1558
Geometallurgy Program at Vargem Grande Iron Ore Complex,
Brazil: Enhancing Process Reconciliation and Plant Performance
Débora Regina de Sá
Mineral Process Development Management, Vale S.A.
Eliomar Ferreira, Elisabeth Fonseca, Keulla Venya Silva, Matheus Rodrigues
Process Development Management, Vale S.A.
Jéssica Lima
Validation of Routes and Technologies Management, Vale S.A.
ABSTRACT: In mineral processing and mining, advanced methodologies like geometallurgy are essential for
improving efficiency. Geometallurgy integrates geological attributes with metallurgical responses, aiding in
ore body mapping, data management, and performance forecasting. This study consists of a geometallurgical
program at the Vargem Grande Iron Ore Complex in Brazil to enhance process accuracy and plant performance.
Challenges in achieving a 1.5% SiO2 concentrate prompted the program, aggravated by material inclusion from
mines not initially considered. The program addresses low predictability in mineral composition and energy
consumption, proving beneficial in mitigating risks and enhancing efficiency. The study employs sampling,
characterization, bench-scale tests, model generation, and industrial data evaluation. Statistical models applied
in the block models predict mass recovery, metallurgical recovery, energy requirement, and SiO2 content. Spatial
geometallurgical models highlight variability in mass and metallurgical recoveries defining geometallurgical
domains. Validation against industrial results shows a moderate to high correlation, affirming model reliability.
In conclusion, the Geometallurgy Program optimizes mineral processing, production planning, and decision-
making, showcasing its potential for enhancing efficiency in mining operations.
INTRODUCTION
In the dynamic field of mineral processing and min-
ing, the integration of advanced methodologies is cru-
cial for improving overall efficiency and productivity.
Geometallurgy, characterized by its multidisciplinary
nature (Lishchuk and Pettersson, 2021 Campos et al.,
2022), has emerged as a fundamental tool for comprehend-
ing the intricate relationship between geological attributes
and metallurgical responses within ore bodies (Coward
and Dowd, 2015 McKay et al., 2016 Dominy et al.,
2018 Both and Dimitrakopoulos, 2022). Consequently,
various geometallurgical programs have been developed
in the industry to map ore body variations, manage data,
and predict metallurgical performance spatially and tem-
porally. These programs also handle complex geological
information, transferring it to geometallurgical domains
for application in process optimization, production plan-
ning, and business decision-making (Kittler et al., 2011
Lund and Lamberg, 2014 Lishchuk, 2016 Parian, 2017
Both and Dimitrakopoulos, 2023). In alignment with this
Geometallurgy Program at Vargem Grande Iron Ore Complex,
Brazil: Enhancing Process Reconciliation and Plant Performance
Débora Regina de Sá
Mineral Process Development Management, Vale S.A.
Eliomar Ferreira, Elisabeth Fonseca, Keulla Venya Silva, Matheus Rodrigues
Process Development Management, Vale S.A.
Jéssica Lima
Validation of Routes and Technologies Management, Vale S.A.
ABSTRACT: In mineral processing and mining, advanced methodologies like geometallurgy are essential for
improving efficiency. Geometallurgy integrates geological attributes with metallurgical responses, aiding in
ore body mapping, data management, and performance forecasting. This study consists of a geometallurgical
program at the Vargem Grande Iron Ore Complex in Brazil to enhance process accuracy and plant performance.
Challenges in achieving a 1.5% SiO2 concentrate prompted the program, aggravated by material inclusion from
mines not initially considered. The program addresses low predictability in mineral composition and energy
consumption, proving beneficial in mitigating risks and enhancing efficiency. The study employs sampling,
characterization, bench-scale tests, model generation, and industrial data evaluation. Statistical models applied
in the block models predict mass recovery, metallurgical recovery, energy requirement, and SiO2 content. Spatial
geometallurgical models highlight variability in mass and metallurgical recoveries defining geometallurgical
domains. Validation against industrial results shows a moderate to high correlation, affirming model reliability.
In conclusion, the Geometallurgy Program optimizes mineral processing, production planning, and decision-
making, showcasing its potential for enhancing efficiency in mining operations.
INTRODUCTION
In the dynamic field of mineral processing and min-
ing, the integration of advanced methodologies is cru-
cial for improving overall efficiency and productivity.
Geometallurgy, characterized by its multidisciplinary
nature (Lishchuk and Pettersson, 2021 Campos et al.,
2022), has emerged as a fundamental tool for comprehend-
ing the intricate relationship between geological attributes
and metallurgical responses within ore bodies (Coward
and Dowd, 2015 McKay et al., 2016 Dominy et al.,
2018 Both and Dimitrakopoulos, 2022). Consequently,
various geometallurgical programs have been developed
in the industry to map ore body variations, manage data,
and predict metallurgical performance spatially and tem-
porally. These programs also handle complex geological
information, transferring it to geometallurgical domains
for application in process optimization, production plan-
ning, and business decision-making (Kittler et al., 2011
Lund and Lamberg, 2014 Lishchuk, 2016 Parian, 2017
Both and Dimitrakopoulos, 2023). In alignment with this