RM - Resumos em livros de actas
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- 3D predictive modelling using Artificial Neural Network Analysis in the Neves-Corvo deposits [Resumo]Publication . Batista, Maria Joao; Represas, Patricia; Carvalho, João; Araújo, Vítor; Marques, Fábio; Xavier Matos, João Manuel; Morais, Igor; Albardeiro, Luís; Inverno, Carlos; de Oliveira, Daniel Pipa Soares; Dias, P.ABSTRACT: This study focuses on mineral and lithological vectoring to target new VMS deposits in the Neves-Corvo district, Portugal. Neves-Corvo is a world-class deposit in the Iberian Pyrite Belt, discovered in 1977 by ground gravity survey and one of Europe’s important copper-zinc producers. The deposit is hosted in volcano-sedimentary sequences within a moderately folded and thrust-faulted setting. Previous studies show differences between massive sulphide ores and stockwork ores, especially in trace-element associations. These geochemical particularities, combined with decades of exploration data, make the area well suited for advanced statistical and multivariate analysis. This study will apply an Artificial Neural Network Analysis (ANNA) methodology to the geochemical data, interpolated from boreholes, and a 3D rock density model, obtained by a constrained inversion of gravity data, to identify patterns that other methods might overlook, thereby improving targeting for new VMS mineralization. ANNA can extract trends from complex datasets and perform non-parametric analysis that do not assume a-priori relationships between variables. Therefore, instead of relying on linear or quadratic regressions approaches, this study employs the so-called black box to determine a mathematical function that can adequately approximate the representation of dependent and independent variables. In this study, the number of variables is considerably smaller than the number of training cases available. The training progresses iteratively, using the previous outputs to carefully and progressively adjust the predictors in an iterative manner, allowing for a continuous validation (based in a set of data taken from the total data before training to monitor the performance of the training in each cycle or iteration) of the different scenarios. The geological model was produced, and the drill-hole density database was used to constrain the 3D gravity inversion. All information was laid in a 5mx5mx5m 3D mesh, eliminating the blocks with missing data. The formatted data was then inputted into in STATISTICA’s ANNA software. The variables considered for the first step of ANNA were Cu, Zn, rock density, gravity inversion and Cu/Zn ratio for the Lombador, Neves Graça, Corvo and Zambujal deposits. From the training and validation procedures, it was possible to conclude that using gravity inversion as target and Cu/Zn and rock density as input data produced the more accurate prediction map.
- Abordagem de risco e perigosidade : experiência do projeto Europeu ESPON-HAZARDSPublication . Batista, Maria Joao
- AfricaMaVal : Mineral Potential Mapping Study of European Critical Raw Materials (ECRM) of Africa [Resumo]Publication . Fullgraf, Thomas; Marques Prazeres, Cátia; Gonçalves, Pedro; Callec, Yannick; Fortes, Carla; Represas, Patricia; Vella, Alex; Guillaneau, Jean-Claude; de Oliveira, Daniel Pipa SoaresABSTRACT: The AfricaMaVal project, a 3.5-year initiative coordinated by the French Geological Survey (BRGM), fosters sustainable EU–Africa partnerships in the critical raw materials (CRM) sector. With 18 partners from 11 countries, it promotes responsible mineral sourcing for European industries while supporting Africa’s sustainable development. Work Package 1 (WP1), “Supply Potential,” led by the Portuguese Geological Survey (LNEG), assesses and maps African supply potential for European Critical Raw Materials (ECRM) through a harmonized, INSPIRE-compliant database. BRGM has developed machine learning (ML) algorithms for mineral resource assessment over the past 20 years, applied at scale since 2022. Within WP1, prospectivity maps for selected ECRMs were generated in ten countries, drawing on BRGM datasets, including 1:10M geological and structural maps and over 55,000 mineral occurrences.
- Alluvial Sn and W minerals mapping for mineral resources exploration and research in Segura mining region (Portugal)Publication . Salgueiro, Rute; Grácio, Nuno; Gaspar, Miguel; de Oliveira, Daniel Pipa SoaresSUMÁRIO: Com base em amostras aluvionares em arquivo no LNEG, foi possível conceber mapas de concentração de grãos de cassiterite, volframite e scheelite, para a região mineira de Segura (Castelo Branco) enquadrada na Faixa metalogenética estanho-tungstanífera de Góis-Segura. O padrão de distribuição da concentração de grãos destes minerais de minério de Sn e W, materializa-se em halos concêntricos distintos, em torno do endo/exo-contacto do granito de Segura; estes padrões podem ser correlacionados com distintos eventos metalogenéticos que ocorreram na região, sob controlo estrutural, litológico ou magmático-hidrotermal e em fases distintas, possivelmente com maior sobreposição na parte oeste da mesma. Deste modo, o mapeamento da cassiterite, volframite e scheelite, à escala regional, provou ser útil para ser aplicado à investigação e prospeção de recursos minerais, podendo contribuir para traçar vetores neste tipo de mineralizações de Sn e W.
- An X-ray spectrometry and absorption spectroscopy study of blue-and-white glazes from ancient Chinese porcelains [Abstract]Publication . Figueiredo, M. Ondina; Silva, Teresa; Veiga, JP
- Áreas potenciais de Portugal para recursos minerais do domínio públicoPublication . Carvalho, Jorge; Filipe, Augusto; Gonçalves, Pedro; Lisboa, Jose; Matos, João Xavier; Batista, Maria Joao; Salgueiro, Rute; de Oliveira, Daniel Pipa SoaresSUMMARY: Land-use planning is decisive for granting access to mineral resources. During the work to identify the actions to be taken for preparing the National Strategy for Geological Resources, a map of mineral potential areas for Portugal was produced. It provides the starting point scenario needed for the implementation of a methodology aimed at the delineation of mineral safeguarding areas.
- Argemela, a high-tonnage Sn-Li deposit in Central Portugal [Abstract]Publication . Inverno, Carlos; Ferraz, Paulo J. V.
- ARQUEOLIT: an open access lithotheque in Portugal [Resumo]Publication . Jordão, Patrícia; Soares, Sofia; Silva, Teresa
- Ascertaining the degradation state of ceramic tiles : a preliminary non-destructive step in view of conservation treatments using gamma radiationPublication . Silva, Teresa; Figueiredo, M. Ondina; Prudêncio, Maria Isabel