The Pb-Zn mine at Jebel Ghozlane is located in the Nappes zone (northern Tunisia). The occurrence... more The Pb-Zn mine at Jebel Ghozlane is located in the Nappes zone (northern Tunisia). The occurrence of the deposit as veins, stockworks, disseminations and replacement heaps at zones of contact between the Triassic dolostones and the Eocene limestones along major faults links the mineralization with tectonic processes. Barite and celestite in the deposit have δ34S values (+14.3 - +24.0‰ VCDT) that are consistent with the derivation of sulfates from Triassic evaporites and probably Messinian seawater. The δ34S values of galenas, varying between -9.1 and +22.1‰, can be split into two groups, one with positive δ34S values (with a median of +13.2‰) and the other with negative δ34S values (with a median of -4.0‰). These data suggest mixing of two sulfur end-members of mineralizing fluids, each corresponding to different reduction mechanisms (bacterial sulfate reduction and abiotic thermochemical sulfate reduction) of Triassic evaporites and probably Messinian seawater. Pb isotopes in galen...
The Shuangqing Fe-Pb-Zn-Cu deposit is located in the Xiangride County of Qinghai Province, China,... more The Shuangqing Fe-Pb-Zn-Cu deposit is located in the Xiangride County of Qinghai Province, China, and is a typical example of skarn deposits in the East Kunlun Mountains. Skarnization and mineralization took place along the contact zone between Carboniferous carbonates and the concealed Triassic plagiogranite. LA-ICP-MS U-Pb dating of zircons from the plagiogranite has yielded ages of 227.2±1.0 and 226.54±0.97 Ma, which are interpreted as the emplacement age of the plagiogranite. Molybdenites separated from ore-bearing quartz-veins yielded a Re-Os isochron age of 226.5±5.1 Ma. These age data confirm that both intrusion and related skarn mineralization initiated at ~227 Ma. Re contents of molybdenite, zircon ε Hf (t) and 176 Hf/ 177 Hf values fall into the ranges 3.31 to 6.58 μg/g, − 8.6 to − 0.0, and 0.282403 to 0.28263850, respectively. The timing of the Shuangqing Fe-Pb-Zn-Cu mineralization coincided with a major change in the stress field in East Kunlun from transpression to extension, related to the partial melting of thickening crustal materials in the a post-collisional tectonic setting.
This paper demonstrates a modeling procedure of mineral potential mapping based on singularity th... more This paper demonstrates a modeling procedure of mineral potential mapping based on singularity theory, and further presents an idea to look into metallogeny of Sn-Cu polymetallic deposits in southeastern Yunnan mineral district, China by applying a localized regression method. Mineralization is a typical cascade process generally accompanied by irregular geological, geochemical and geophysical signatures. Singularity index as an efficient anomaly analytical tool helps to identify anomalies as well as characterize formation processes of these anomalies. In this study, the singularity-based mineral potential mapping method was utilized to characterize hydrothermal mineralization associated with magmatic, tectonic and sedimentary processes in this district. Based on the results, a mineral prospectivity model was constructed to delineate target areas. In addition to mineral prospectivity, controlling effects of geo-processes on mineralization are spatially non-stationary. Geographically-weighted regression analysis was thus employed to investigate these spatially-varied controlling effects and it has contributed to improve understanding to local metallogeny in the study area. Results of the spatial analysis presented can be used to guide following stages of mineral exploration in the district.
Data-driven evidential belief (EB) modeling has already been demonstrated for mineral prospectivi... more Data-driven evidential belief (EB) modeling has already been demonstrated for mineral prospectivity mapping in areas with many (i.e., >20) deposits/prospects (i.e., with indicated/ inferred resources). In this paper, EB modeling is applied to a case-study area measuring about 920 km 2 with 12 known porphyry-Cu prospects and with evidential data layer containing missing values. Porphyry-Cu prospectivity of the same area has been modeled previously using weights-of-evidence modeling, which serves as reference for evaluating the results of EB modeling. Initially, EB modeling was used to quantify spatial associations of the known porphyry-Cu prospects with various geological features perceived to be porphyry-Cu mineralization controls. Spatial associations of the known porphyry-Cu prospects with geochemical data layers with missing values were also quantified. Then, geological and geochemical data layers found to have positive spatial associations with the known porphyry-Cu prospects were used as predictors of porphyry-Cu prospectivity. The results show that EB modeling is as efficient as WofE modeling in predictive modeling of mineral prospectivity in areas with as few as 12 prospects and with evidential data layers containing missing values.
The Huachanggou gold deposit is located in Lueyang County, Shaanxi Province, central China; it is... more The Huachanggou gold deposit is located in Lueyang County, Shaanxi Province, central China; it is situated in the Mian−Lue sutural zone in the western Qinling orogen and controlled by a WNW-striking ductile shear zone. The ore deposit is developed in spilite, limestone and phyllite in the Middle-Lower Devonian Sanhekou Group, and the wall rocks show evidence of deformation. Pyrite is the main gold-bearing mineral, and the native gold is either visible or microscopic.
The Random Forests (RF) algorithm is a machine learning method that has recently been demonstrate... more The Random Forests (RF) algorithm is a machine learning method that has recently been demonstrated as a viable technique for data-driven predictive modeling of mineral prospectivity, and thus, it is instructive to further examine its usefulness in this particular field. A case study was carried out using data from Catanduanes Island (Philippines) to investigate further (a) if RF modeling can be used for data-driven modeling of mineral prospectivity in areas with few (i.e., <20) mineral occurrences and (b) if RF modeling can handle predictor variables with missing values. We found that RF modeling outperforms evidential belief (EB) modeling of prospectivity for hydrothermal Au-Cu deposits in Catanduanes Island, where 17 hydrothermal Au-Cu prospects are known to exist. Moreover, just like EB modeling, RF modeling allows analysis of the spatial relationships between known prospects and individual layers of predictor data. Furthermore, RF modeling can handle missing values in predictor data through an RF-based imputation technique whereas in EB modeling, missing values are simply represented by maximum uncertainty. Therefore, the RF algorithm is a potentially useful method for data-driven predictive modeling of mineral prospectivity in regions with few (i.e., <20) occurrences of mineral deposits of the type sought. However, further testing of the method in other regions with few mineral occurrences is warranted to fully determine its usefulness in data-driven predictive modeling of mineral prospectivity.
The western Qinling, belonging to the western part of the Qinling-Dabie-Sulu orogen between the N... more The western Qinling, belonging to the western part of the Qinling-Dabie-Sulu orogen between the North China Block and South China Block, is one of the most important gold regions in China. Isotopic dates suggest that the Mesozoic granitoids in the western Qinling region emplaced during the Middle-Late Triassic, and the deposits formed during the Late Triassic.
Cite this article as: Emmanuel John M. Carranza and Alice G. Laborte, Random forest predictive mo... more Cite this article as: Emmanuel John M. Carranza and Alice G. Laborte, Random forest predictive modeling of mineral prospectivity with small number of prospects and data with missing values in Abra (Philippines), Computers and Geosciences, http://dx.
Index overlay and Boolean logic are two techniques customarily applied for knowledgedriven modeli... more Index overlay and Boolean logic are two techniques customarily applied for knowledgedriven modeling of prospectivity for mineral deposits, whereby weights of values in evidential maps and weights of every evidence map are assigned based on expert opinion. In the Boolean logic technique for mineral prospectivity modeling (MPM), threshold evidential values for creating binary maps are defined based on expert opinion as well. This practice of assigning weights based on expert opinion involves trial-and-error and introduces bias in evaluating relative importance of both evidential values and individual evidential maps. In this paper, we propose a data-driven index overlay MPM technique whereby weights of individual evidential maps are derived from data. We also propose a data-driven Boolean logic MPM technique, whereby thresholds for creating binary maps are defined based on data. For assigning weights and defining thresholds in these proposed data-driven MPM techniques, we applied a prediction-area plot from which we can estimate the predictive ability of each evidential map with respect to known mineral occurrences, and we use that predictive ability estimate to assign weights to evidential map and to select thresholds for generating binary predictor maps. To demonstrate these procedures, we applied them to an area in the Kerman province in southeast Iran as a MPM case study for porphyry-Cu deposits.
In the last two to three decades or so, the spatial pattern of mineral occurrences of a deposit-t... more In the last two to three decades or so, the spatial pattern of mineral occurrences of a deposit-type has been studied to derive insights to mineralization controls and assist mineral exploration. In the Skellefte district, Fry plots of volcanogenic massive sulfide (VMS) mines/ prospects reveal patterns that are likely due to postmineralization deformation events. The fractal dimensions of the spatial patterns of the present-day VMS mines/ prospects and that of the 'original' VMS deposits support the concept that spatial patterns of mineral deposits are spatially-invariant. Therefore, analysis of the spatial pattern of mineral deposits is useful not only in research about pre-and syn-mineralization geological settings but also post-mineralization geological settings.
The accuracy of classification of the Spectral Angle Mapping (SAM) is warranted by choosing the a... more The accuracy of classification of the Spectral Angle Mapping (SAM) is warranted by choosing the appropriate threshold angles, which are normally defined by the user. Trial-and-error and statistical methods are commonly applied to determine threshold angles. In this paper, we discuss a real value-area (RV-A) technique based on the established concentration-area (C-A) fractal model to determine less biased threshold angles for SAM classification of multispectral images. Short wave infrared (SWIR) bands of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) images were used over and around the Sar Cheshmeh porphyry Cu deposit and Seridune porphyry Cu prospect. Reference spectra from the known hydrothermal alteration zones in each study area were chosen for producing respective rule images. Segmentation of each rule image resulted in a RV-A curve. Hydrothermal alteration mapping based on threshold values of each RV-A curve showed that the first break in each curve is practical for selection of optimum threshold angles. The hydrothermal alteration maps of the study areas were evaluated by field and laboratory studies including X-ray diffraction analysis, spectral analysis, and thin section study of rock samples. The accuracy of the SAM classification was evaluated by using an error matrix. Overall accuracies of 80.62% and 75.45% were acquired in the Sar Cheshmeh and Seridune areas, respectively. We also used different threshold angles obtained by some statistical techniques to evaluate the efficiency of the proposed RV-A technique. Threshold angles provided by statistical techniques could not enhance the hydrothermal alteration zones around the known deposits, as good as threshold angles obtained by the RV-A technique. Since no arbitrary parameter is defined by the user in the application of the RV-A technique, its application prevents introduction of human bias to the selection of optimum threshold angle for SAM classification.
Previous prospectivity modelling for epithermal Au-Ag deposits in the Deseado Massif, southern Ar... more Previous prospectivity modelling for epithermal Au-Ag deposits in the Deseado Massif, southern Argentina, provided regional-scale prospectivity maps that were of limited help in A C C E P T E D M A N U S C R I P T ACCEPTED MANUSCRIPT 2 guiding exploration activities within districts or smaller areas, because of their low level of detail. Because several districts in the Deseado Massif still need to be explored, prospectivity maps produced with higher detail would be more helpful for exploration in this region. We mapped prospectivity for low-and intermediate-sulfidation epithermal deposits (LISEDs) in the Deseado Massif at both regional and district scales, producing two different prospectivity models, one at regional scale and the other at district-scale. The models were obtained from two datasets of geological evidence layers by the weights-of-evidence (WofE) method. We used more deposits than in previous studies, and we applied the leave-one-out cross validation (LOOCV) method, which allowed using all deposits for training and validating the models. To ensure statistical robustness, the regional and district-scale models were selected amongst six combinations of geological evidence layers based on results from conditional independence tests.
In this contribution, multivariate regression was applied to surface channel rock and borehole ge... more In this contribution, multivariate regression was applied to surface channel rock and borehole geochemical data from the world-class Sari Gunay epithermal gold deposit, in northwest Iran, to model subsurface mineralization for further drilling. Multiple, factorial, polynomial and response surface regression models were applied to the geochemical data sets from a training mineralized area to evaluate the accuracy of these models using separate geochemical data from a test area. Geochemical data of 31 elements in surface channel rock samples were used as independent variables, and three parameters namely average grade, sum and productivity in individual 25 m by 25 m grid cells, obtained by kriging of borehole data, were used as dependent variables. All the multivariate regression models revealed high determination coefficients for three parameters, among which the response surface regression model yielded the highest values. The response surface regression yielded the best result, followed by the multiple regression, in modeling the geochemical data from the test area. Therefore, the result of the response surface regression was used to model subsurface gold mineralization at the Sari Gunay gold deposit in order to design additional drillings.
This paper presents a statistical method for deriving the optimal prospective field sampling sche... more This paper presents a statistical method for deriving the optimal prospective field sampling scheme on a remote sensing image to represent different categories in the field. The iterated conditional modes algorithm (ICM) is used for segmentation followed by simulated annealing within each category. Derived field sampling points are more intense in heterogenous segments. This method is applied to airborne hyperspectral data from an agricultural field. The optimized sampling scheme shows superiority to simple random sampling and rectangular grid sampling in estimating common vegetation indices and is thus more representative of the whole study area.
A data-driven application of the theory of evidential belief to map mineral potential is demonstr... more A data-driven application of the theory of evidential belief to map mineral potential is demonstrated with a redefinition of procedures to estimate evidential belief functions. The redefined estimates of evidential belief functions take into account not only the spatial relationship of an evidence with the target mineral deposit but also consider the relationships among the subsets of spatial evidences within a set of evidential data layer. Proximity of geological features to mineral deposits is translated into spatial evidence and evidential belief functions are estimated for the proposition that mineral deposits exist in a test area. The integrated maps of degrees of belief for the proposition that mineral deposits exist in a test area is classified into a binary mineral potential map. For the Baguio district (Philippines), the binary gold potential map delineates (a) about 74% of the training data (i.e., locations of large-scale gold deposits) and (b) about 64% of the validation data (i.e., locations of small-scale gold deposits). The results demonstrate the usefulness of a geologically constrained mineral potential mapping using data-driven evidential belief functions to guide further surficial exploration work in the search for yet undiscovered gold deposits in the Baguio district. The results also indicate the usefulness of evidential belief functions for mapping uncertainties in the geologically constrained integrated predictive model of gold potential. D
Wildcat modelling of mineral prospectivity has been proposed for greenfields geologically-permiss... more Wildcat modelling of mineral prospectivity has been proposed for greenfields geologically-permissive terranes where mineral targets have not yet been discovered but a geological map is available as a source of spatial data of predictors of mineral prospectivity. This paper (i) revisits the initial way of assigning wildcat scores (Sc) to predictors of mineral prospectivity and (ii) proposes an improvement by transforming Sc into improved wildcat scores (ISc) by using a logistic function. This was shown in wildcat modelling of prospectivity for low-sulphidation epithermal-Au (LSEG) deposits in Aroroy district (Philippines). Based on knowledge of characteristics of and controls on LSEG mineralization in the Philippines, the spatial predictors of LSEG prospectivity used in the study are proximity to porphyry plutonic stocks, faults/fractures and fault/fracture intersections. The Sc and ISc of spatial predictors are input separately to principal components analysis to extract a favourability function that can be interpreted as a wildcat model of LSEG prospectivity. The predictive capacity of the wildcat model of LSEG prospectivity based on the ISc of geological predictors is roughly 70% higher than that of the wildcat model of LSEG prospectivity based on the Sc of geological predictors. A slight increase of predictive capacity of wildcat modelling of LSEG prospectivity is also achieved when the ISc of geological predictors are integrated with the ISc of geochemical anomalies, but not with the Sc of geochemical anomalies. The proposed improvement is significant because if the study district were a greenfields exploration area, then a wildcat model of LSEG prospectivity based on the old wildcat methodology would have caused several LSEG targets to be missed.
The Jebel Ressas Pb-Zn deposits in North-Eastern Tunisia occur mainly as open-space fillings (lod... more The Jebel Ressas Pb-Zn deposits in North-Eastern Tunisia occur mainly as open-space fillings (lodes, tectonic breccia cements) in bioclastic limestones of the Upper Jurassic Ressas Formation and along the contact of this formation with Triassic rocks. The galena-sphalerite association and their alteration products (cerussite, hemimorphite, hydrozincite) are set within a calcite gangue. The Triassic rocks exhibit enrichments in trace metals, namely Pb, Co and Cd enrichment in clays and Pb, Zn, Cd, Co and Cr enrichment in carbonates, suggesting that the Triassic rocks have interacted with the ore-bearing fluids associated with the Jebel Ressas Pb-Zn deposits. The d 18 O content of calcite associated with the Pb-Zn mineralization suggests that it is likely to have precipitated from a fluid that was in equilibrium with the Triassic dolostones. The d 34 S values in galenas from the Pb-Zn deposits range from -1.5 to +11.4‰, with an average of 5.9‰ and standard deviation of 3.9‰. These data imply mixing of thermochemically-reduced heavy sulfur carried in geothermal-and fault-stressdriven deep-seated source fluid with bacterially-reduced light sulfur carried in topography-driven meteoric fluid. Lead isotope ratios in galenas from the Pb-Zn deposits are homogenous and indicate a single upper crustal source of base-metals for these deposits. Synthesis of the geochemical data with geological data suggests that the base-metal mineralization at Jebel Ressas was formed during the Serravallian-Tortonian (or Middle-Late Miocene) Alpine compressional tectonics.
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