Automatic radioelement anomaly detection
We recognize two types of radioelement anomalies. Consider the two anomalies (A and B) in the figure. The value at anomaly A occurs only once in the dataset – its value is rare. We call this a “spectral anomaly”. In the case of 3-component radioelement data (K, U and Th), spectral anomalies are those areas of the map or profiles where the 3-component radioelement signature (K, U and Th concentrations) are rare. They do not necessarily have anomalous amplitudes - rather, it is the relative concentrations of K, U and Th (i.e. the ratios between the radioelement concentrations) that is anomalous.
Spectral anomalies may, or may not, be important from a mapping or mineral/petroleum exploration perspective. But because they have unusual signatures, they need to be identified and assessed. The value at anomaly B, on the other hand, occurs at several places in the dataset. But it is anomalous with respect to the local background. We call these “point” anomalies. Point anomalies are contextual anomalies – they are anomalous within a local context.
GAMMA_Target is a proprietary gamma-ray processing methodology developed by Minty Geophysics for the detection of radioelement anomalies from airborne gamma-ray spectrometric data. The method detects both spectral and point anomalies and can be applied to either grid or profile data.
GAMMA_Target outputs gamma anomalies to two ESRI shape files – one for spectral anomalies, and one for point anomalies. The anomaly attributes for spectral and point anomalies differ slightly and are listed in the GAMMA_Target Product brochure (see Downloads page).
Users can use the anomaly attributes to selectively display anomalies to assist in their interpretation. When applied to grid data, the anomalies can also be saved as a grid with an index based on the anomaly type (K, U, Th, U+Th etc) as the grid value. An example is shown below.
(data courtesy Geoscience Australia )