A multivariate geostatistical methodology to delineate areas of potential interest for future sedimentary gold exploration

Goovaerts, Pierre; Albuquerque, M.T.D.; Antunes, I.M.H.R.

Publication

A multivariate geostatistical methodology to delineate areas of potential interest for future sedimentary gold exploration

2016Journal article

dc.contributor.author	Goovaerts, Pierre
dc.contributor.author	Albuquerque, M.T.D.
dc.contributor.author	Antunes, I.M.H.R.
dc.date.accessioned	2019-07-23T15:36:55Z
dc.date.available	2019-07-23T15:36:55Z
dc.date.issued	2016
dc.description.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.	pt_PT
dc.description.version	info:eu-repo/semantics/publishedVersion	pt_PT
dc.identifier.citation	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	pt_PT
dc.identifier.doi	10.1007/s11004-015-9632-8	pt_PT
dc.identifier.issn	1874-8961
dc.identifier.uri	http://hdl.handle.net/10400.11/6623
dc.language.iso	eng	pt_PT
dc.peerreviewed	yes	pt_PT
dc.relation.publisherversion	https://link.springer.com/article/10.1007%2Fs11004-015-9632-8	pt_PT
dc.rights.uri	http://creativecommons.org/licenses/by-nd/4.0/	pt_PT
dc.subject	Sequential indicator simulation	pt_PT
dc.subject	Soft indicators	pt_PT
dc.subject	Cluster analysis	pt_PT
dc.subject	Linear regression	pt_PT
dc.subject	Accuracy plots	pt_PT
dc.title	A multivariate geostatistical methodology to delineate areas of potential interest for future sedimentary gold exploration	pt_PT
dc.type	journal article
dspace.entity.type	Publication
oaire.citation.endPage	939	pt_PT
oaire.citation.issue	8	pt_PT
oaire.citation.startPage	921	pt_PT
oaire.citation.title	Mathematical Geosciences	pt_PT
oaire.citation.volume	48	pt_PT
person.familyName	Albuquerque
person.familyName	antunes
person.givenName	Maria Teresa
person.givenName	Isabel Margarida
person.identifier.ciencia-id	5A1C-8956-4C0A
person.identifier.ciencia-id	CB1E-FAD2-37D6
person.identifier.orcid	0000-0002-8782-6133
person.identifier.orcid	0000-0003-3456-5926
person.identifier.rid	B-1536-2013
person.identifier.rid	M-1043-2013
person.identifier.scopus-author-id	55507421600
person.identifier.scopus-author-id	6701817085
rcaap.rights	restrictedAccess	pt_PT
rcaap.type	article	pt_PT
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relation.isAuthorOfPublication.latestForDiscovery	e2c2d171-e148-4c23-9cf8-0eb6d810c15e