Behnam Sadeghi from EarthByte Group has published a new paper in journal “Ore Geology Reviews”, based on his PhD thesis.
In this research, to explore the VMS Cu deposits throughout Sweden a novel multifractal model of concentration-distance from centroids (C-DC) has been developed and applied to the till data provided by the Geological Survey of Sweden. In this model, the effects of ice movements in glaciers and the distance between the samples and known relevant mineral deposits have been taken into consideration. This model is in a frequency framework, but based on several scenarios to achieve a more efficient classified model in terms of geostatistical uncertainty.
Various fractal models have been implemented to separate populations and characterize spatial distributions in geochemical data derived from regional mapping programs. This study compares the conventional number-size with a proposed concentration-distance from centroids (C-DC) fractal model to detect geochemically anomalous populations. These models have been applied to centered log-ratio transformed data of VMS-style mineralization related element concentrations in till from a low-density national survey conducted across Sweden. The C-DC model has been applied to the distance between till samples and centroids of geological sub-provinces containing a number of VMS-style deposits, and is derived from the concentration-distance (C-D) approach originally developed using a radial-density (R-D) model. The efficiencies of the models in detecting a multivariate geochemical response to known mineralization are compared using a variant of the overall accuracy matrix. The C-DC model provides accuracy of classification similar to the N-S model. Therefore, Monte Carlo simulation was applied to quantify uncertainties in setting of population thresholds using the two fractal models. It demonstrated greater efficiency of the C-DC model.
Full link to this paper is: https://www.sciencedirect.com/science/article/abs/pii/S0169136821003280
169 total views, 1 views today