Generation of aquifer heterogeneity maps using two-dimensional spectral texture segmentation techniques

Numerical models that solve the governing equations for subsurface fluid fl ow and transport require detailed quantitative maps of spatially variable h ydraulic properties. Recently, there has been great interest in,methods tha t can map the spatial variability of hydraulic properties such as porosity and hydraulic conductivity (permeability). Presently, only limited data on natural permeability spatial structure are available. These data are often based on extensive discrete sampling in outcrops or boreholes. Then methods are used to interpolate between data values to map aquifer heterogeneity I nterpolation methods often,mask critical local or intermediate scale hetero geneities. As sediment texture is directly correlated with many hydraulic p roperties we developed two new texture segmentation algorithms based on a s pace-local two-dimensional wavenumber spectral method known as the S-Transf orm. Existing texture segmentation algorithms could not delineate the subtl e and continuous texture variations that exist in natural sediments. The S- Transform algorithms successfully delineated geologic structures and grain size patterns in photographs of outcrops in a glacial fluvial deposit; thus , no interpolation methods were required to produce continuous two-dimensio nal maps of texture facies. The S-Transform method is robust and is insensi tive to changes in light intensity and moisture variations. This makes the algorithm particularly applicable to natural sedimentary outcrops. The effe ctiveness of our methods are tested by correlating measured relative grain sizes in the images with actual grain size measurements taken from the sedi mentary outcrops.