In this study, predictive models that characterize gold potential zones within the Josephine Prospecting Licence (PL) Area of Northwestern Ghana have been created by data-driven methods comprising ...frequency ratio and information value. These predictive models were evaluated using known locations of gold (Au) occurrence datasets and compared to each other. The mineral prospectivity models (MPMs) of gold occurrence areas within the Josephine PL Area were constructed by determining the spatial correlation between known locations of Au occurrences and eight mineralization related factors. The locations of these known Au occurrences, which characterize regions of anomalously high Au geochemical concentration and regions of previous or ongoing artisanal mining operations were identified by using geographic positioning systems (GPS). Eight mineralization related factors (geoscientific thematic layers) over the entire study area composed of analytic signal, lineament density, uranium-thorium ratio, uranium, potassium-thorium ratio, potassium, reduction-to-equator and geology were used to generate the MPMs. The predictive capacity of each of the MPMs generated was determined by employing the area under the receiver operating characteristics curve (AUC). The AUC score obtained for the predictive models produced based on the information value and the frequency ratio approaches were respectively 0.794 and 0.815. The AUC scores generated indicate that the MPMs produced are good predictive models (with an AUC greater than 0.7) and can therefore assist in narrowing down the highly prospective zones of mineral occurrences within the study area. However, the overall predictive potential of the frequency ratio approach was better than the model produced by the information value approach.
The southern part of the West African Craton includes the Baoulé-Mossi Domain, the world’s premier Paleoproterozoic gold province (~10,000 metric ton gold endowment). Structural, metamorphic, and ...geochronological data suggest gold mineralisation occurred during three episodes that span much of the Eoeburnean and Eburnean orogenic cycles. Eoeburnean orogenic and rare skarn-hosted gold deposits formed between ca. 2200 and 2135 Ma during repeated episodes of volcanism, plutonism, and shortening, which thickened the Paleoproterozoic crust. Early Eburnean orogenic and placer gold deposits formed between ca. 2110 and 2095 Ma during inversion, metamorphism, and subsequent oblique shortening of intra-orogenic basins filled after ca. 2135 Ma. This episode of mineralisation terminated when the Baoulé-Mossi Domain docked with the Archean Kénéma-Man Domain at ca. 2095 Ma. Late Eburnean orogenic and less common intrusion-related gold deposits formed between ca. 2095 and 2060 Ma during strike-slip to oblique-slip tectonics, post-collisional high-K plutonism and crustal reworking across the western and southern Baoulé-Mossi Domain. Eoeburnean gold deposits include ca. 10 % of the gold endowment of the Baoulé-Mossi Domain, whereas the Early Eburnean and Late Eburnean deposits include ca. 50–70% and 20–40%, respectively. Here, we highlight the favourable confluence of accretion-collision tectonics, involving juvenile crust formation as well as protracted magmatic, metamorphic, and deformation histories that resulted in diachronous gold events spread over at least 100 myr throughout the Baoulé-Mossi Domain.
Contrary to what is currently known, archetypal zircon samples from gneisses and intrusive leucogranites in the Palaeoproterozoic Suhum Basin, SE Ghana, suggest the involvement of Neoarchean crustal ...material in the formation of the Palaeoproterozoic juvenile crust of the Birimian terranes in Ghana. The zircons dated using U–Pb dating methods and subjected to Lu–Hf isotopic analysis suggest that crustal‐forming events from different contemporaneous magmatic episodes within the Suhum Basin took place over a time interval of 139 Ma from 2224 to 2085 Ma. Whole‐rock Lu–Hf data obtained for the gneissic and leucogranitic rocks gave model ages (T
DM2
) ranging from 2789 to 2456 Ma with ɛHf(t) values ranging from −1.1 to +5.4. These model ages imply that the magmas that formed these rocks were sourced from the early Palaeoproterozoic juvenile mantle with substantial Neoarchean crustal reworking.
Geospatial modeling of mineral prospective regions is essential, owing to its significant contribution towards the development and economic gains of many mineral-endowed countries including, Ghana. ...Thus, the primary objective of this study is to delineate mineral potential zones in the Gomoa Area of Ghana's southern Kibi-Winneba belt in order to supplement mineral resources in Ghana's existing mineral prospective zones. To achieve the aforementioned objective, researchers generated predictive models characterising gold mineralisation prospects within the study area by employing machine learning techniques comprising support vector machines (SVM) and naive bayes (NB) classifiers on mineral-related conditioning factors. These mineral-related factors (geoscientific thematic layers) were sourced from geophysical, remote sensing, and geological datasets. The resulting mineral prospective models (MPM) produced based on SVM and NB classifiers were exhibited in binary classes (prospective and non-prospective zones). Regions delineated as prospective zones within the study area were, respectively estimated to cover an area extent of 181.62 km2 and 296.02 km2 for the SVM-derived MPM and NB-derived MPM and analogously characterise 22.07% and 35.97% of the study area. The ability of these two models to predict was determined using the area under the receiver operating characteristic curve (AUC). The AUC scores obtained for the SVM-derived MPM and the NB-derived MPM were, respectively, 0.90 and 0.83. Outputs of the AUC scores generally indicate that the two models produced have good accuracy, although the SVM-derived MPM performed better than that of the NB-derived MPM. Thus, the machine learning-based mineral prospectivity models produced in this study are worthy outputs to guide the planning of detailed mineral exploration surveys within the study area.
•Gold mineralisation prospects of the Gomoa Area of the southern Kibi-Winneba belt.•Mineral prospectivity modeling using support vector machine and naive bayes classifiers.•Model validation using the receiver operating characteristics curve.
Mineral prospectivity models (MPMs) are significantly essential in delineating target zones with the optimum likelihood of containing a particular sought-after mineral deposit. This present study ...carried out mineral potential mapping over the Collette Prospecting Licence (PL) Area of north-western Ghana using bivariate data-driven spatial statistical models composed of statistical index (SI) and weighting factor (WF) approaches. In the first instance, the geographic coordinates of variously known locations of artisanal mining operations as well as high Au concentration locations were mapped during a field survey. As a result, 181 known locations of Au occurrences were identified, out of which 127 (70%) were selected randomly for training and creating the mineral prospectivity models, whereas the remaining 54 (30%) were used to assess and validate the accuracy of the predictive models produced. The efficacy of mineral prospectivity models generated enormously depends on the appropriate selection of mineral-related factors. In this study, the following mineral-related condition factors (evidential layers) comprising analytic signal, lineament density, uranium-thorium ratio, uranium, potassium-thorium ratio, potassium, reduction-to-equator, and geology were used. The aforementioned evidential layers were derived and sourced from geophysical and geological datasets, which were later prepared for the generation of the models in a geographic information systems (GIS) environment. Finally, the validation of the mineral prospectivity models generated was carried out by applying the receiver operating characteristics (ROC) curve. The estimated results based on the ROC plots obtained for the predictive models showed that the area under the ROC curve (AUC) scores obtained for the SI-based and WF-based mineral prospectivity models were respectively, 0.780 and 0.733. Hence, it can be concluded that both mineral predictive models created in this study produced reasonably good accuracy (AUC score greater than 0.7) in predicting the potential zones of gold mineralisation occurrences within the Collette PL Area of north-western Ghana. These MPMs can serve as essential models for mineral exploration programmes within the study area.
•Gold mineralisation prospect of the Collette tenement in NW Ghana.•Mineral prospectivity modelling using the statistical index and the weighting factor techniques.•Model validation score using receiver operating characteristics curve.
The Bepkong gold deposit is one of several gold camps in the Paleoproterozoic Wa-Lawra greenstone belt in northwest Ghana. These deposits lay along the Kunche-Atikpi shear zone, which is part of the ...larger transcurrent Jirapa shear zone. The formation of these shear zones can be attributed to the general ESE-WNW major shortening that took place in the Wa-Lawra belt. Gold mineralization in the Bepkong deposit mainly occurs within graphitic shales and volcaniclastic rocks. The ore consists of four N-S trending lenticular bodies, plunging steeply to the south, that are lithologically and structurally controlled. Their shape and thickness are variable, though a general strike length of 560 m and an overall thickness of 300 m can be defined. An alteration mineral assemblage characterises the ore, and consists of chlorite-calcite-sericite-quartz-arsenopyrite-pyrite. Pyrite, as distinct from arsenopyrite, is not limited to the altered rocks and occurs throughout the area. At Bepkong, gold is associated with arsenopyrite and pyrite, which occur disseminated in the mineralized wall rock, flanking Type-1 quartz veins, or within fractures crossing these veins. Textural observations indicate the early formation of abundant arsenopyrite, followed by pyrite, with chalcopyrite, galena, sphalerite and pyrrhotite occurring as inclusions within pyrite and altered arsenopyrite. Detailed petrography, coupled with SEM, LA-ICP-MS and EMP analyses, indicate that gold in the Bepkong deposit occurs in three distinct forms: (i) invisible gold, mostly in arsenopyrite (ii); visible gold as micron-size grains within fractures and altered rims of arsenopyrite, as well as at the interface of sulphide grains; (iii) free visible gold in fractures in quartz veins and their selvages. We interpret the invisible gold to have co-precipitated with the early-formed arsenopyrite. The small visible gold grains observed within the sulphide interfaces, altered arsenopyrite, fractures and grain boundaries, are interpreted to have formed as a result of the dissolution and redistribution of the invisible gold during later alteration of arsenopyrite, which took place at lower temperatures during crenulation and fracturing accompanying late deformation, and was accompanied by pervasive pyritization of the wall rock.
•One of the few published work on gold in NW Ghana.•Using a multiscale approach to understand a gold deposit.•Relative rare case of gold in arsenopyrite with no gold associated with pyrite.•Using fluid inclusion and arsenopyrite geothermobarometry to understand the trapping conditions for gold.
In southern Ghana, the region along the coast between Accra and Cape Coast hosts a large number of pegmatites mineralized in lithium, niobium-tantalum and tin. The pegmatites occur in many distinct ...groups, each extending over several kilometers. They intrude metasedimentary units of the Birimian Supergroup, and are associated with early to late orogenic granite intrusions which are metaluminous, sterile, and too old to be potential parental granites for the pegmatites. In this study, we characterized the Winneba-Mankoadze group of geographically coeval pegmatites, using field description, petrography, rare-metal mineralogy and accessory mineral geochemistry on micas, garnet and Nb–Ta–Sn minerals, in order to determine its rare-metal potential and to investigate its origin. The results indicate that the pegmatites are part of the albite-spodumene type of the Lithium–Cesium–Tantalum (LCT) family. The rare metal mineral assemblages are particularly complex and display relevant oxide species such as columbite- and wodginite-group minerals, tapiolite, microlite, cassiterite and rutile, which are evidences of an extremely evolved magmatic system. Based on mineral assemblages, whole-rock geochemistry, and mineral geochemistry on garnet, micas and the CGM, two pegmatite fields are distinguished in the Winneba-Mankoadze group, and an anatectic origin is proposed. For the first time in West Africa, we fully describe a highly fractionated LCT-family pegmatite field comparable to the most evolved pegmatite bodies in the world.
•The Winneba pegmatites are Li-rich and contain mega-crystals of blue beryl and pink or green spodumene.•Minor red garnet and black tourmaline are common are common at Mankoadze.•The Winneba and Mankoadze pegmatites of the rare-element class and Lithium–Cesium–Tantalum (LCT) family.•The CGM compositions show high Nb/Ta fractionation, typical of highly fractionated flourine and Lithium enriched pegmatites.•Mineral fractionation patterns at Winneba-Mankoadze evidence the independent formation and evolution of two pegmatite fields.
In arid and semi-arid areas such as Ghana’s northern regions, water scarcity is prevalent particularly during the dry seasons (between the middle of November to April) and thus, the yearly demand for ...groundwater during these periods is very high in these areas. Hence, the delineation of prospective zones of groundwater resource occurrence offers an invaluable response towards the mitigation of the water scarcity issues that arise particularly during the dry seasons. In view of this, the employability capacity of the evidence belief functions (EBF) and weight of evidence (WOE) approaches towards the preparation of groundwater prospectivity models (GPM) have been assessed and compared in the eastern part of Ghana’s Northern Region. In carrying out the aforesaid task, multiple groundwater-related geospatial layers comprising drainage density (DD), digital elevation model (DEM), geology, lineament density (LD), slope, soil type, stream power index (SPI), topographic position index (TPI), topographic roughness index (TRI) and topographic wetness index (TWI) sourced from geophysical, geological, geomorphological and remote sensing datasets were used as inputs for both the EBF and WOE models. Inventory data comprising 230 existing locations of productive groundwater boreholes and wells, obtained from historical data and field surveys were applied. 161 of the groundwater inventory data prepared were randomly selected to train and subsequently generate groundwater prospectivity models based on the EBF and WOE approaches. The remaining 69 groundwater inventory data points were used as testing data to determine the efficacy of the GPM produced based on the two aforementioned data integration approaches using the receiver operating characteristics (ROC) curve. From the area under the ROC (AUC) scores obtained, the predictive performance of the GPM based on the EBF and WOE approaches were respectively 0.96 and 0.98. The validation results of the models show the ability of the models to correctly predict the potential of groundwater sources in relation to the geology, with the Bunya sandstone member and the Afram formation towards the eastern part of the study area verified as the most producible lithologies for groundwater occurrence. It is envisaged that the outputs developed in this study would be useful for planners to plan and manage groundwater resources effectively, especially in difficult geologic terranes with limited success of boreholes.
This study determines which predictors derived from geophysics or remote sensing data best generate a mineral prospectivity model (MPM) over Ghana's southern Kibi-Winneba belt in a scenario-based ...modeling case using Random Forest (RF) algorithm. Ten geophysically-derived predictors and six-remote sensing derived predictors were used as inputs in the first and second scenarios respectively. In the third case, the sixteen predictors derived from these afore-mentioned geoscientific datasets were used as inputs. Thus, three binary RF-based MPM were generated, and compared accordingly. The predictive performance in all three scenario-based RF-derived MPM produced was determined using the area under the receiver operating characteristic curve (AUC). AUC scores of 0.840, 0.785 and 0.809 respectively, were obtained for the first, second and third scenarios. The AUC scores obtained further indicates that, MPM developed based on using only the geophysics-sourced layers as inputs performed better in comparison with the MPMs generated in second and third scenarios.
The Leo Man Craton in West Africa is host to numerous economic gold deposits. If some regions, such as the SW of Ghana, are well known for world-class mineralizations and have been extensively ...studied, gold occurrences elsewhere in the craton have been discovered only in the last half a century or so, and very little is known about them. The Julie gold deposit, located in the Paleoproterozoic Birimian terrane of NW Ghana, is one such case. This deposit is hosted in a series of granitoid intrusives of TTG composition, and consists of a network of deformed, boudinaged quartz lodes (A-type veins) contained within an early DJ1 E–W trending shear zone with dextral characteristics. A conjugate set of veins (C-type) perpendicular to the A-type veins contains low grade mineralization. The main ore zone defines a lenticular corridor about 20–50m in width and about 3.5km along strike, trending E–W and dipping between 30 and 60°N. The corridor is strongly altered, by an assemblage of sericite+quartz+ankerite+calcite+tourmaline+pyrite. This is surrounded by a second alteration assemblage, consisting of albite+sericite+calcite+chlorite+pyrite+rutile, which marks a lateral alteration that fades into the unaltered rock. Mass balance calculations show that during alteration overall mass was conserved and elemental transfer is generally consistent with sulfidation, sericitization and carbonatization of the host TTG.
Gold is closely associated with pyrite, which occurs as disseminated grains in the veins and in the host rock, within the mineralized corridor. SEM imagery and LA-ICP-MS analyses of pyrites indicate that in A-type veins gold is associated with bismuth, tellurium, lead and silver, while in C-type veins it is mostly associated with silver. Pyrites in A-type veins contain gold as inclusions and as free gold on its edges and fractures, while pyrites from C-type veins contains mostly free gold. Primary and pseudosecondary fluid inclusions from both type veins indicate circulation in the system of an aqueous-carbonic fluid of low to moderate salinity, which entered the immiscibility PT region of the H2O–CO2–NaCl system, at about 220°C and <1kbar.
•One of very few published work on gold deposits in NW Ghana.•Next operating mine in NW Ghana and largest deposit in this region.•Relatively rare case of orogenic gold mineralization hosted in granitoids.•Unusual fluid inclusion composition for orogenic gold deposits in the WAC.
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