QUANTITATIVE TEXTURAL MEASURES OF POTENTIAL FIELD ANOMALY DATA

The distribution of anomalies in a gravity or magnetic field dataset displays spatial patterns often distinctive to a lithologic group. These patterns can be described as textures. The texture of a potential field is here defined as a description of the spatial variation of amplitudes in a potential field. A textural measure is the distribution of some measure of the spatial variation in amplitudes of a potential field. Six measures are presented here that can be used to provide a quantitative description of textural variations useful in characterizing potential field responses of lithologic units. The measures are presented as distributions of the measure from a window moving over a chosen textural domain of the data grid. Window sizes depend on interpretation objectives and are of the order of a few km for high resolution densely spaced potential field data to several tens of km for regional scale studies. The measures include the frequency distributions of anomaly amplitude, number of extrema, elongation ratio of ridge and trough anomaly shapes to total of ridges, troughs, peaks, holes and saddle points, mean anomaly strike direction, variability of the anomaly strike directions, and the anomaly surface area (a measure of the overall amplitude). Three field examples are discussed. The first example quantitatively characterizes at regional scale two different areas of the Arctic Ocean aeromagnetic field. A second example shows the estimation of the likely lithology for two concealed mineral target areas using high resolution aeromagnetic data supported by gravity anomaly data. The third example shows some results from ongoing research to characterize basement lithologies for the Great Basin, Basin and Range, and Colorado Plateau provinces of Nevada, Utah, southeastern California, and Arizona. Studies of quantitative comparison of frequency distributions including statistical distance measures and residual difference between distributions are helping to distinguish contributions to the potential field anomaly maps of the basement crust versus later structural and igneous events. Quantitative comparisons of the distributions are necessary because the similarity of two distributions often cannot be judged by visual comparison of the plots of two distributions.