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Identification of Geochemical Anomalies Using a Memory-Augmented Autoencoder Model with Geological Constraint 基于地质约束的记忆增强自编码器模型地球化学异常识别
IF 5.4 2区 地球科学
Natural Resources Research Pub Date : 2024-12-11 DOI: 10.1007/s11053-024-10433-2
Tonghui Luo, Zhongli Zhou, Long Tang, Hao Gong, Bin Liu
{"title":"Identification of Geochemical Anomalies Using a Memory-Augmented Autoencoder Model with Geological Constraint","authors":"Tonghui Luo, Zhongli Zhou, Long Tang, Hao Gong, Bin Liu","doi":"10.1007/s11053-024-10433-2","DOIUrl":"https://doi.org/10.1007/s11053-024-10433-2","url":null,"abstract":"<p>The identification and mapping of geochemical anomaly patterns have emerged as a more precise and efficient approach for mineral exploration, with deep learning algorithms being extensively employed in this realm. However, existing methodologies require further investigation regarding model interpretability and correlation with established mineral control factors. This paper proposes a regional geochemical anomaly identification method based on the memory-augmented autoencoder (MemAE), incorporating geological controlling factors. Firstly, the MemAE model is introduced to address the excessive generalization capability of the traditional autoencoder (AE) model. Secondly, utilizing multifractal singularity theory, a nonlinear functional relationship between faults and mineral deposits is established. This relationship reveals the controlling effect of faults on mineralization and it is incorporated as a constraint term in the MemAE's loss function. Finally, the constructed geochemical anomaly identification model is employed to delineate prospective mineralization areas, with comparative studies conducted on AE, MemAE, and geologically constrained MemAE models. The results demonstrate that the geologically constrained MemAE exhibits superior performance, achieving an AUC of 0.802. The eight delineated mineralization prospective areas show strong concordance with actual distributions. The proposed method, which considers geological controlling factors, effectively enhances model interpretability and demonstrates excellent geochemical anomaly identification capabilities. Consequently, this approach can be considered a viable methodology for mineral exploration.</p>","PeriodicalId":54284,"journal":{"name":"Natural Resources Research","volume":"24 5 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142805443","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Forecasting Copper Price with Multi-view Graph Transformer and Fractional Brownian Motion-Based Data Augmentation 基于多视图图变压器和分数布朗运动的数据增强预测铜价
IF 5.4 2区 地球科学
Natural Resources Research Pub Date : 2024-12-09 DOI: 10.1007/s11053-024-10442-1
Qiguo Sun, Xibei Yang, Meiyu Zhong
{"title":"Forecasting Copper Price with Multi-view Graph Transformer and Fractional Brownian Motion-Based Data Augmentation","authors":"Qiguo Sun, Xibei Yang, Meiyu Zhong","doi":"10.1007/s11053-024-10442-1","DOIUrl":"https://doi.org/10.1007/s11053-024-10442-1","url":null,"abstract":"<p>Copper price forecasting is crucial for both investors and governments due to its significant economic impact. Recently, machine learning techniques have been widely employed to construct copper price forecasting models, demonstrating high forecasting accuracy. However, there are two main limitations in these models: (1) the lack of ability to capture the non-Euclidean relationships among numerous features; and (2) using purely data-driven algorithms, which lack tractability and physical effectiveness. To address these challenges, this study proposes a multi-view graph transformer (MVGT) model for 1-month ahead copper price forecasting. MVGT integrates a parametric fractional Brownian motion module, which provides conditional expectations of future copper prices for data augmentation. Moreover, to comprehensively capture the non-Euclidean structure of copper features, MVGT introduces five graph generation methods. Furthermore, a multi-view graph transformers model is designed to provide structural copper feature embeddings, and an attention-based multi-view fusion mechanism is developed to enable the MVGT to comprehensively understand market trends while focusing on the most influential views. Experimental results on the COMEX and LME datasets demonstrate that MVGT outperforms baseline models in terms of training efficiency, forecasting accuracy, and generalization.</p>","PeriodicalId":54284,"journal":{"name":"Natural Resources Research","volume":"1 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142793853","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Evaluating Productivity in Opencast Mines: A Machine Learning Analysis of Drill-Blast and Surface Miner Operations 露天矿山生产率评估:钻爆和露天采矿作业的机器学习分析
IF 5.4 2区 地球科学
Natural Resources Research Pub Date : 2024-12-03 DOI: 10.1007/s11053-024-10429-y
Geleta Warkisa Deressa, Bhanwar Singh Choudhary
{"title":"Evaluating Productivity in Opencast Mines: A Machine Learning Analysis of Drill-Blast and Surface Miner Operations","authors":"Geleta Warkisa Deressa, Bhanwar Singh Choudhary","doi":"10.1007/s11053-024-10429-y","DOIUrl":"https://doi.org/10.1007/s11053-024-10429-y","url":null,"abstract":"<p>Productivity in opencast mining, particularly in drill-blast (DB) and surface miner (SM) operations, is crucial for optimizing efficiency and reducing costs. These operations are directly affected by fragmentation, which in turn impacts equipment utilization, loading cycle times, and downstream operations. This study analyzed field data such as rock properties, machine parameters, blast design results, and post-blast fragmentation size (0.15–0.82 m), with 0.45 m identified as the optimal fragmentation size for a 12 m<sup>3</sup> shovel bucket. Traditional productivity assessments often use simplistic models that fail to capture the complexities of mining operations. To address this, an explainable machine learning (ML) model was developed, integrating fragmentation size, rock and machine parameters, and geometric factors to evaluate DB and SM operations in opencast coal mines. Various ML techniques, such as artificial neural network (ANN), random forest regression (RFR), gradient boosting regressor (GBT), and support vector regression (SVR), were employed to analyze these parameters. Among these, the RFR model demonstrated the highest accuracy, with a coefficients of determination (<i>R</i><sup>2</sup>) of 99.5% for training and 99.2% for testing in DB datasets, and 99.9% for training and 99.5% for testing in SM datasets. Furthermore, the RFR model had the lowest root mean square error, mean absolute error, and mean absolute percentage error of 10.35, 4.788, and 2.1% for DB training datasets, and 5.53, 1.75, and 1.5% for SM training datasets, respectively, underscoring its superior performance. Using SHAP (Shapley Additive exPlanations), the study identified key productivity drivers: SM cycle time, diesel consumption, and coal face length. Fragmentation size, resulting from blasting, was also found to influence shovel efficiency and overall productivity significantly. This paper highlights the effectiveness of ensemble ML models in predicting and analyzing complex productivity dynamics in opencast mining.</p>","PeriodicalId":54284,"journal":{"name":"Natural Resources Research","volume":"13 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2024-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142760011","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Freeze–Thaw Response of Permeability and Absorption Channel Structure and Moisture Distribution in Different Coal Ranks 不同煤级渗吸通道结构及水分分布的冻融响应
IF 5.4 2区 地球科学
Natural Resources Research Pub Date : 2024-11-27 DOI: 10.1007/s11053-024-10425-2
Lei Qin, Sinyin Lv, Shugang Li, Hui Wang, Pengfei Liu, Miao Mu, Jiawei Li
{"title":"Freeze–Thaw Response of Permeability and Absorption Channel Structure and Moisture Distribution in Different Coal Ranks","authors":"Lei Qin, Sinyin Lv, Shugang Li, Hui Wang, Pengfei Liu, Miao Mu, Jiawei Li","doi":"10.1007/s11053-024-10425-2","DOIUrl":"https://doi.org/10.1007/s11053-024-10425-2","url":null,"abstract":"<p>Low-permeability coal seams are widely distributed in China, with significant differences in coal ranks and properties. Identifying an effective method for nitrogen fracturing is an urgent challenge. To study the impact of coal ranks on fracturing, lignite, bituminous coal, and anthracite were used in liquid nitrogen freeze–thaw experiments. Low-field nuclear magnetic resonance was used to measure <i>T</i><sub><i>2</i></sub> curves, porosity, and pore throat distribution during the freeze–thaw process. The fractal characteristics of pore microstructure and the dynamic evolution of unfrozen water were analyzed. The results indicate that liquid nitrogen freeze–thaw promotes pore development in coal of all ranks. Lignite, with its high moisture content and abundant pore structure, showed the most significant transformation effect, followed by bituminous coal and anthracite. After a single freezing–thawing cycle, the pore growth rates of lignite, bituminous coal, and anthracite are 135.98%, 104.17%, and 53.65%, respectively. Additionally, the transformation effect on different types of pores shows different characteristics. The distribution of adsorption pore throats slightly decreases, while the increase in distribution of permeable pore throats follows the order: lignite &gt; bituminous coal &gt; anthracite. The fractal dimension D<sub>A</sub> of adsorption pores is less than 2, indicating no fractal characteristics, while the fractal dimension D<sub>S</sub> of permeable pores is greater than 2.9, showing significant fractal characteristics. During the freezing process, lignite exhibits the greatest decrease in unfrozen water content, while during the thawing process, all three coal samples show a sudden increase in unfrozen water content, with bituminous coal showing the smallest increase, only 1836.49.</p>","PeriodicalId":54284,"journal":{"name":"Natural Resources Research","volume":"199 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2024-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142753772","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Nanopore Structure Evolution in Acid- and Alkali-Treated Coal Under Stress: Insights from SAXS Analysis 酸处理和碱处理煤在应力作用下的纳米孔结构演变:SAXS 分析的启示
IF 5.4 2区 地球科学
Natural Resources Research Pub Date : 2024-11-25 DOI: 10.1007/s11053-024-10426-1
Yaoyu Shi, Xiangchun Li, Yihui Pang, Baisheng Nie, Jianhua Zeng, Shuhao Zhang, Xiaowei Li, Qingdong Qu
{"title":"Nanopore Structure Evolution in Acid- and Alkali-Treated Coal Under Stress: Insights from SAXS Analysis","authors":"Yaoyu Shi, Xiangchun Li, Yihui Pang, Baisheng Nie, Jianhua Zeng, Shuhao Zhang, Xiaowei Li, Qingdong Qu","doi":"10.1007/s11053-024-10426-1","DOIUrl":"https://doi.org/10.1007/s11053-024-10426-1","url":null,"abstract":"<p>Research on the effects of acidic and alkaline solutions and stress on coal’s pore structure has traditionally focused on larger scales, leaving a gap in understanding nanoscale impacts. This study utilized a self-developed small-angle X-ray scattering (SAXS) miniature loading system and in situ synchrotron SAXS to investigate nanopore evolution under varying pH conditions and external stress. By analyzing the scattering data obtained, we investigated the changes in the internal nanopore structures of coal soaked in solutions with different pH values and subjected to external loading. The results showed that all coal samples exhibited negative Porod deviations. The degree of negative Porod deviation decreased after the coal samples were soaked in acidic solutions, while it increased after soaking in alkaline solutions. Negative Porod deviations increased notably under destructive loading. There are significant differences in the changes of internal nanopore structures in coal samples treated with chemical solutions of different pH values. The porosity and specific surface area of coal samples decreased significantly after soaking in acidic solutions, while coal samples treated with alkaline solutions showed substantial increases in both parameters. During subsequent loading, the samples soaked in acidic solutions exhibited minimal changes, whereas those treated with alkaline solutions experienced notable alterations. Chemically treated coal samples also showed increased sensitivity to external stress, especially in smaller nanopores. The study identifies three stages of nanopore evolution under stress: minor damage, compression, and rupture.</p>","PeriodicalId":54284,"journal":{"name":"Natural Resources Research","volume":"34 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2024-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142697055","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Petrophysical Characteristics of the Paleocene Zelten Formation in the Gialo Oil Field, Sirte Basin, Libya 利比亚苏尔特盆地 Gialo 油田古新世 Zelten 地层的岩石物理特征
IF 5.4 2区 地球科学
Natural Resources Research Pub Date : 2024-11-21 DOI: 10.1007/s11053-024-10416-3
Bassem S. Nabawy, Emad Abd El Aziz, Saad Mogren, Adel Kamel Mohamed, Habeeb Farag, Elkhedr Ibrahim, S. M. Talha Qadri
{"title":"Petrophysical Characteristics of the Paleocene Zelten Formation in the Gialo Oil Field, Sirte Basin, Libya","authors":"Bassem S. Nabawy, Emad Abd El Aziz, Saad Mogren, Adel Kamel Mohamed, Habeeb Farag, Elkhedr Ibrahim, S. M. Talha Qadri","doi":"10.1007/s11053-024-10416-3","DOIUrl":"https://doi.org/10.1007/s11053-024-10416-3","url":null,"abstract":"&lt;p&gt;This work evaluated the hydrocarbon potentiality and petrophysical properties of the Paleocene Zelten Formation in the Libyan Sirte Basin. It aimed to delineate the influence of the microfacies composition of the studied sequence on the reservoir characteristics. The study was based on petrographical and petrophysical data derived from six wells. The petrophysical data included well-logging data (gamma-ray, caliper, PEF, sonic, neutron porosity, density, spectral gamma-ray, and deep and shallow resistivity) and conventional core data (density, porosity, permeability, and fluid saturations). Lithologically, the carbonate Zelten reservoir sequence is composed of four non-clastic lithofacies: (1) argillaceous limestone; (2) calcareous shale; (3) fossiliferous limestone, sometimes slightly dolomitic; and (4) dolomite lithofacies. Petrographically, four microfacies were defined: (1) oolitic grainstone; (2) dolomitic bioclastic packstone; (3) dolomudstone; and (4) ferruginated bioclastic wackestone microfacies. The petrophysical characteristics of the studied sequence were deduced by analyzing well-logging data sets to evaluate the effective and total porosities, shale volume, fluids saturations, and thickness of the net pay. Moreover, detailed processing of the core dataset was applied to estimate the average reservoir pore radius (R&lt;sub&gt;35&lt;/sub&gt;) and the reservoir quality parameters. Petrophysically, the Zelten reservoir was sliced into four reservoir rock types (RRTs), with the RRT1 group having much better reservoir quality than the other RRTs; it forms the topmost parts of the Zelten Formation, averaging 78 ft thick and primarily composed of oolitic grainstone microfacies. It has fair to very good permeability (2.3–479.0 mD), poor to excellent porosity (8.1–41.8%), good to tight reservoir quality parameters, and micro- to meso-pore sizes (0.97–8.08 µm). Besides, the oil saturation was in the range of 0.70–44.6%. In contrast, the RRT4 is a compact reservoir rock type; it primarily consists of ferruginated bioclastic wackestone microfacies and is characterized by excellent porosity (10.5–34.8%), fair to tight permeability (0.013–1.4 mD), tight reservoir quality index (RQI) and flow zone indicator (FZI) values (0.011 and 0.153 µm, respectively), micropore sizes (0.05–0.34 µm), and 0.9–31.5% oil saturation. The petrophysical characters of the RRT2-3 samples have transitional reservoir quality (average porosity = 22.7 and 24.8 %, average permeability = 12.34 and 2.789 mD, RQI&lt;sub&gt;av&lt;/sub&gt; = 0.198 and 0.091 μm, FZI&lt;sub&gt;av&lt;/sub&gt; = 0.588 and 0.291 μm, and R&lt;sub&gt;35&lt;/sub&gt; = 1.29 and 0.53 μm for RRT2 and RRT3, respectively) between the tight RRT4 and the best RRT1 reservoir samples. Also, the Zelten reservoir was sliced vertically into six zones, with the best reservoir quality assigned for zone 5 (net-pay thickness = 348.3 ft, average porosity = 18.7%, average water saturation = 48.3%, and shale volume = 27.9%). The proposed integrated petrophysical and ","PeriodicalId":54284,"journal":{"name":"Natural Resources Research","volume":"4 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142678492","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Research on Coal Reservoir Pore Structures: Progress, Current Status, and Advancing 煤储层孔隙结构研究:进展、现状和推进
IF 5.4 2区 地球科学
Natural Resources Research Pub Date : 2024-11-19 DOI: 10.1007/s11053-024-10411-8
Kai Wang, Lin Guo, Chao Xu, Wenjing Wang, Tong Yang, Yuanyuan Hu, Yongwang Yuan
{"title":"Research on Coal Reservoir Pore Structures: Progress, Current Status, and Advancing","authors":"Kai Wang, Lin Guo, Chao Xu, Wenjing Wang, Tong Yang, Yuanyuan Hu, Yongwang Yuan","doi":"10.1007/s11053-024-10411-8","DOIUrl":"https://doi.org/10.1007/s11053-024-10411-8","url":null,"abstract":"<p>Coalbed methane (CBM) storage and transport are facilitated by an intricate multi-scale pore structure. It is of great significance to study the characteristics of the pore structure and its role in CBM storage and transport in order to enhance CBM extraction, prevent CBM disasters, and improve the efficiency of CO<sub>2</sub> geological storage. Here, we review the current progress in coal reservoir pore structure research worldwide based on 8199 published papers on \"coal pore structure\" identified from the Web of Science Core Collection database. Using a bibliometric method with high-frequency core keywords as important database quantitative indices, five clusters with high-frequency keywords were selected as the core content to provide a comprehensive review of the progress of research on the pore structure of the coal body. The findings indicate that, with global attention focused on the storage of greenhouse gases, such as CO<sub>2</sub>, and clean energy extraction of CBM, research on pore structure of coal rock reservoirs has increased rapidly since 2010, with studies from China, the USA, Australia, Poland, and Japan the most abundant. With the development of testing technology, research on the basic parameters of coal pore structure, the intrinsic mechanism of pore formation, and the factors influencing the evolution of pore structure has evolved from the macroscopic to the micromolecular level, and from qualitative descriptions to quantitative or semi-quantitative characterization. From keyword analysis, it is evident that the control mechanisms of pore structures with regard to adsorption–desorption–diffusion–seepage of CBM in coal reservoirs have received considerable attention. The development of technologies such as molecular simulation provides important technological support for analyzing the intrinsic mechanisms competitive CO<sub>2</sub>, CH<sub>4</sub>, and N<sub>2</sub> adsorption in coal–rock reservoirs at the molecular level. The development of molecular dynamics simulations and digital imaging technology will provide crucial support for the quantitative <i>in situ</i> characterization of pore structures and other physical parameters of unconventional reservoirs, such as coal and rock. Moreover, studying the microscopic mechanisms of gas adsorption and fluid flow in porous systems under extreme conditions (e.g., high temperature, high pressure, ultra-microscale) has become a research frontier in this field.</p>","PeriodicalId":54284,"journal":{"name":"Natural Resources Research","volume":"250 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142673408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Risk-Based Optimization of Post-Blast Dig-Limits Incorporating Blast Movement and Grade Uncertainties with Multiple Destinations in Open-Pit Mines 基于风险的露天矿爆破后掘进限界优化,纳入多目的地爆破运动和品位的不确定性
IF 5.4 2区 地球科学
Natural Resources Research Pub Date : 2024-11-18 DOI: 10.1007/s11053-024-10428-z
Samer Hmoud, Mustafa Kumral
{"title":"Risk-Based Optimization of Post-Blast Dig-Limits Incorporating Blast Movement and Grade Uncertainties with Multiple Destinations in Open-Pit Mines","authors":"Samer Hmoud, Mustafa Kumral","doi":"10.1007/s11053-024-10428-z","DOIUrl":"https://doi.org/10.1007/s11053-024-10428-z","url":null,"abstract":"<p>Dig-limits optimization is one of the most important steps in the grade control process at open-pit mines. It aims to send blasted materials to their optimal destinations to maximize the profitability of mining projects. Grade and blast movement are key uncertainties that affect the optimal determination of dig-limits. This paper presents an integrated workflow for optimizing dig-limits under grade and blast movement uncertainties. The proposed methodology incorporates these uncertainties into the grade control process to enhance material classification and destination optimization, thereby minimizing ore loss and dilution. A multivariate geostatistical simulation workflow is developed to capture spatial uncertainties in grade distribution and blast movement distance and direction. By applying projection pursuit multivariate transformation and sequential Gaussian simulation for modeling blast movement distances at all locations and flitches within the bench section, the anticipated D-like shape from blasting is reproduced, and uncertainty is quantified. The maximum expected profit method effectively determines optimal material destinations under uncertainty improving overall mining profitability. The proposed risk-based dig-limits optimization model accounts for mining equipment selectivity, irregular bench shapes, and varying orebody orientations, resulting in operational and economically viable dig-limits. A case study on a porphyry copper deposit demonstrated the significant impact of blast movement on ore loss and dilution, emphasizing the need for accurate blast movement modeling and its integration into grade control procedures. By accounting for differential blast movement, the proposed workflow ensures reliable post-blast material classifications, reducing suboptimal decisions, thus improving project profitability and operational efficiency.</p>","PeriodicalId":54284,"journal":{"name":"Natural Resources Research","volume":"1 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2024-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142670798","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Correlation Between and Mechanisms of Gas Desorption and Infrasound Signals 气体解吸与次声信号之间的相关性和机制
IF 5.4 2区 地球科学
Natural Resources Research Pub Date : 2024-11-18 DOI: 10.1007/s11053-024-10417-2
Sijie Yang, Yuanping Cheng, Yang Lei, Zhuang Lu, Xiaoxi Cheng, Hao Wang, Kuo Zhu
{"title":"Correlation Between and Mechanisms of Gas Desorption and Infrasound Signals","authors":"Sijie Yang, Yuanping Cheng, Yang Lei, Zhuang Lu, Xiaoxi Cheng, Hao Wang, Kuo Zhu","doi":"10.1007/s11053-024-10417-2","DOIUrl":"https://doi.org/10.1007/s11053-024-10417-2","url":null,"abstract":"<p>Coal and gas desorption, as a major form of gas energy release, is a key factor in triggering coal and gas outbursts. Therefore, studying the physical characteristics during coal and gas desorption is essential for understanding the development process of coal and gas outbursts. Based on gas dynamics during coal particle gas desorption, this study established a connection between gas desorption and infrasound signals, elaborating on the generation mechanism of infrasound signals during coal particle gas desorption and validating the feasibility of the theory through experimental data, thereby demonstrating the spontaneous occurrence of subsonic tremors during coal particle gas desorption. Combining observational data, it was found that the peak value of infrasound signals generated during desorption experiments is correlated positively with the initial pressure; while, the dominant frequency of infrasound signals is influenced by the proportion of intergranular pores and fractures within the experimental vessel. To further validate the theory of subsonic generation, a mathematical model describing pressure oscillations within intergranular pores, thereby explaining the mechanism of subsonic tremors, was established. The model confirms that the generation and characteristics of infrasound signals are controlled by the parameters of intergranular pores in coal samples. The model effectively simulates changes in the characteristics of infrasound signal tremors during desorption under different conditions, confirming that the physical properties of intergranular pores are crucial factors influencing the generation of infrasound signals and their characteristics during coal and gas desorption.</p>","PeriodicalId":54284,"journal":{"name":"Natural Resources Research","volume":"80 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2024-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142670828","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Lateritic Ni–Co Prospectivity Modeling in Eastern Australia Using an Enhanced Generative Adversarial Network and Positive-Unlabeled Bagging 利用增强型生成式对抗网络和正向无标记袋装法建立澳大利亚东部红土镍钴矿远景模型
IF 5.4 2区 地球科学
Natural Resources Research Pub Date : 2024-11-18 DOI: 10.1007/s11053-024-10423-4
Nathan Wake, Ehsan Farahbakhsh, R. Dietmar Müller
{"title":"Lateritic Ni–Co Prospectivity Modeling in Eastern Australia Using an Enhanced Generative Adversarial Network and Positive-Unlabeled Bagging","authors":"Nathan Wake, Ehsan Farahbakhsh, R. Dietmar Müller","doi":"10.1007/s11053-024-10423-4","DOIUrl":"https://doi.org/10.1007/s11053-024-10423-4","url":null,"abstract":"<p>The surging demand for Ni and Co, driven by the acceleration of clean energy transitions, has sparked interest in the Lachlan Orogen of New South Wales for its potential lateritic Ni–Co resources. Despite recent discoveries, a substantial knowledge gap exists in understanding the full scope of these critical metals in this geological province. This study employed a machine learning-based framework, integrating multidimensional datasets to create prospectivity maps for lateritic Ni–Co deposits within a specific Lachlan Orogen segment. The framework generated a variety of data-driven models incorporating geological (rock units, metamorphic facies), structural, and geophysical (magnetics, gravity, radiometrics, and remote sensing spectroscopy) data layers. These models ranged from comprehensive models that use all available data layers to fine-tuned models restricted to high-ranking features. Additionally, two hybrid (knowledge-data-driven) models distinguished between hypogene and supergene components of the lateritic Ni–Co mineral systems. The study implemented data augmentation methods and tackled imbalances in training samples using the SMOTE–GAN method, addressing common machine learning challenges with sparse training data. The study overcame difficulties in defining negative training samples by translating geological and geophysical data into training proxy layers and employing a positive and unlabeled bagging technique. The prospectivity maps revealed a robust spatial correlation between high probabilities and known mineral occurrences, projecting extensions from these sites and identifying potential greenfield areas for future exploration in the Lachlan Orogen. The high-accuracy models developed in this study utilizing the Random Forest classifier enhanced the understanding of mineralization processes and exploration potential in this promising region.</p>","PeriodicalId":54284,"journal":{"name":"Natural Resources Research","volume":"64 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2024-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142665230","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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