Exploration Theories, Methods and Technologies: Latest Advances and Prospects

Finding new, effective predictive variables for 3D mineral prospectivity modeling is both important and challenging. The 3D ore-forming numerical modeling quantitively characterizes the complex coupling-mineralization process of the structure, fluid, heat, and wall rock, which may be potential indicators for mineral exploration. We here conducted 3D mineral prospectivity modeling with the integration of ore-forming computational simulation information in the Xiadian orogenic gold deposit, China, to examine whether the simulation data input can improve the reliability of prospectivity modeling. First, we constructed the 3D models of the orebody and fault to extract the fault geometric features using spatial analysis, as they are always considered to be the crucial controls of gold distribution. Second, we performed 3D numerical modeling of the deformation–fluid–heat-coupling process of the structurally controlled hydrothermal Au system using the FLAC^3D platform. Finally, the fault-geometry features (buffer, dip, dip variation, and undulation) and the ore-formation-simulation indices (volume strain, shear strain, temperature variation, and fluid flux) were integrated using Bayesian decomposition modeling, which has a promising nonlinear model ability and a flexible variable-integration ability. The prospectivity modeling results demonstrated that the model generated by combining geometry and simulation variables achieved significantly higher AUC, precision, accuracy, Kappa, and F1 scores compared to other models using a single-predictor-variable dataset. This suggests that the joint use of geometry and simulation variables construct a comprehensive association between gold and its ore-controlling factors, thereby resulting in a highly reliable prospectivity model. Thus, the approach of 3D mineral prospectivity modeling aided by ore-forming numerical simulation proves to be more useful in guiding mineral exploration, especially in the condition of fewer variables. Based on the prospectivity modeling outcomes, we identified four gold targets at depth in the Xiadian district that warrant focused exploration efforts. Full article

The statistical modeling with ILR-RPCA-back CLR has two problems when dealing with the closure effect of geochemical data. Firstly, after performing isometric logratio (ilr) transformation, robust principal component analysis (RPCA) is employed for processing. The double-plot diagram illustrates that the element sequence transformation occurs in the first and second principal components, while the unique principal component remains unattainable. Secondly, by transforming both the score and load into the centered logratio (CLR) space using the U matrix, it is possible to obtain a score result that corresponds to the original order of elements according to the CLR = ILR·U formula. However, for obtaining a load result that corresponds to the original order of elements, an alternative formula “CLR = UT·ILR” must be used instead. In order to determine the optimal element assemblage for porphyry copper deposits, this study conducted statistical analysis on mineral assemblages from discovered deposits in the Gangdese metallogenic belt and identified Cu, Mo, Au, Ag, W, and Bi as key elements associated with porphyry copper deposits. Subsequently, by analyzing the singularities of the composite elements, the spatial overlay of the combined element is carried out, and concentration-area (C-A) fractal filtering is applied to identify the anomaly and background areas. To facilitate comparison, we conducted an analysis of various mineral and ore deposit types, revealing the following findings: (1) Combination elements exhibit superior recognition capability than single elements in porphyry copper deposits; (2) Skarn-type copper deposits unrelated to porphyry show a high degree of dissimilarity compared to those related to porphyry; (3) this method offers advantages over the single element method in evaluating porphyry gold deposits by reducing anomaly levels and initial investment during the evaluation stage for porphyry copper anomalies; (4) However, this method has limited ability in distinguishing between porphyry copper and molybdenum deposits. Full article

Chromite is a strategic mineral resource for many countries, and chromite deposit occurrences are widespread in the ultramafic rocks of the Yarlung Zangbo ophiolite belt, particularly in the harzburgite unit of the mantle section. Conducting field surveys in complex and poorly accessible terrain is challenging, expensive, and time-consuming. Remote sensing is an advanced method of achieving modern geological work and is a powerful technical means of geological research and mineral exploration. In order to delineate outcrops of chromite-bearing mantle peridotite, the present research study integrates seven image-enhancement techniques, including optimal band combination, decorrelation stretching, band ratio, independent component analysis, principal component analysis, minimum noise fraction, and false color composite, for the interpretation of Landsat8 OLI and WorldView-2 satellite data. This integrated approach allows the effective discrimination of chromite-containing peridotite outcrops in the Luobusa area, Tibet. The interpretation results derived from these integrated image-processing techniques were systematically verified in the field and formed the basis of the feature selection process of different lithologies supported by the support vector machine algorithm. Furthermore, the distribution range of the ferric contamination anomaly is detected through the de-interference abnormal principal component thresholding technique, which shows a high spatial matching relationship with mantle peridotite. This is the first study to utilize Landsat8 OLI and WorldView-2 remote sensing satellite data to explore the largest chromite deposit in China, which enriches the research methods for the chromite deposits in the Luobusa area. Accordingly, the results of this investigation indicate that the integration of information extracted from image-processing algorithms using remote sensing data could be a broadly applicable tool for prospecting chromite ore deposits associated with ophiolitic complexes in mountainous and inaccessible regions such as Tibet’s ophiolitic zones. Full article

Studying the activation, migration and precipitation processes of ore-forming elements is essential for understanding the genesis and mechanisms of skarn deposits. A typical skarn profile formed by the intrusion of Yanshanian granodiorite into the Carboniferous carbonate strata was studied. The profile is highly consistent with the classic skarn profile, ranging from the intrusion, weak alteration belt, skarn belt (inner and outer skarn belt) and mineralization belt (mainly characterized by Cu mineralization) to the surrounding marble without being affected by late-stage low-temperature or supergene weathering alteration. Whole-rock data show that the major and trace elements exhibit relatively small changes in the granodiorite and inner skarn, but huge variation in the boundary between the inner and outer skarn; Na, Al, Ti and Sr show significant decreases, while Fe, Mg, Zn, V and Ni show significant increases. The elemental content in the outer skarn is 10–100 times or more higher than that in the marble, but the elements such as Ca, Sr and Cs diluted from the marble. During the migration process from the inner skarn to the outer skarn, some elements (such as K, Rb and Ba) were depleted in the inner, but not enriched in the outer, indicating that they may migrate to farther locations. Grossularite developed in the inner skarn, with light rare earth element (LREE) depletion and heavy REE enrichment, as well as positive and negative anomalies of Eu (δEu = 0.42–3.95). Andradite developed in the outer skarn, with zonation development, light REE enrichment, and heavy REE depletion and a positive Eu anomaly (δEu = 0.36–46.83). Some negative Eu anomalies appear at the edges of garnets in the outer skarn, indicating fluctuations in fO₂ during the late skarn process. A positive correlation between Fe³⁺ and REE³⁺ in the garnets from the inner skarn, as well as between Al³⁺ and REE³⁺ from the outer skarn indicated that there are different YAG substitution mechanisms of REE between the inner and outer skarn. Low garnet REE contents and highly variable Y/Ho ratios in outer skarn suggest that the significant fluctuations in REEs may be primarily controlled by water-rock interactions. Considering the whole-rock major and trace element contents, as well as the trace element features of garnet, we found that whole-rock Na, Al, Ti and Sr elements, garnet Ti, Zr and Nb elements exhibit significant differences between the inner and outer skarn. These characteristics can be used to distinguish the boundary between the rock body and carbonate during the skarnification process. Full article