied to measured data collected from 14 wells at a site in the United States near Mobile, Alabama. The three-dimensional K-distributions generated by each of the methods are used as inputs to an advective based transport model with the resulting model output compared to a two-well tracer study run previously at the same site