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A new method is proposed to estimate porosity within heterogeneous karst aquifers using techniques borrowed from remote sensing and geospatial analysis. High-resolution borehole images are classified into binary images consisting of pixels designated as either rock matrix or pore space. Two-dimensional porosity is calculated by summing the total area occupied by pores within a rectangular sampling window placed over the binary image. Small sampling windows quantify the heterogeneous nature of porosity distribution in the aquifer, whereas large windows provide an estimate of overall porosity. Applying this procedure to imagery taken from the Biscayne aquifer of south Florida yields a porosity of ∼40%, considerably higher than the ∼28% mean porosity measured in the laboratory from recovered core samples. Geospatial analysis, using geographic information systems, may provide the more reliable estimate, because it incorporates large solution cavities and conduits captured by the borehole image yet not recovered in core samples. The representative elementary area (REA) is estimated from borehole images by varying the size of sampling windows around prominent conduits and evaluating the change in porosity as a function of window size. Average porosities decrease systematically with increasing sampling window size, eventually converging to a constant value of ∼40% for a window height of ∼5 m. The representative elementary volume (REV) for porosity in this section of the Biscayne aquifer is thus estimated as ∼125 m3.

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