A Multivariate Geostatistical Methodology to Delineate Areas of Potential Interest for Future Sedimentary Gold Exploration

Abstract

This paper describes a multivariate geostatistical methodology to delineate areas of potential interest for future sedimentary gold exploration, with an application to an abandoned sedimentary gold mining region in Portugal. The main challenge was the existence of only a dozen gold measurements confined to the grounds of the old gold mines, which precluded the application of traditional interpolation techniques, such as cokriging. The analysis could, however, capitalize on 376 stream sediment samples that were analyzed for twenty two elements. Gold (Au) was first predicted at all 376 locations using linear regression (R2=0.798) and four metals (Fe, As, Sn and W), which are known to be mostly associated with the local gold’s paragenesis. One hundred realizations of the spatial distribution of gold content were generated using sequential indicator simulation and a soft indicator coding of regression estimates, to supplement the hard indicator coding of gold measurements. Each simulated map then underwent a local cluster analysis to identify significant aggregates of low or high values. The one hundred classified maps were processed to derive the most likely classification of each simulated node and the associated probability of occurrence. Examining the distribution of the hot-spots and cold-spots reveals a clear enrichment in Au along the Erges River downstream from the old sedimentary mineralization.

Characterizing the Spatial Scales of Extreme Daily Precipitation in the United States

“…We use indicator semivariograms to quantify the length scale of extreme precipitation using our binary p90 dataset. Indicator semivariograms have been used in previous studies to spatially interpolate the probability of the presence of a threshold variable using indicator kriging (e.g., Berezowski et al 2016;Goovaerts et al 2016;Haberlandt 2007). However, in our study, we use indicator semivariogram methods to directly compute the length scales of extreme precipitation, without kriging the binary variable.…”

“…The theory and calculation of indicator semivariograms is described in detail by Goovaerts (1997) and applied in many studies to understand the spatial structure of environmental variables (e.g., Berezowski et al 2016;Goovaerts et al 2016;Haberlandt 2007). In the following subsections, we first describe the methods for selecting the data used in the calculation of indicator semivariograms (including the moving neighborhood method) so that we capture any seasonal and regional variations in p90 length scales.…”

“…In this study, we focus on the practical range a, with which we represent the length scale of p90 daily precipitation (Goovaerts 1997;Haberlandt 2007;Fig. 3c).…”

Spatial environmental risk evaluation of potential toxic elements in stream sediments

“…Stream sediment also remains a common geochemical approach used for regional gold exploration (Fletcher 1997;Darwish and Poellmann 2010;Goovaerts et al 2014Goovaerts et al , 2016. The exploration of sedimentary gold (alluvial) has occurred in distinct mineralized areas and is linked up with different genetic deposits (Townley et al 2003;Chapman and Mortensen 2006;McInnes et al 2008).…”

“…Geochemical mapping, historically used to enhance the interpretation of metal distribution patterns in mineral exploration, has recently become essential in environmental studies (Plant et al 2001;Antunes and Albuquerque 2013;Antunes et al 2014;Goovaerts et al 2016). Understanding the geochemical processes that control precipitation and dissolution of secondary minerals in abandoned or active mines is crucial for the elaboration of models to predict the environmental impact of such sites (Gieré et al 2003).…”