Search Results (49)

The Terziali is a shear-hosted orogenic gold prospect located in the Central Anatolian Crystalline Complex, Türkiye. This study focuses on soil geochemistry, element correlations, background and threshold values, and evaluates exploration implications over a survey area of 35.5 km². A total of 1826 soil samples were collected from the B horizon using a grid of 100 × 50 m and were analyzed using ICP-AES, ICP-MS, and fire assay techniques. Statistical techniques of median + 2MAD threshold calculations, descriptive statistics, Kolmogorov–Smirnov tests, correlation analysis, hierarchical clustering, and Q–Q plots were carried out to identify geochemical anomalies. The data demonstrate Au threshold (28 ppb) and peak concentration (460 ppb), non-normal distributions characterized by strong positive skewness, revealing the outliers linked to mineralization. Soil geochemistry indicates a moderate association between Au and As in the four-acid dataset (r = 0.465), although the correlations between Au and Sb and Ag and W are relatively weak. The spatial analysis indicates that Au anomalies are predominantly linked to the NW–SE-oriented Demirli Thrust Fault. As displays extensive dispersion halos surrounding the gold anomalies; it establishes itself as an efficient pathfinder element. Conversely, Sb and W exhibit unique anomaly patterns, whereas Ag patterns are weak and dispersed. The Terziali prospect provides a substantial geochemical framework for identifying structurally controlled orogenic gold systems in Central Anatolia and the western Tethyan metallogenic belt. Full article

Geochemical data provide direct constraints on mineralization, and the extraction of mineralization-related geochemical anomalies is essential for mineral resource prediction and assessment. The regional geochemical field reflects the spatial expression of ore-forming environments resulting from the superposition of multiple geological processes, with distinct elemental assemblages corresponding to different processes. The Ailaoshan metallogenic belt, located in the southeastern segment of the India–Eurasia collisional orogen, experienced multiple episodes of opening and closure, extension, amalgamation, and compression, leading to intense deformation. Its complex structural framework, multistage magmatism, and metamorphism have generated abundant mineral resources, particularly Au, Sn, Cu, Pb-Zn, and Ni deposits. Using the 1:200,000–scale national stream sediment geochemical dataset, principal component analysis (PCA) was applied to identify major ore-forming elemental assemblages. Singular value decomposition (SVD) was then used to extract regional and local anomalies for PC2 (Ag-As-Bi-Cu-Mn-Pb-Sn), PC3 (B-Be-Bi-Cu-F-W), PC4 (La-Nb-Th-U-Y-Zr), and PC10 (Au-Hg). Ultimately, six metallogenic prospective areas were consequently delineated. Full article

Stream sediment geochemistry is a widely used reconnaissance tool in early-stage mineral exploration, particularly in regions where direct evidence of mineralisation is limited. Because stream sediment anomalies provide indirect geochemical signatures and are typically constrained by limited ground-truth information, labelled datasets are often scarce and spatially biased. This limitation restricts the applicability of supervised learning approaches and highlights the need for robust unsupervised methods. In this study, six unsupervised techniques, Principal Component Analysis (PCA), Non-negative Matrix Factorisation (NMF), Uniform Manifold Approximation and Projection (UMAP), Autoencoder (AE), Deep Embedded Clustering (DEC), and an Averaged Ensemble Index (AVE), were evaluated for integrating multivariate stream sediment geochemical data and delineating gold prospectivity zones. Eight gold-related elements (Au, As, Ag, B, Hg, Mo, Sb, and W) were selected based on regional metallogenic characteristics and previously reported geochemical associations. To facilitate direct comparison, all model outputs were normalised to a fuzzy membership scale ranging from 0 to 1. Model performance was quantitatively assessed using Receiver Operating Characteristic–Area Under the Curve (ROC–AUC) and Matthews Correlation Coefficient (MCC) metrics based on independently verified mineralised and non-mineralised locations. The results indicated that DEC and AE consistently outperformed the other methods investigated, achieving the highest ROC–AUC and MCC values, whereas UMAP exhibited comparatively weaker performance. The findings demonstrated that unsupervised representation learning approaches, particularly DEC and AE, provided a more effective framework for integrating multivariate geochemical data and delineating gold-related anomalies in data-limited exploration environments than conventional dimensionality reduction and heuristic integration methods. Full article

In this research, surface Au concentration measurements are considered as a spatially correlated geochemical field associated with deep occurrences of disturbing masses using real geological exploration data from the Novo-Khairuzovsky gold deposit in East Kazakhstan. The approach is based on the relationship between potential-field continuation problems and reconstruction of subsurface geological anomalies from surface observations. The considered approaches include Tikhonov and Lavrentiev regularization, SVD, and TSVD. Special attention is given to regularization parameter selection using the L-curve method, Morozov discrepancy principle, and GCV. Comparative computational analysis is performed to evaluate the accuracy, stability, and efficiency of these methods in solving first-kind Fredholm integral equations. Results are assessed using error metrics and spatial visualization of reconstructed fields within a Geographic Information System (ArcGIS), enabling consistent geospatial interpretation. Results show that Lavrentiev regularization with L-curve criterion provides the most stable and reliable reconstruction across all depths, achieving high correlations ($R=0.8876$ at 100 m and $R=0.8049$ at 200 m) with low reconstruction errors. Tikhonov regularization performs acceptably at 100 m but becomes less stable at greater depths. Among spectral methods, TSVD improves stability compared with classical SVD, while standard SVD shows weak correlations and larger reconstruction errors due to high noise sensitivity. Full article

The Western Chagai Belt of Pakistan hosts major porphyry Cu-Au systems, but prospectivity mapping in this arc remains difficult because favorable lithology, intrusive bodies, fault corridors, hydrothermal alteration, and Cu geochemical anomalies are spatially heterogeneous across a structurally complex and arid terrain. These conditions create a scientific need for an integrated mapping framework that can combine remote sensing alteration evidence, geology, structure, and geochemistry within a unified and reproducible workflow. This study presents GeoHybridGNN, a hybrid deep learning framework for porphyry copper prospectivity mapping in the Western Chagai Belt. The framework integrates multi-source raster evidence, including remote sensing-derived spectral alteration indices, a Cu geochemical raster, and distance-to-fault information, with graph-based node representations that combine regular neighborhood adjacency on retained grid cells with node attributes derived from lithology and aligned geoscientific raster summaries. All predictors were harmonized to a common 30 m reference raster grid and evaluated using five-fold spatial block cross-validation to provide a more spatially realistic assessment than ordinary random splitting. The implemented model combines a CNN-based raster patch encoder with a GraphSAGE-based graph classifier. Raster patches extracted around graph nodes are encoded into 64-dimensional embeddings, and these embeddings are concatenated with node-level graph features before full-batch graph learning and prediction. Copper occurrences were used only for supervised label assignment and evaluation and were not used as predictive inputs. The results show that GeoHybridGNN produces spatially coherent prospectivity maps, stable fold-wise prediction patterns, and improved target delineation relative to the tested comparison models. Cu geochemical integration produces only a limited change in global discrimination but provides modest local target sharpening in selected zones. These results indicate that GeoHybridGNN can serve as an uncertainty-aware and geologically constrained decision support workflow for porphyry copper targeting. More broadly, the framework provides a transparent strategy for exploration screening in structurally complex and data-heterogeneous metallogenic belts where remote sensing, geological, structural, and geochemical evidence must be integrated consistently. Full article

The Jiangnan Orogenic Belt is a world-renowned metallogenic region for Au-W-Sb mineralization, with the Wangu deposit being a representative one. Previous research has demonstrated that tungsten in this Au-W-Sb deposit is sourced from the hosting metasedimentary rocks, but the specific mineral that provides tungsten is still unclear. This study evaluates the tungsten source by conducting petrographic observations and geochemical and geochronological analyses on the rutile from the host slate the Wangu deposit. The results show that rutile from wall rocks of the Wangu deposit yields an age of 955 ± 13 Ma, which is older than both the ore-forming age of the deposit and the age of the host strata. Electron microprobe analyses (EMPA) and laser ablation–inductively coupled plasma–mass spectrometry (LA-ICP-MS) elemental analyses show that detrital rutile is enriched in elements such as Fe, Cr, V, and W, as well as high-field-strength elements (HFSE) including Nb, Ta, Zr, and Hf. The total rare earth element (ΣREE) ranges from 3.37 ppm to 156.85 ppm. The samples are generally enriched in light rare earth elements (LREEs) and exhibit distinct negative Eu anomalies. These geochemical features and a geochronological age of 955 ± 13 Ma suggest that the rutile is of detrital origin and they are possibly derived from the Grenvillian rocks. It is concluded that the detrital rutile in the metasediments could be an important source for hydrothermal tungsten enrichment. Full article

Apatite is a widespread accessory mineral, which can provide information on the geochemical characteristics of magma and the conditions of hydrothermal alteration of the rocks in magmatic–hydrothermal deposits. This study aims to understand the relationships between the geochemical and textural features of apatites from diorite porphyries that have undergone different degrees of hydrothermal alteration in the Sharlo Dere area, Chelopech epithermal Cu-Au deposit, Bulgaria. The apatites were characterized by laser ablation–inductively coupled plasma mass spectrometry, scanning electron microscopy with energy-dispersive X-ray spectroscopy, electron probe microanalysis with wave-dispersive spectroscopy, optical cathodoluminescence and multi-element mapping. Magmatic apatites from “hematitic”, propylitic and propylitic-sericitic zones of alteration are distinguished by euhedral crystals with oscillatory zoning and brown luminescence in CL images. In quartz-sericitic alteration zones, apatite has a yellow CL response. Hydrothermally altered apatites in the diorite porphyries overprinted by advanced argillic alteration have corroded, irregular forms and pink-green luminescence. Apatite crystals of magmatic origin reveal high contents of chlorine, strontium, light rare earth elements (LREE), negative Eu anomalies and high La_N/Sm_N and Ce_N/Yb_N ratios. Hydrothermally altered or hydrothermal apatites are distinguished by their higher contents of Na₂O, F, SO₃, Y and middle rare earth elements (MREEs) and their low La_N/Sm_N and Ce_N/Yb_N ratios. The intensity of hydrothermal alteration affects the luminescence and major and trace element contents, including the rare earth element patterns in the apatites, implying apatite can be used as a geochemical indicator to study magmatic–hydrothermal ore deposits. Full article

The Huxu Au-dominated deposit is a representative intermediate sulfidation epithermal deposit in the middle section of the Gan-Hang belt. The formation of such deposits is commonly closely related to deep magmatism. However, the specific relationship between the formation of the Huxu deposit and the magmatic rocks, and the tectonic setting of the related magmatism and mineralization in this deposit still remains unclear. In this study, we present the results of U-Pb dating, major and trace element analysis, and Nd isotope analysis of the magmatic zircon and apatite from the ore-bearing quartz diorite porphyry in the Huxu deposit. The results show that the U-Pb ages of zircon and apatite from the quartz diorite porphyry are 137.9 ± 1.3 Ma and 130 ± 16 Ma, respectively; the total content of rare earth elements (ΣREEs) in the zircons ranges from 446.66 to 2752.92 ppm, exhibiting enrichment in heavy REE and depletion in light REE, with a slightly negative Eu anomaly and a slightly positive Ce anomaly; the ΣREEs in the apatite is relatively high, ranging from 3252.02 to 13,155.92 ppm, averaged 5604.16 ppm, and exhibits a right-leaning mode with light REE enrichment and heavy REE depletion, with a moderate degree of negative Eu anomaly; the distribution of ¹⁴³Nd/¹⁴⁴Nd ratios of the apatite is rather concentrated (0.512145–0.512271), and the εNd(t) value calculated based on the U-Pb age of apatite ranges from −8.31 to 5.79. By combining the geological characteristics and the geochemical data of the deposit and the ore-bearing magmatic rocks, we propose that the ore-bearing quartz diorite porphyry of the Huxu Au-dominated polymetallic deposit belongs to I-type granite; the parental magma is the mixture of juvenile and ancient crustal melts; the tectonic setting of the intrusion and mineralization is the continental margin arc related to the subduction of the ancient Pacific Ocean Plate in the Early Cretaceous Epoch; and the ore-forming fluids and metals are provided by deep magma. Full article

Ataúro Island, located in the inner Banda Arc, provides a natural laboratory to investigate the interplay between magmatic evolution, hydrothermal circulation, and near-surface weathering in an active arc–continent collision setting. This study presents the first systematic island-wide geochemical baseline for Ataúro Island, based on multi-element analyses of stream sediments integrated with updated geological, structural, and hydromorphological information. Compositional Data Analysis (CoDA–CLR–PCA), combined with anomaly mapping and spatial overlays, defines a coherent three-tier geochemical framework comprising: (i) a lithogenic component dominated by Fe–Ti–Mg–Ni–Co–Cr, reflecting the geochemical signature of basaltic to andesitic volcanic rocks; (ii) a hydrothermal component characterized by Ag–As–Sb–S–Au associations spatially linked to structurally controlled zones; and (iii) an oxidative–supergene component marked by Fe–V–Zn redistribution along drainage convergence areas. These domains are defined strictly on geochemical criteria and represent geochemical process domains rather than proven metallogenic provinces. Rare earth element (REE) systematics further constrain the geotectonic setting and indicate that the primary geochemical patterns are largely controlled by lithological and magmatic differentiation processes. Spatial integration of geochemical patterns with fault architecture highlights the importance of NW–SE and NE–SW structural corridors in focusing hydrothermal fluid circulation and associated metal dispersion. The identified Ag–As–Sb–Au associations are interpreted as epithermal-style hydrothermal geochemical enrichment and exploration-relevant geochemical footprints, rather than as evidence of confirmed or economic mineralization. Overall, Ataúro Island emerges as a compact natural analogue of post-arc geochemical system evolution in the eastern Banda Arc, where lithogenic background, hydrothermal fluid–rock interaction, and early supergene processes are superimposed. The integrated geochemical framework presented here provides a robust baseline for future targeted investigations aimed at distinguishing lithogenic from hydrothermal contributions and evaluating the potential significance of the identified geochemical enrichments. Full article

The Hadamengou gold deposit, located on the northern margin of the North China Craton, represents one of the region‘s most significant gold mineralization clusters. However, exploration in its deeper and peripheral sectors is constrained by ecological protection policies and the structural complexity of the ore-forming systems. Multivariate analysis combined with multi-model integration provides an effective mathematical approach for interpretating geochemical datasets and guiding mineral exploration, yet, its application in the Hadamengou region has not been systematically investigated. To address this research gap, this study developed a pilot framework in the key Buerhantu area, on the periphery of the Hadamengou metallogenic cluster, applying and adapting a multivariate-multimodel methodology for mineral prediction. The goal is to improve exploration targeting, particularly for concealed and deep-seated mineralization, while addressing the methodological challenges of mathematical modeling in complex geological conditions. Using 1:10,000-scale lithogeochemical data, we implemented a three-step workflow. First, isometric log-ratio (ILR) and centered log-ratio (CLR) transformations were compared to optimize data preprocessing, with a reference column (YD) added to overcome ILR constraints. Second, principal component analysis (PCA) identified a metallogenic element association (Sb-As-Sn-Au-Ag-Cu-Pb-Mo-W-Bi) consistent with district-scale mineralization patterns. Third, S-A multifractal modeling of factor scores (F1–F4) effectively separated noise, background, and anomalies, producing refined geochemical maps. Compared with conventional inverse distance weighting (IDW), the S-A model enhanced anomaly delineation and exploration targeting. Five anomalous zones (AP01–AP05) were identified. Drilling at AP01 confirmed the presence of deep gold mineralization, and the remaining anomalies are recommended for surface verification. This study demonstrates the utility of S-A multifractal modeling for geochemical anomaly detection and its effectiveness in defining exploration targets and improving exploration efficiency in underexplored areas of the Hadamengou district. Full article

Intense chemical weathering in tropical environments poses challenges for conventional geochemical exploration, as primary lithological signatures become heavily altered. Stream sediment geochemistry provides a robust alternative for detecting anomalous geochemical patterns under these conditions. In this study, 636 stream sediment samples and 15 rock samples were evaluated using Principal Component Analysis (PCA), Median + 2 Median Absolute Deviation (MAD), and Concentration–Area (C–A) fractal modeling to identify potential anomaly zones. These results were compared with the traditional Mean plus 2 Standard Deviation (SD) approach. The findings indicated that Mean + 2SD offers a conservative threshold but overlooks anomalies in heterogeneous datasets, while Median + 2MAD provides robustness against outliers. The C-A fractal model effectively characterizes low- and high-order anomalies by capturing multiscale variability. Elements such as Au–Ag–Hg–Se–Sb–As form a system indicating low- to intermediate-sulphated epithermal mineralization. Au–Pb points to polymetallic hydrothermal mineralization along intrusive contacts. The southern region is a primary mineralization center controlled by an intrusive–volcanic boundary, whereas the east and west areas exhibit secondary mineralization, characterized by altered lava breccia. The correlation between shallow epithermal and deeper intrusive-related porphyry systems, especially regarding Au–Ag, offers new insights into the metallogenic landscape of the Sunda–Banda arc. Beyond regional significance, this research presents a geostatistical workflow designed to mitigate exploration uncertainty in geochemically complex zones, providing a structured approach applicable to volcanic-arc mineralized provinces worldwide. Full article

The traditional methods for classifying elemental concentrations such as the cumulative frequency method, the logarithmic interval method, and the mean–standard deviation method all have the limitation of depending on a specific dataset. An objective “ruler” that can measure the elemental concentration level regardless of the amount of data (even for a single sample) and enables comparisons among different elements and regions is highly necessary. Recently, the 19-level fixed-value method was proposed as a “ruler” to measure the elemental concentrations of Sn, Li, Mo, and Ni objectively and to facilitate comparisons across elements and regions. However, the method for Au has not been proposed until now. In this paper, we propose the “ruler” for Au, which objectively divides Au concentrations into 19 levels with 18 fixed values from the detection limit to the cut-off grade with easily understood numbers. The “ruler” for Au along with those for Mo and Sn was applied to geochemical survey data at 1:200,000 and 1:50,000 scales, respectively, in the Zhongchuan area of Western Qinling, China, to classify elemental concentrations and draw geochemical maps. The results show that elemental concentrations can be measured using the “ruler” to assess the background, anomaly, and mineralization levels objectively, and the levels can be compared across different elements, regions, and even different scales. Geochemical maps show that in the study area, known gold deposits are all associated with high anomalies or mineralization levels of Au, while the Mo and Sn concentrations are predominantly at background levels. These results are consistent with the known mineral resources in this area. When superimposing geochemical maps of larger scales onto those of smaller scales, the variation in the elemental concentration levels with different survey scales indicates valuable geochemical meanings for mineral exploration. Full article

The Northeastern Hunan Province (NEH), situated within the Central Jiangnan Orogen, hosts abundant Au-polymetallic deposits. However, the coupling mechanism between the deep tectono-magmatism and Au-polymetallic mineralization remains poorly understood. In this study, a three-dimensional (3D) resistivity model derived from 59 magnetotelluric (MT) stations is presented to investigate the lithospheric architecture and its relationship to Au-polymetallic mineralization. The model reveals three prominent mid-to-lower crustal conductors (3–30 Ω·m) at 15–35 km depth beneath Au-polymetallic deposits along NE faults. These anomalies are interpreted as source zones and pathways for magmatic-hydrothermal fluids during the Late Mesozoic tectono-magmatism, likely formed by the enrichment of graphite films and sulfides along faults, which thus account for the observed conductive features. Moreover, the model reveals a thinning electrical lithosphere–asthenosphere boundary (eLAB) at ~80 km depth beneath the Southeastern NEH, attributed to lithospheric delamination triggered by the rollback of the Paleo-Pacific plate. This delamination facilitated the upwelling and lateral migration of asthenospheric materials, which promoted intense extension and crust–mantle interaction. Consequently, metallic elements were extensively extracted from the crust and concentrated into large-scale Au-polymetallic deposits in the NEH. Integrating with previous geochemical study, a deep-seated magmatic underplating and MASH model is proposed as key drivers of Au-polymetallic enrichment in the NEH, effectively linking deep tectono-magmatism with shallow mineralization. From a rheological perspective, three low-viscosity zones within the mid-to-lower crust likely acted as both vertical conduits and deep sources for metallogenic fluids, providing favorable pathways for their migration and accumulation. Full article

The Galale Cu–Au deposit lies on the northern margin of the western Gangdese metallogenic belt, near the western edge of the Gangdese arc within the Bangong–Nujiang suture zone. Unlike the well-studied Miocene Cu belt in southern Gangdese, this region remains insufficiently investigated, particularly in terms of geochemical characterization, leading to an ambiguous metallogenic model and a debated tectonic setting—specifically, the unresolved issue of subduction polarity across the Bangong–Nujiang suture. This tectonic ambiguity has important implications for understanding magma sources, metal transport pathways, and, consequently, for guiding mineral exploration strategies in the area. To address this, we conducted zircon U–Pb dating on the ore-related quartz diorite and granodiorite, yielding crystallization ages of 84.05 ± 0.34 Ma and 77.20 ± 0.69 Ma, respectively. Integrated with previous data, these results constrain mineralization to 83–89 Ma, which includes both skarn-type Cu–polymetallic and porphyry-type Cu mineralization. Regional comparisons support a tectonic model involving slab rollback and southward subduction of the Bangong–Nujiang oceanic lithosphere. Geochemical analyses of quartz diorite, granodiorite, and monzonitic granite show high-K calc-alkaline, peraluminous I-type affinities, with enrichment in LREEs and LILEs, and depletion in HREEs and HFSEs. Notably, the monzonitic granite is marked by high SiO₂, Sr/Y, and Rb/Sr ratios, low Zr/Hf, strong LREE enrichment, weak Eu anomalies, and pronounced Nb–Ta depletion, indicating high oxygen fugacity and favorable conditions for Mo mineralization. The deposit formed through tectono-magmatic processes related to the closure of the Bangong–Nujiang Neo-Tethys Ocean. Subduction and subsequent lithospheric delamination induced partial melting of mantle and crustal sources, generating quartz diorite and granodiorite intrusions. Magmatic fluids interacted with carbonate wall rocks to form skarn assemblages, concentrating ore metals along structures. The mineralization formed within the contact zones between intrusions and surrounding country rocks. Late-stage granite porphyry intrusions (~77 Ma), inferred from major, trace, and rare earth element compositions to have the highest Mo potential, may represent an extension of earlier skarn mineralization in the area (83–89 Ma). This study presents the first comprehensive geochemical dataset for the Galale deposit, refines its metallogenic model, and identifies key geochemical indicators (e.g., Sr, Y, Nb, Rb, Zr, Hf) for Mo exploration. Full article

Carlin-type gold deposits in southwestern Guizhou, China require systematic exploration methods to identify deep and peripheral prospecting potential beyond known deposits. We conducted a 1:50,000-scale soil geochemical survey across 928 km² in the Nibao gold deposit and its surrounding areas, with a total of 8842 samples collected. Fifteen elements were systematically analyzed, with particular focus on pathfinder elements associated with Carlin-type gold mineralization. Building on previous comparative analyses of soil geochemical and tectono-geochemical characteristics, this research systematically examines the enrichment patterns of soil geochemistry and their significance for ore prospecting. The results demonstrate that (1) elements such as Au, As, Sb, Hg, W, and Mo show significant positive correlation and strong enrichment patterns, indicating excellent metallogenic potential; (2) 176 and 12 single- and composite-element anomalies were delineated, respectively, with HS-2, HS-3, and HS-7 anomalies exhibiting high intensity and distinct concentration zonation, similar to those of the high factor score distribution of Au-As-Sb-Hg-W-Mo; (3) three prospecting targets were identified based on anomaly characteristics and geological conditions, including Nibao, Baogudi, and Sandaogou; (4) multiple mineralized bodies were revealed through engineering verification, indicating good prospecting potential in the deep and surrounding areas of the targets. These findings provide a scientific basis for further exploration of Carlin-type gold deposits in the study area and southwestern Guizhou. Full article