A regional geochemical map interpolated from point data, usually sampled in surficial media such as stream sediments or lake sediments, may contain a large amount of information critical for mineral exploration and environmental studies. The geochemical map is, however, not ‘ready-to-use’ for such tasks as the determination of a local ‘anomaly’ or the characterization of a regional trend of one or more chemical elements as may be required for the purpose of mineral resource prediction. This becomes possible only after the map has been clearly divided into different components. Fractal filtering, a recently developed technique for decomposing a map or image into different components, helps to separate the anomaly from background or to extract other meaningful patterns from the geochemical map using both frequency and spatial information.
The fractal filters are formed by applying the fractal concentration-area model to the power spectrum of the processed geochemical field. They often constitute a group of irregularly shaped filters in the frequency domain that can separate the domain of wave numbers into distinct regions, each with a power spectrum following a similar power-law or fractal property. The corresponding patterns of the separate components are obtained after transformation back to the spatial domain.
The fractal filter can be applied to decompose the original geochemical field into a set of map components with distinct scaling ranges and anisotropy. The analysis of relationships among these decomposed maps can provide useful information for the interpretation and evaluation of anomalies or trends.
This paper briefly introduces the theory behind the fractal filtering technique. A case study of regional geochemical data of lake sediments from western Meguma Terrain, Southern Nova Scotia, Canada, is used to illustrate application of this technique to process the regional geochemical maps of the study area for the prediction of the turbidite-hosted gold deposits.