The biotite pegmatites in the Shangdan domain of the North Qinling orogenic belt contain economic concentrations of U, constituting a low-grade, large-tonnage pegmatite-hosted uraniferous province. Uraninite is predominant and ubiquitous ore mineral and coffinite is common alteration mineral after initial deposit formation. A comprehensive survey of the uraninite and coffinite assemblage of the Chenjiazhuang, Xiaohuacha, and Guangshigou biotite pegmatites in this uraniferous province reveal the primary magmatic U mineralization and its response during subsequent hydrothermal events. Integrating the ID-TIMS (Isotope Dilution Thermal Ionization Mass Spectrometry) 206Pb/238U ages and U-Th-Pb chemical ages for the uraninites with those reported from previous studies suggests that the timing of U mineralization in the uraniferous province was constrained at 407–415 Ma, confirming an Early Devonian magmatic ore-forming event. Based on microtextural relationships and compositional variation, three generations of uranium minerals can be identified: uaninite-A (high Th-low U-variable Y group), uranite-B (low Th-high U, Y group), and coffinite (high Si, Ca-low U, Pb group). Petrographic and microanalytical observations support a three-stage evolution model of uranium minerals from primary to subsequent generations as follows: (1) during the Early Devonian (stage 1), U derived from the hydrous silicate melt was mainly concentrated in primary magmatic uaninite-A by high-T (450–607 °C) precipitation; (2) during the Late Devonian (stage 2), U was mobilized and dissolved from pre-existing uraninite-A by U-bearing fluids and in situ reprecipitated as uraninite-B under reduced conditions. The in situ transformation of primary uraninite-A to second uraninite-B represent a local medium-T (250–450 °C) hydrothermal U-event; and (3) during the later low-T (100–140 °C) hydrothermal alteration (stage 3), U was remobilized and derived from the dissolution of pre-existing uraninite by CO2- and SiO2-rich fluids and interacted with reducing agent (e.g., pyrite) leading to reprecipitation of coffinite. This process represents a regional and extensive low-T hydrothermal U-event. In view of this, U minerals evolved from magmatic uraninite-A though fluid-induced recrystallized uraninite-B to coffinite, revealing three episodes of U circulation in the magmatic-hydrothermal system.
The weak classifier ensemble algorithms based on the decision tree model, mainly include bagging (e.g., fandom forest-RF) and boosting (e.g., gradient boosting decision tree, eXtreme gradient boosting), the former reduces the variance for the overall generalization error reduction while the latter focuses on reducing the overall bias to that end. Because of its straightforward idea, it is prevalent in MPM (mineral prospectivity mapping). However, an inevitable problem in the application of such methods is the hyperparameters tuning which is a laborious and time-consuming task. The selection of hyperparameters suitable for a specific task is worth investigating. In this paper, a tree Parzen estimator-based GBDT (gradient boosting decision tree) model (TPE-GBDT) was introduced for hyperparameters tuning (e.g., loss criterion, n_estimators, learning_rate, max_features, subsample, max_depth, min_impurity_decrease). Then, the geological data of the gold deposit in the Xiong ‘ershan area was used to create training data for MPM and to compare the TPE-GBDT and random search-GBDT training results. Results showed that the TPE-GBDT model can obtain higher accuracy than random search-GBDT in a shorter time for the same parameter space, which proves that this algorithm is superior to random search in principle and more suitable for complex hyperparametric tuning. Subsequently, the validation measures, five-fold cross-validation, confusion matrix and success rate curves were employed to evaluate the overall performance of the hyperparameter optimization models. The results showed good scores for the predictive models. Finally, according to the maximum Youden index as the threshold to divide metallogenic potential areas and non-prospective areas, the high metallogenic prospect area (accounts for 10.22% of the total study area) derived by the TPE-GBDT model contained > 90% of the known deposits and provided a preferred range for future exploration work.
Natural gas hydrates are a strategic energy resource in China. The China Geological Survey has discovered segregated hydrate mass formations under the seepage mechanism in the South China Sea through exploration, and gas hydrates occur in nodular, massive, and vein formations in silty clay sediment. Previous work has focused on the analysis of sediment mechanical properties with respect to the uniform distribution of natural gas hydrates in pore spaces, but the mechanical properties of hydrate-bearing sediments containing segregated hydrate masses are not well understood. Spherical hydrates are used to characterize nodular hydrates, a method is proposed for the preparation of sediment samples containing segregated hydrates masses, and a series of triaxial compression tests are carried out on the samples containing spherical hydrates with two kinds of particle sizes at a certain volume fraction. The paper presents triaxial stress–strain curves for the samples containing spherical hydrates. A model for predicting elastic modulus is established. The results present two distinct stages in the triaxial compression tests of silty clay sediments containing spherical hydrates; they also show that the elastic moduli predicted by the model are in good agreement with the experimental results when the model parameters are set at α = 0.5 and β = −0.21. These results provide fundamental mechanical parameters for the safety evaluation of strata containing segregated gas hydrates.
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