Integração de dados aerogeofísicos e de sensores remotos aplicada à prospecção no Distrito Ferrífero Nova Aurora, Minas Gerais
Ano de defesa: | 2015 |
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Autor(a) principal: | |
Orientador(a): | |
Banca de defesa: | |
Tipo de documento: | Dissertação |
Tipo de acesso: | Acesso aberto |
Idioma: | por |
Instituição de defesa: |
Universidade Federal de Minas Gerais
UFMG |
Programa de Pós-Graduação: |
Não Informado pela instituição
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Departamento: |
Não Informado pela instituição
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País: |
Não Informado pela instituição
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Palavras-chave em Português: | |
Link de acesso: | http://hdl.handle.net/1843/BUBD-9Y7HEF |
Resumo: | The Nova Aurora Iron District (Northern Minas Gerais State, Brazil) comprises iron deposits associated with metadiamictites of the Neoproterozoic Macaúbas Group. These deposits, included in the Riacho Poções Member, Nova Aurora Formation, consist of hematite and/or magnetite matrix-rich metadiamictites, which iron content range from 13 to 60 wt% Fe. They show irregular distribution and are mostly covered by the thick lateritic soils exposed on extensive plateaus, hiding their real lateral dimensions. This paper presents a geological, geophysical and remote sensing integrated study with the aim to support mineral prospecting from regional to local scale. The regional model show scattered favorable areas, with several high density concentration of probable iron ore deposits. In the local model, including field and borehole data, the Euler Deconvolution reveals magnetic source depths in agreement with the ore body thickness shown by boreholecontrolled geological sections. This local integrated model also fits well with the iron ore outcrops visited in the field. The very extensive lateritic covers mask the lateral dimensions of the iron formations in gammaspectrometry and Landsat 8 images, since these sensors mainly reflect the surface response of ground material. Magnetometry data may reveal the most favorable targets for iron ore prospecting, although it lacks enough detail for more specific studies. Integrated models may better constrain prospecting targets, even in the extensive plateau areas. |