Application of nonlinear geostatistical indicator kriging in lithological categorization of an iron ore deposit

Nonlinear geostatistics is commonly used in ore grade estimation and seldom used in lithological characterization. Categorization of lithological units is essential in ore grade estimation, and this can be done based on the lithological information obtained from drill-hole data. In general, a conven...

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Veröffentlicht in:	Current Science. - Current Science Association. - 108(2015), 3, Seite 413-421
1. Verfasser:	Rao, V. Kameshwara (VerfasserIn)
Weitere Verfasser:	Narayana, A. C.
Format:	Online-Aufsatz
Sprache:	English
Veröffentlicht:	2015
Zugriff auf das übergeordnete Werk:	Current Science
Schlagworte:	Physical sciences Business Mathematics


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245	1	0	\|a Application of nonlinear geostatistical indicator kriging in lithological categorization of an iron ore deposit
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520			\|a Nonlinear geostatistics is commonly used in ore grade estimation and seldom used in lithological characterization. Categorization of lithological units is essential in ore grade estimation, and this can be done based on the lithological information obtained from drill-hole data. In general, a conventional classification method was used to delineate different lithological units using geological cross-sections derived from borehole logs. In this study, we suggest an approach based on geostatistical nonlinear indicator kriging (IK) to delineate different lithological units of an iron ore deposit. Iron ore has been broadly grouped into eight litho units based on physical and chemical characteristics of the core samples recovered from drill holes during exploration stage. IK helps in the construction of litho maps for different benches of the mining deposit. Fe grades were estimated using ordinary kriging model and grade maps were prepared for all the benches of the deposit. A comparison was done between the grades of each litho type resulting from the two methods, i.e. IK model and geological cross-sectional model and the relative merits of the IK approach have also briefly discussed.
540			\|a © 2015 Current Science Association
650		4	\|a Physical sciences \|x Earth sciences \|x Geology \|x Petroleum geology \|x Lithology
650		4	\|a Physical sciences \|x Earth sciences \|x Geology
650		4	\|a Physical sciences \|x Earth sciences \|x Geography \|x Geomorphology \|x Rocks \|x Sedimentary rocks \|x Clastic sedimentary rocks \|x Mudrocks \|x Shales
650		4	\|a Physical sciences \|x Earth sciences \|x Geography \|x Applied geography \|x Geostatistics \|x Kriging
650		4	\|a Physical sciences \|x Earth sciences \|x Geology \|x Mineralogy \|x Minerals \|x Ferrous minerals
650		4	\|a Physical sciences \|x Earth sciences \|x Geography \|x Geodesy \|x Cartography \|x Maps
650		4	\|a Physical sciences \|x Earth sciences \|x Geology \|x Mineralogy \|x Minerals \|x Ferrous minerals \|x Hematite
650		4	\|a Business \|x Industry \|x Industrial sectors \|x Extractive industries \|x Mining industries \|x Mining \|x Metals mining \|x Iron mining
650		4	\|a Mathematics \|x Applied mathematics \|x Statistics \|x Applied statistics \|x Inferential statistics \|x Statistical estimation
650		4	\|a Mathematics \|x Applied mathematics \|x Statistics \|x Applied statistics \|x Statistical models \|x Parametric models \|x RESEARCH COMMUNICATIONS
655		4	\|a research-article
700	1		\|a Narayana, A. C. \|e verfasserin \|4 aut
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773	1	8	\|g volume:108 \|g year:2015 \|g number:3 \|g pages:413-421
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