A multivariate geostatistical methodology to delineate areas of potential interest for future sedimentary gold exploration
Type
article
Identifier
GOOVAERTS, P.; ALBUQUERQUE, M. T. D.; ANTUNES, I. M. H. R. (2016). A multivariate geostatistical methodology to delineate areas of potential interest for future sedimentary gold exploration. Mathematical Geosciences. ISBN: 1874-8961. 48(8), p. 921–939
1874-8961
10.1007/s11004-015-9632-8
Title
A multivariate geostatistical methodology to delineate areas of potential interest for future sedimentary gold exploration
Subject
Sequential indicator simulation
Soft indicators
Cluster analysis
Linear regression
Accuracy plots
Soft indicators
Cluster analysis
Linear regression
Accuracy plots
Date
2019-07-23T15:36:55Z
2019-07-23T15:36:55Z
2016
2019-07-23T15:36:55Z
2016
Description
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.
info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/publishedVersion
Access restrictions
restrictedAccess
http://creativecommons.org/licenses/by-nd/4.0/
http://creativecommons.org/licenses/by-nd/4.0/
Language
eng
Comments