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Projeto de investigação
Sustainable mineral resources by utilizing new Exploration technologies
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3D Constrained Gravity Inversion and TEM, Seismic Reflection and Drill-Hole Analysis for New Target Generation in the Neves-Corvo VMS Mine Region, Iberian Pyrite Belt
Publication . Marques, Fábio; Dias, Pedro; Carvalho, João; Represas, Patricia; Spicer, Bill; Araújo, Vítor; Matos, João Xavier; Morais, Igor; Albardeiro, Luís; Sousa, Pedro; Pacheco, Nelson; Gonçalves, Pedro; Barbosa, Diego
ABSTRACT: Located in the Iberian pyrite belt, the Neves-Corvo mine is a world-class massive sulfide deposit and the largest operating mine in Portugal with underground mining down to 1000 m depth focused on massive and stockwork Cu, Zn, Pb rich ores. Gravimetric data have had a leading role in the discovery of the seven known deposits, together with time-domain electromagnetic (TEM) ground data. In this work, we present the results of a 3D constrained gravity inversion carried out with legacy ground gravity data. The 3D gravity inversions were carried out using an updated density database containing approximately 142,000 measurements. A recently constructed 3D geological model based on reprocessed 2D seismic reflection, 3D seismic, TEM and updated geology from detailed surface mapping and drill-hole data, was used to constrain the inversions. The results show multiple high-density anomalies that may indicate the presence of mineralization at depth. These anomalies were therefore cross-checked with holes previously drilled. Approximately 97% of more than 1000 available surface drill-holes located on or at a distance of less than 200 m from the high-density anomalies intersected mineralization. However, gravity anomalies have been drilled in the past and particularly dense black shales or rhyolitic/gabbroic rocks have been intersected. To increase the success of future drilling, gravimetric anomalies have been correlated spatially with high-conductivity TEM zones and strong-amplitude seismic reflections, because igneous rocks usually present weak-to-moderate conductivity and a massive column of black shales presents a seismic signature quite different from that of mineralization. We concluded that some of these locations represent high-quality targets to consider following up with drilling and further exploration.
3D reflection seismic imaging of volcanogenic massive sulphides at Neves-Corvo, Portugal
Publication . Donoso, George; MALEHMIR, Alireza; Carvalho, João; Araújo, Vítor
ABSTRACT: Three-dimensional reflection seismic data from the Neves-Corvo area, southern Portugal, were reprocessed with the main objective of improving the seismic signature of the Lombador and Semblana volcanogenic massive sulphide deposits. The sensitivity for choosing adequate parameters for targeted imaging, even during the pre-processing stage, such as common-depth point binning size, was studied in detail before the main processing work began helping to optimize bin size parameters; preliminary stacking results from this analysis presented severe acquisition footprint, and seismic targets were not clearly identifiable. Processing results using pre-stack dip move-out and post-stack migration methods show strong moderate to steeply dipping reflections. Several of the observed reflections can be correlated with known lithological contacts, some of which are interpreted to originate from the Semblana and Lombador deposits. Despite the mixed signal-to-noise ratio, the seismic cube reveals both shallow and deep three-dimensional structures, allowing to account for the deposits' lateral extension beyond the capabilities of two-dimensional seismic imaging alone. Given the data processing approach taken it was possible to distinguish strong diffraction patterns, interpreted as originating from faults and edges of the Lombador deposit, illustrating the usefulness of diffraction patterns for better interpretation of geological features in hard-rock environments.
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.
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Entidade financiadora
European Commission
Programa de financiamento
H2020
Número da atribuição
775971