A simple adaptable data fusion methodology for geophysical exploration

We present a simple and adaptive method of data fusion using grey-scale grids for general geophysical exploration. The methodology relies upon: (1) understanding the physical property variations that might be associated with the mineral exploration target, and (2) applying appropriate (forward or inverse) grey-scaling to each input dataset so that before addition of the grids the anomalous patterns all express the phenomena of interest in the same sense (i.e. all positive anomalies). If the resulting fused dataset has a Gaussian population distribution then a linear grey-scale is applied to the data within the 95% (2σ) confidence interval; if it is non-Gaussian then the linear grey scale is applied to the entire dataset. The methodology has been applied to very low frequency (VLF), aeromagnetic and radiometric data measured during the 1980s over the Hemlo disseminated lode-gold deposit. The resulting fused data derived from our methodology produces a coherent region of anomalous geophysical response that is coincident in location and geometry to the surficial extent of the known mineralized zone of the deposit. Integration of multi-sensor response has the added advantage of significantly reducing the number of false-targets. Further, this method also illustrates the continued benefits that can be obtained from re-evaluation of older data.