A spatial reconnaissance survey for gold exploration in a schist belt (original) (raw)
Ore Geology Reviews, 2020
There has always been a need for new methodologies and research to improve the decision-making process at the early stages of mineral exploration. This article presents a novel approach to integrating geodata in support of a mineral systems-based spatial analysis of orogenic gold deposits in the Rio das Velhas Greenstone Belt (RVGB), Quadrilátero Ferrífero Province, Brazil. The gold mineralization in the RVGB is spatially associated with thrust faults and shear zones and mainly hosted by iron-rich rocks such as mafic-ultramafic sequences and banded iron formations. To best represent the targeting elements of this mineral system spatially, a knowledge-based fuzzy logic method was employed to map the expressions of the gold depositional processes at the province (1:500,000), district (1:100,000) and camp (1:50,000) scales. At each scale, multivariate statistical techniques served to enhance multiple geological, geophysical, and geochemical datasets and extract from these data spatial proxies of the gold depositional processes. The results of this multi-scale predictive analysis were as follows: The first, province-scale model (M1) identified the entire gold prospective tract and the areas within it that may be of greatest relevance to future exploration. The second, district-scale model (M2) identified the different gold camps within the prospective tract and mapped the areas of gold favorability in a more detailed manner. The third, camp-scale model (M3) identified areas that, based on the current knowledge and distribution of high resolution geodata, are the most favorable whilst also being small enough as to permit target testing using conventional mineral exploration tools such as geophysics, geochemistry and/or drilling. The results obtained from our predictive models were validated by comparing them against the known gold occurrences using ROC (receiver operating characteristics) curves and AUC (area under the curve) graphs. According to these validations, model M1 scored an accuracy of 93.38%, whereas models M2 and M3 scored accuracies of 88.31% and 93.38%, respectively. A key observation made in the course of this study is that the gold prospective area as predicted by models M1, M2 and M3 varies according to the scale of the analysis. A novel factor in our approach is that we aimed assess the targeting criteria and spatial datasets that underpin them according to their spatial resolution and presented the results in form of integrated maps. In addition, the tools developed in this study have the capacity to reduce the cost of direct detection technologies regarding the transition from broad regional to camp scale at the early stages of mineral exploration, where the most initial decisions in search and area reduction are critical.
Research Journal of Applied Sciences, Engineering and Technology, 2016
Sian Goldfields Limited (SGL) recently reexamined its concession by integrating data in a GIS environment for the improvement of the mapping of the local geology as well as for delineating potential gold targets. Data employed included geochemical, topographic, geological and aerial photographic information. The geochemical data included 5660 soil samples collected over a terrain underlain by six different lithologies namely, rhyolites, greenstones, sheared greenstones, phyllites, sandstones and granites. The various lithologies and their boundaries were obtained from the shaded relief map derived from the topographic information whilst "ground truthing" confirmed and established the other geological contacts. The updated geology map generated from the geosciences data was superimposed on the soil gold geochemical plot. The integration of these datasets in the form of maps resulted in the easy definition of anomalous gold targets. The targets were delineated using background and threshold values of 30 ppb and 50 ppb respectively. The integration model approach portrayed many of the geological boundaries to have relations with mineralization. The use of the MapInfo-Discover GIS markedly aided to ascertain the geological contacts in areas where outcrops were uncommon. The re-analysis of the remote-sensed data and the ground truthing showed the clear contact between the Birimian system and the Voltaian units at the north eastern side of the concession. The integration of this information with soil geochemical gold results highlighted the most prospective gold targets. It is recommended that the granite-sheared greenstones/sheared greenstone-massive greenstones contacts and areas with defined soil anomalies should be subjected to further exploration works.
Data mining is a promising new tool in mineral exploration. Here, we combined data-mining procedures with spatial prediction modeling for gold exploration targeting in the Buhweju area in southwestern Uganda. It was employed in a data-rich context of unavoidably partly redundant and correlated information that offered challenges in extracting significant relationships. Our study utilized a database of co-registered digital maps related to gold mineralization. It comprised Landsat TM, Shuttle Radar Topographic Mission (SRTM), and geophysical (radiometric and magnetic) datasets for geological and structural mapping. The locations of 15 orogenic gold deposits and 87 gold occurrences were obtained from the Geological Survey of Uganda database. These were considered direct evidence of the presence of gold mineralization. The geological and geophysical settings at the gold deposit/ occurrences locations were based on geological units as host rocks, contacts, and structural elements, together with continuous field values of geophysics, radiometry, and other remotely sensed imagery. A gold exploration targeting proposition (T p) was defined as: ''That a point p within the study area contains a gold deposit given the presence of spatial evidence.'' All outstanding combinations of spatial evidence were obtained using empirical likelihood ratios. With a data-mining strategy, the ratios were filtered and modeled to identify stronger spatial associations, to rank the study area according to the likelihood of future discoveries, to represent ranking quality, to estimate associated uncertainty, and to select prospective target areas. The empirical likelihood ratios facilitated a transparent strategy for generating prediction patterns and extracting small prospective target areas with higher likelihood of discovery and lower-ranking uncertainty. Conclusions are provided on the knowledge extraction for prospectivity with further data and the challenges of reducing the arbitrariness of decisional steps.
Journal of Applied Geology
Western Java is a part of the Sunda Banda magmatic belt. This belt is well known to be host for several gold deposits in Indonesia, the distribution of 107 Au occurrences in this area was examined in terms of spatial association with various geological phenomena. The goal of this project is to use GIS to conduct weights of evidence (WofE) model for gold mineralization in West Java, Indonesia. A Geographic Information System (GIS) is a computer system for capturing, storing, querying, analyzing, and displaying geospatial data and weight of evidence method is one of the most important datadriven methods for mapping in GIS. The method is a probability based on technique for mapping mineral potential using the spatial distribution of known mineral occurrences. Therefore this method is very useful for gold potential mapping. There are six evidences maps such as NE–SW lineaments NW–SE Lineament, host rocks, heat sources, clay alteration and limonitic alteration, have been combined using a...
International journal of innovation and scientific research, 2019
This work aims to identify potentials sites suitable for mining research through the use of Geographic Information Systems (GIS). The method of pair comparisons by the hierarchical analysis process developed was used to the ponderation of criteria to generate different thematic maps. By the technic of complete aggregation based on the ponderation, these different maps were combined to produce the indicator map to result in the synthesis map. The map of potential sites for the auriferous mineralization which is a synthesis map reveals that 10% (350Km² or 3500ha) of the study area is moderately mineralized, 30% (1050km² or 1050ha) is mineralized and 13% (455Km² or 45500ha) is very mineralized. This map is of great importance for possible auriferous explorations. It highlights the auriferous potentialities of Katiola department.
Remote Sensing and Geographic Information System (GIS) have played an active role in mineral exploration by helping in the identification or discovery of new gold deposits in most part of the world such as Spain, Nova Scotia (Canada) and Egypt. Different authors have used Remote Sensing and GIS in exploring minerals deposits. Birim North District of the Eastern Region of Ghana is one of the gold-mineralized districts but there is no gold potential map covering the whole district. This research work was aimed at producing a gold potential map covering the whole of Birim North District through the use of Remote Sensing and GIS technique. The Landsat Enhanced Thematic Mapper (ETM+) image of the Birim North was processed by applying the clay-mineral ratio (Band 5 to Band 7) and the principal component analysis. The result was further processed to obtain the alteration map of Birim North District which represented the altered rocks associated with gold-mineralization. The Aeromagnetic image of the same area was enhanced by using the Edge Detection Directional Filter and later digitized manually on-screen to produce the lineament map of Birim North District. These results obtained from the Remote Sensing processes were integrated into GIS environment with other geospatial datasets such as the soil geochemical data and geophysical data. The Arc-weight of evidence was used as the spatial data integration model in the prediction of the potential gold areas. A total of 250 known gold deposits was used, 180 were used as training samples and 70 were used for the validation. The results obtained from the research work indicated that the best predictors of the new gold deposits were the soil geochemical data, geophysical data and the lineament. The alteration was the least predictor. The gold potential map demarcates 158 km2 (i.e., 32%) of the total of 497 km2 as favourable for the occurences of the gold deposits within the study area. The gold potential map also has a success rate of 88% (i.e, the percentage of the training deposits or points in the predicted favourable gold deposits zones) and a prediction rate of 83% (i.e, the percentage of the validation deposits or points in the predicted favourable gold deposits areas). Many of the mining communities and Newmont Ghana Gold limited mine area were found in the areas associated with relative higher posterior probabilities.
Journal of African Earth Sciences, 2018
Linear and nonlinear geostatistic is commonly used in ore grade estimation and seldom used in Geographical Information System (GIS) technology. In this study, we suggest an approach based on geostatistic linear ordinary kriging (OK) and Geographical Information System (GIS) techniques to investigate the spatial distribution of alluvial gold content, mineralized and gangue layers thicknesses from 73 pits at the Ngoura-Colomines area with the aim to determine controlling factors for the spatial distribution of mineralization and delineate the most prospective area for primary gold mineralization. Gold content varies between 0.1 and 4.6 g/m 3 and has been broadly grouped into three statistical classes. These classes have been spatially subdivided into nine zones using ordinary kriging model based on physical and topographical characteristics. Both mineralized and barren layer thicknesses show randomly spatial distribution, and there is no correlation between these parameters and the gold content. This approach has shown that the Ngoura-Colomines area is located in a large shear zone compatible with the Riedel fault system composed of P and P 0 fractures oriented NE-SW and NNE-SSW respectively; E-W trending R fractures and R 0 fractures with NW-SE trends that could have contributed significantly to the establishment of this gold mineralization. The combined OK model and GIS analysis have led to the delineation of Colomines, Tissongo, Madubal and Boutou villages as the most prospective areas for the exploration of primary gold deposit in the study area.
2021
The Zuru Schist Belt is one of the gold-bearing schist belts in northwestern Nigeria. The gold mineralisation is mainly associated with NE-trending shear zones and is hosted in veins of quartz, quartz-tourmaline and quartz-feldspar. In this study, the spatial pattern of gold and associated elements was identified and delineated through statistical analysis of trace element geochemical data. Statistical analyses including spearman correlation, principal component analysis and hierarchical cluster analysis were applied on the geochemical data to decipher and interpret multi-element association related with gold mineralisation. Spearman correlation revealed significant positive correlation amongst Co, Mn, Fe, V, Ni and Zn (>0.70), while Au has moderate correlation with Ag, Bi and Cu (>0.30). Based on principal component analysis and hierarchical cluster analysis, three element associations can be recognised: (a) Zn-Ni-Co-Mn-Fe-V, (b) Au-Ag-Bi-Pb and (c) Zn-U-Th-Sr-La-Ba. The firs...
Earth Sciences, 2020
Mineral Prospectivity Mapping (MPM) is a multi-step process that ranks a promising target area for more exploration. This is achieved by integrating multiple geoscience datasets using mathematical tools to determine spatial relationships with known mineral occurrences in a GIS environment to produce mineral prospectivity map. The study area lies within Latitudes 9° 00ʹ N to 9° 15ʹ N and 6° 45ʹ to 7° 00ʹ E and is underlain by rocks belonging to the Basement Complex of Nigeria which include migmatitc gneiss, schist, granite and alluvium. The datasets used in this study consist of aeromagnetic, aeroradiometric, structural, satellite remote sensing and geological datasets. Published geologic map of the Sheet 185 Paiko SE was used to extract lithologic and structural information. Landsat images were used to delineate hydroxyl and iron-oxide alterations to identify linear structures and prospective zones at regional scales. ASTER images were used to extract mineral indices of the OH-bearing minerals including alunite, kaolinite, muscovite and montmorillonite to separate mineralized parts of the alteration zones. Aeromagnetic data were interpreted and derivative maps of First Vertical Derivative, Tilt derivative and Analytic signal were used to map magnetic lineaments and other structural attributes while the aeroradiometric dataset was used to map hydrothermally altered zones. These processed datasets were then integrated using Fuzzy Logic modelling to produce a final mineral prospectivity map of the area. The result of the model accurately predicted known deposits and highlighted areas where further detailed exploration may be conducted.
Mineralium Deposita, 2009
In the southwestern part of the Ashanti Belt, the results of fractal and Fry analyses of the spatial pattern of 51 known mines/prospects of (mostly lode) gold deposits and the results of analysis of their spatial associations with faults and fault intersections suggest different predominant structural controls on lode gold mineralisation at local and district scales. Intersections of NNE-and NW-trending faults were likely predominantly involved in local-scale structural controls on lode gold mineralisation, whilst NNEtrending faults were likely predominantly involved in district-scale structural controls on lode gold mineralisation. The results of the spatial analyses facilitate the conceptualisation and selection of spatial evidence layers for lode gold prospectivity mapping in the study area. The applications of the derived map of lode gold prospectivity and a map of radial density of spatially coherent lode gold mines/ prospects results in a one-level prediction of 37 undiscovered lode gold prospects. The applications of quantified radial density fractal dimensions of the spatial pattern of spatially coherent lode gold mines/prospects result in an estimate of 40 undiscovered lode gold prospects. The study concludes finally that analysis of the spatial pattern of discovered mineral deposits is the key to a strong link between mineral prospectivity mapping and assessment of undiscovered mineral deposits.