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Digital geology and quantitative mineral exploration ZHAO Pengda, CHEN Yongqing 2021, 28(3): 1-5.  DOI: 10.13745/j.esf.sf.2021.1.22 Abstract ( 918 )   HTML ( 31 )   PDF (999KB) ( 668 )   The concept of mineral exploration, or so-called “exploration philosophy” in the Western countries, is the thoughts, methodology, technology, goal and organization guiding mineral exploration. The three basic elements of mineral exploration are “what to find”, “where to find” and “how to find”. As these elements evolve with time, it provides a powerful force to gradually changing the concept, methodology and technology of mineral exploration. Innovative ideas of mineral exploration come from the continuing scientific exploration and development keeping pace with the times. Digital geology, the data analysis component of geoscience, is the combination of mathematical geology and information technology.Geological data science uses the general methodology of data science to study geology based on the characteristics of geological data and the needs of geological work. And digital mineral exploration is the application of digital geology in mineral exploration to reduce uncertainty in ore prospecting. Figures and Tables | References | Related Articles | Metrics

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What are Mathematical Geosciences and its frontiers? CHENG Qiuming 2021, 28(3): 6-25.  DOI: 10.13745/j.esf.sf.2021.1.17 Abstract ( 1424 )   HTML ( 50 )   PDF (4924KB) ( 1156 )   The lack of a unified definition of Mathematical Geology or Mathematical Geosciences as an interdisciplinary field of natural science, may lead to misunderstanding of the subject or not even treating it as an independent discipline. This has, to some extent, affected the development of the field of Mathematical Geosciences. As a decade-long (2004-2016) lead administrator of the International Association for Mathematical Geosciences (IAMG), the author of this paper has witnessed and led the transformation of IAMG from Mathematical Geology to Mathematical Geosciences, and has overseen the updates of the names and contents of various journals and conferences related to IAMG. In 2014, a new definition and disciplinary connotation of Mathematical Geosciences were put forward by the author in the IAMG President Forum in Newsletters. In 2018, in celebrating the 50th anniversary of IAMG, the definition, connotation, contribution, and leading-edge researches of Mathematical Geosciences were discussed in detail in the Handbook of Mathematical Geosciences. The current paper reviews the main contributions, scientific progress, frontiers, and public education of the field under the framework of the new discipline of Mathematical Geosciences. On the basis of reviewing the developmental history of the discipline, the difference between Mathematical Geosciences and Mathematical Geology is analyzed, and the significant contributions of Mathematical Geosciences to the advances in geodesy, geophysics, plate tectonics theory, geochemistry, sedimentology, geographic information system, and mineral resources and energy forecasting are introduced. The frontiers of Mathematical Geosciences are discussed from a viewpoint of the challenges in international Earth Sciences, while new growth directions of Mathematical Geosciences are proposed, such as quantitative research on the complexity of the Earth, big data, deep machine learning, and complex artificial intelligence. This paper aims to answer such questions: What is Mathematical Geosciences? What contributions are made by mathematical geoscientists to advance Earth Sciences? And, Is the discipline of Mathematical Geosciences at the forefront of Geosciences? Figures and Tables | References | Related Articles | Metrics

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Metallogenic background, process and exploration as one: A trinity concept for prospecting for super-large ore deposits CHEN Yongqing, MO Xuanxue 2021, 28(3): 26-48.  DOI: 10.13745/j.esf.sf.2021.1.11 Abstract ( 755 )   HTML ( 23 )   PDF (5566KB) ( 876 )   Super-large ore deposits are giant storages for one or some kinds of mineral resources. About Roughly 70%-85% of world’s known ore reserves are concentrated in super-large deposits that account for 10% of the world’s total in terms of deposit numbers. Thus the discovery of super-large deposits is of great importance to the socioeconomic development of a country. The geological background of a super-large deposit is the basis of its formation; the metallogenic process is the key to its mineralization; and conceptual exploration, evaluation is the fundamental approach to its discovery. In this paper we attempt to explore the idea of trinity—metallogenic background, process and exploration as one—for prospecting for super-large deposits. For hidden and new types of super-large deposits, ore prospecting based on the trinity concept is the key to the success of mineral exploration. According to the theory of Earth dynamics, we define the geological anomaly area (e.g., various kinds of plate boundaries) with a complex crustal structure as the feasible ore prospecting area; within this area, the subarea associated with key metallogenic factors (source, transport, storage, cover) is defined as the favorable ore prospecting area according to the concept of metallogenic system; inside the favorable ore prospecting area, the district with variable mineralization types is defined as the ore prospective area based on the concept of ore-forming series. According to the theory of self-organization, metallogenic system in an ore-rich area follows the power-law distribution, hence it requires multi-scale oriented ore prospecting; while the uncertainty of single information on geology and mineralization warrants collection of comprehensive ore-forming information. Metallogenic system-based mineral exploration, combined with prediction model based on comprehensive ore-forming information, is the most effective way to determine the possible mineralization area as it takes account of two factors simultaneously: the mechanism of mineralization (essence) and the correlation (phenomenon) between ore deposit and various ore controlling factors. The search for super-large deposits should be regarded as a scientific exploration from the viewpoint of geoscience. It involves first integrating the ore-forming information extracted from various sources, including geological, geochemical, geophysical, and remote sensing data; then transforming the obtained information of key ore-forming processes and parameters into spatial information of ore prospecting; next identifying and confirming such spatial information according to the target selection model; and finally delineating the ore-prospecting target area of varying scales, from global ore deposit zones to metallogenic provinces to ore-rich areas. The trinity concept lays a theoretical, methodological foundation for future exploration of super-large deposits and provides a reasonable engineering scheme for the application of direct prospecting technology in ore exploration. Figures and Tables | References | Related Articles | Metrics

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Data science-based theory and method of quantitative prediction of mineral resources ZUO Renguang 2021, 28(3): 49-55.  DOI: 10.13745/j.esf.sf.2020.12.1 Abstract ( 674 )   HTML ( 48 )   PDF (1178KB) ( 626 )   Quantitative prediction of mineral resources needs the support of data science urgently as the field has now changed from qualitative to quantitative, from data sparse to data intensive. On the basis of previous studies, this paper discusses data science-based theory and method of quantitative prediction of mineral resources. The theoretical basis of such theory and method are correlation theory and anomaly theory. The former, via supervised machine learning algorithms, provides a theoretical basis for the prediction of undiscovered mineral deposits by mining the correlations between geological prospecting big data and locations of mineral deposits; the latter, by detecting geological anomaly present in geological prospecting big data, provides a theoretical basis for the prediction of mineral deposits. This data science-based approach emphasizes the importance of geological prospecting big data and machine learning algorithms, as the type, diversity, quality and accuracy of geospatial data can affect the final prediction results, whilst machine learning algorithms can improve the efficiency of feature extraction and information integration fusion. This paper presents the workflow of quantitative prediction of mineral resources by the data science-based theory and method, introduces the methods for feature extraction and prospecting information fusion, and discusses potential prediction uncertainty inherent in such theory and method. Figures and Tables | References | Related Articles | Metrics

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Quantitative prediction of molybdenum-copper polymetallic mineral resources in the Xindalai grassland-covered area of Inner Mongolia based on geological anomalies XIA Qinglin, ZHAO Mengyu, WANG Xiaochen, LENG Shuai, LI Tongfei, XIONG Shuangcai 2021, 28(3): 56-66.  DOI: 10.13745/j.esf.sf.2021.1.16 Abstract ( 309 )   HTML ( 7 )   PDF (4496KB) ( 294 )   The Xindalai grassland-covered area of Inner Mongolia, in the western part of the Erlian-Dongwuqi molybdenum-copper polymetallic belt of the Paleo-Asian metallogenic domain, distributes endogenous granophile metal deposits with favorable ore-forming conditions, such as the Wulandele copper-molybdenum deposit and the Zhunsujihua molybdenum deposit. However, due to the influence of large herbage and Quaternary overlays, all kinds of mineralization/ore indicators in this area are indirect, mixed, concealed, weak or incomplete, causing considerable uncertainty and hazard to ore prospecting and exploration. Therefore, it is necessary to develop a quantitative prediction model to guide ore prospecting in the overlay area. In this paper, guided by the geological anomaly theory developed originally by Zhao et al., we analyzed the diversity of mineralization in Xindalai and its adjacent areas and summarized the vertical distribution of mineralization data. Using the S-A multifractal filtering model, the overlay interference on soil geochemical and high-precision magnetic survey data is reduced, and weak anomalies from deep sources are identified and extracted. The extracted information on faults, Jurassic granitic rocks, dykes and rock mass-wall rock contact zones, as well as on PC1-PC2 element combination anomalies, high-precision geomagnetic anomalies, and geographic location (X-Y coordinates) of metallogenic and non-metallogenic units, were taken as input variables using the random forest (RF) prediction method. The SMOTE sampling technology was used to overcome training sample insufficiency caused by limited number of ore deposits/occurrences in the grassland-covered area. Eventually the comprehensive geo-anomalies closely related to mineralization were quantified after five hundred iterations in the RF simulation. The simulation results show that the average OOB error and ACU value were 2.26% and 0.972, respectively, and 88.46% of known ore deposits/occurrences correspond to geo-anomalies with metallogenic advantage ≥0.783, demonstrating the effectiveness of the prediction method. In order to further reduce the exploration risk, we performed a risk-return analysis to show that 25 out of 26 ore deposits/occurrences were distributed in the positive return range, and only 3 ore occurrences were associated with medium to high risk values. On this basis, we used the metallogenic advantages of geo-anomalies associated with low-risk, high-return areas to re-map the grassland-covered area and ultimately delineated the preferable ore-finding district. Figures and Tables | References | Related Articles | Metrics

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Constructing knowledge graph for the porphyry copper deposit in the Qingzhou-Hangzhou Bay area: Insight into knowledge graph based mineral resource prediction and evaluation ZHOU Yongzhang, ZHANG Qianlong, HUANG Yongjian, YANG Wei, XIAO Fan, JI Junjie, HAN Feng, TANG Lei, OUYANG Chong, SHEN Wenjie 2021, 28(3): 67-75.  DOI: 10.13745/j.esf.sf.2021.1.2 Abstract ( 649 )   HTML ( 41 )   PDF (2928KB) ( 590 )   Knowledge graphs, fundamental to artificial intelligence, describe the real world in graphic forms using a language that can be understood by both humans and machines. This paper presents a case study on the construction of knowledge graph for porphyry copper deposit. The raw text data were collected and integrated from six selected porphyry and porphyry-skarn copper deposits in the Qinzhou-Hangzhou Bay metallogenic belt, one of the key metallogenic belts of China. The entities, relations and attributes in the text are labeled and extracted in reference to the conceptual model of porphyry copper deposit. The resulted knowledge graph has the basic application functions. As part of a planned integrated knowledge graph—from a single deposit, through upper-geared metallogenic series, to top metallogenic province (belt)—the present study may be extended toward understanding and improving future way of mineral resource prediction and evaluation. The interrelationship among the earth system, the metallogenic system, the exploration system, and the prediction and evaluation system (ES-MS-ES-PS) should be fully understood, and a knowledge graph for the ES-MS-ES-PS system is essential. The key scientific and technological challenges to attain such a large-scale knowledge graph for the ES-MS-ES-PS system thus include system of progressive association of domain ontology and knowledge graph, automation technology for constructing large-scale domain ontology and knowledge graph, self-evolution and complementary techniques for embedding multi-modal correlation data into knowledge graph, and ES-resource prediction theory and methods based on knowledge graph, big-data mining and artificial intelligence. Figures and Tables | References | Related Articles | Metrics

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Considerations on big data-based genetic mineralogical research LI Shengrong, SHEN Junfeng, LI Lin, ZHANG Huafeng 2021, 28(3): 76-86.  DOI: 10.13745/j.esf.sf.2021.1.18 Abstract ( 460 )   HTML ( 15 )   PDF (2411KB) ( 520 )   With the launching of the Deep-time Digital Earth program (DDE) by the International Union of Geosciences, it is of great significance to carry out the construction of big data platforms for genetic mineralogy and in-depth data mining research. We suggest that priority should be given to constructing big data platform for mineral phylogenetic history, mineral typomorphism and mineral genetic classification researches, which involves building big data models, developing big data processing methods, and extracting information from the big data processing results. Big data-based phylogenetic history (or mineral evolution) research should be conducted on several strategic key metals (e.g, lithium, gallium, uranium, cerium and platinum, etc.) and mineral classes to analyze their accumulation and dispersion patterns in different tectonic units and geological eras as a basis for key metal ore prediction. It is possible to reveal the nature, distribution, scale and radiation effect of important geochemical, geophysical and biological events during the Earth’s geologic history by studying mineral evolution through in-depth mining of mineralogical big data and researching mineral phylogenetic history. Big data platform for genetic mineralogical research should be employed in finalizing the classification of “explicit” genetic mineral groups and related map compilation and, later on, in carrying out the classification of “implicit” genetic mineral groups and related map compilation. Attention should be paid to cultivating talents for big data-based interdisciplinary mineralogical research, while big data-based genetic mineralogical research should be pursued at the graduate level. Figures and Tables | References | Related Articles | Metrics

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Magnetite geochemical big data: Dataset construction and application in genetic classification of ore deposits HONG Shuang, ZUO Renguang, HU Hao, XIONG Yihui, WANG Ziye 2021, 28(3): 87-96.  DOI: 10.13745/j.esf.sf.2021.1.10 Abstract ( 630 )   HTML ( 28 )   PDF (2244KB) ( 513 )   Magnetite is an oxide mineral commonly found in magmatic, hydrothermal and sedimentary deposits. Its geochemical elemental composition is largely dependent on temperature, oxygen fugacity and other physicochemical conditions, and can reveal the ore-forming environment and indicate the genetic type of ore deposits. The major and trace elements in magnetite have been used for genetic classification of ore deposits since the 1960s. However, due to genetic diversity of ore deposits and complexity of geochemical composition of magnetite from the same type of ore deposits, the applicability of magnetite discrimination diagrams is often limited based on limited magnetite geochemical data. In this study, we collected from various publications a large amount of magnetite geochemical data (n=7388) determined by electron probe microanalysis (EPMA) and laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) to construct, preliminarily, two magnetite geochemical big data sets, and subsequently established a new genetic classification model based on random forest algorithm, and explored the importance of trace elements in the genetic classification of ore deposits. The results show that magnetite big data mining based on a machine learning algorithm can effectively distinguish the main types of ore deposit, with an overall classification accuracy up to 95%. Because the LA-ICP-MS magnetite data set contains high quality data on many trace elements, the classification accuracy is higher based on LA-ICP-MS data than on EPMA data, indicating the classification accuracy of ore deposit is affected by the number of trace elements in magnetite and by the accuracy of data analysis. At the same time, we found element V plays an important role in the classification of ore deposits. In addition, analyzing new magnetite data using the new discrimination model can yield the probability of each ore type and effectively distinguish the genetic type of ore deposit. Figures and Tables | References | Related Articles | Metrics

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A two-way forecasting method based on numerical simulation of mineralization process for the prediction of concealed ore deposits AN Wentong, CHEN Jianping, ZHU Pengfei 2021, 28(3): 97-111.  DOI: 10.13745/j.esf.sf.2021.1.5 Abstract ( 297 )   HTML ( 11 )   PDF (5604KB) ( 304 )   In this paper, we propose a two-way forecasting method for locating blind orebodies based on numerical simulation of mineralization process and 3D quantitative predication. The parameters used in predicting blind orebodies were obtained by numerical simulation, and the methodology involves 3D geological modeling of large-scale blind orebodies, 3D quantitative prediction, numerical simulation, and two-way forecast and evaluation. Using this novel forecasting method, we established seven favorable prospective targets in a project test zone of the Yidinan gold deposit in Gansu Province. In the 3D quantitative prediction, we calculated the ore-forming probabilities of prospective blocks using the techniques of weigh of evidence and information value; by numerical simulation of mineralization process, we delineated the metallogenic favorable area based on the simulated distributions of prospective blocks with favorable pore pressures (pp values) and volumetric strain rates (vsr values). These application results show that using the two-way forecasting method can effectively reduce prediction uncertainty in the deep blind orebody prediction and evaluation. Figures and Tables | References | Related Articles | Metrics

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Primary halo zonation in and a deep orebody prediction model for the inner-outer contact zone of the Laochang Sn-Cu deposit in Gejiu ZHU Xu, YANG Rong, CHEN Yongqing, WANG Lianyue, LI Gang 2021, 28(3): 112-127.  DOI: 10.13745/j.esf.sf.2021.1.8 Abstract ( 300 )   HTML ( 7 )   PDF (5725KB) ( 324 )   The primary haloes of mineral deposits occur as envelopes around individual mineral deposits and are usually contemporaneous with mineral alteration and deposition. Zonation of primary haloes of mineral deposits is quite predictable and explicable, thus it generally provides better ore prospecting targets. Besides, primary haloes of some metal deposits may provide important insight for targeting deeply buried orebodies. The Laochang Sn-polymetallic deposit is an important member of the Gejiu giant (Sn-Cu) polymetallic deposit characterized by skarnized mineralization. The skarnized mineralization can be subdivided into endoskarn and exoskarn mineralization types based on the spatial distribution patterns. The former occurs in the inner altered intrusion zone while the latter mainly in carbonate rocks near intrusions. They have the following geochemical similarities and differences: (1) The axial zoning sequences of endoskarn and exoskarn orebodies are (from head to tail) Ag-As-Bi-Cu-F-Pb-Sn-Zn-B → Ba-Co-Cr-Ni-Sb-V → Be-Mo-W and F-B-Ba-W → Cu-Sb-Be-Cr → Sn-Pb-Zn-Ni-Ag → Co-Mo-Bi-As, respectively, indicating consistency in anomaly element but not in axial zoning sequence. (2) In endoskarn mineralization, there are three ore-forming element associations: (a) As-B-Be-Co-Sn, representing greisenized cassiterite-sulfide-tourmaline mineralization; (b) Ag-Pb-Cu-Zn, representing kerargyrite-galena-sphalerite-chalcopyrite mineralization; and (c) Mo-W, representing skarnized molybdenite-scheelite mineralization. (3) In exoskarn mineralization, there are also three ore-forming element associations: (a) Ag-Bi-Sn-Cu, representing kerargyrite-bismuthinite-stannite(cassiterite)-chalcopyrite mineralization; (b) As-Zn-Pb, representing skarnized arsenopyrite-galena-sphalerite mineralization; and (c) F-Be-W-Mo, representing greisenized fluorite-beryl-scheelite-molybdenite mineralization. The above ore-forming element associations indicate skarn mineralization involves multistage processes. Finally, on the basis of primary halo axial zoning sequence, the prediction patterns of deep orebodies in endoskarn and exoskarn zones are established, thereby providing a powerful tool for the prediction of concealed orebodies. Figures and Tables | References | Related Articles | Metrics

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A combined prediction method for reducing prediction uncertainty in the quantitative mineral resources prediction KONG Weihao, XIAO Keyan, CHEN Jianping, SUN Li, LI Nan 2021, 28(3): 128-138.  DOI: 10.13745/j.esf.sf.2021.1.6 Abstract ( 408 )   HTML ( 10 )   PDF (2828KB) ( 236 )   Mineralization is a complex physical and chemical process. In the quantitive prediction and evaluation of mineral resources, prediction uncertainties are common in the final predication results due to geologic factors, improper data collection and processing, use of empirical parameters, etc. On the basis of recognizing the sources of uncertainty, uncertainty reduction becomes a major research direction in mineral prospecting. A combined metallogenic prediction method using the forward inverse technique has proven to be an effective solution for reducing uncertainties in the geological anomaly analysis. The combined method is composed of numerical simulation of metallogenic processes based on the genetic model of deposit, and model-driven prediction and evaluation technique based on prospecting model and data. As the combined method takes into account both mineralization processes and model-driven prediction/evaluation in the geo-anomaly analysis, it reduces multiple interpretations of a single metallogenic information therefore reducing prediction uncertainty. In its core contents of analyzing metallogenic patterns and establishing prospecting models, the combined method, mainly using spatial database and geostatistics and GIS analysis techniques as well as 3D geological model building, performs weight of evidence analysis and information value evaluation of the distribution of geological variables to investigate its influence on the prediction result. The aim is to build a “3D cube prediction model” for quantitive prediction, fulfilling the goal of Location, Quantity, Probability quantification in blind orebody prospecting. In conclusion, the combined prediction method, as an important basis for delineating the “5P” prospecting areas, was born by innovatively combining two prediction methods that have complementary predictive functions and values. By doing so, a complete forward inverse combined prediction scheme is realized. We show by example that the combined method can improve accuracy and reduce uncertainties in the quantitative prediction and evaluation of mineral resources, which helps to promote the transformation of geoscience research from qualitative to quantitative. Figures and Tables | References | Related Articles | Metrics

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Resource-environmental joint forecasting in the Luanchuan mining district, China through big data mining and 3D/4D modeling WANG Gongwen, ZHANG Shouting, YAN Changhai, PANG Zhenshan, WANG Hongwei, FENG Zhankui, DONG Hong, CHENG Hongtao, HE Yaqing, LI Ruixi, ZHANG Zhiqiang, HUANG Leilei, GUO Nana 2021, 28(3): 139-155.  DOI: 10.13745/j.esf.sf.2021.1.1 Abstract ( 615 )   HTML ( 15 )   PDF (5509KB) ( 447 )   The “fourth paradigm” of the 21 st century Earth Science, the fourth industrial era and the 5G+ intelligent communication provide mineral researchers with a new opportunity to study the relationship between mining development and environmental protection. This study is based on the geoscientific theory that emphasizes the connections between geodynamic background, metallogenic process and quantitative assessment. Taking the Luanchuan mining district as an example, using geoscience big data (multi-dimensional, multi-scale geological, geophysical, geochemical, multi-temporal hyperspectral/high-resolution remote sensing, real-time mining data) platform, including deep artificial intelligence mining technology as well as 3D/4D multi-disciplinary, multi-parameter, multi-scale modeling technology, we constructed a 3D geological model, a metallogenic process model and a quantitative exploration model at the district and deposit scales, and performed quantitative prediction and assessment of the related mineral resources. The aim was to achieve dynamic assessment of high-precision 3D geo-environmental (rock, structure, hydrology, soil, etc.) protection and comprehensive development and utilization of resources in digital mines, so as to provide a scientific basis for the sustainable mineral resource development in the study area. The research results are summarized in three main aspects: (1) Application of geoscience big data in resource prediction and assessment of district. By mining geoscience big data such as 3D geological modeling, geological and geophysical forward/backward interpretation, geochemical and remote sensing data mining, etc., with use of the self-developed GeoCube2.0 software, deep target optimization and comprehensive mineral resources assessment were achieved for the Luanchuan mining district (500 km2 in area, 2.5 km deep). The predicted Mo, W and Pb-Zn-Ag resources in the mining district were 6.5, 1.5 and 5 million tons, respectively. (2) Three-dimensional geologic modeling of ore deposit and mineral exploration related to mining environment. Field data collected from the Nannihu-Sandaozhuang-Shangfang open pits and the Luotuoshan deep channel mining zones show that the spatial correlation between the NW-trending porphyry-skarn deposit/orebody and groundwater space is not high, and the NE-trending faults—usually tensional or tenso-torsional in the post-metallogenic period—are the pathway for groundwater migration. In the NW-trending Pb-Zn deposit, there are significant secondary metalloid leaching, where shallow Pb-Zn oxides and Mn-Fe minerals are associated with malachite and bloom from water erosion. There is a risk of groundwater pollution in the high-altitude Pb-Zn mining zone as well as in the Lengshui and Bailugou deposits, where NE-trending faults are developed outside of the porphyry-skarn Mo(W) deposits in the study area. (3) Geoscience model construction in intelligent digital mines for resource-environmental joint assessment and planning. A 3D geological model, with relevance to ancient mining caves, open pits, and deep laneways in the mining area, was established for large mines to provide guidance for the mining industry toward sustainable resource development. Using hyperspectral database, 3D models for both useful and harmful mineral elements were constructed to unite the mineral exploration, mining and processing processes in facilitating the recovery of harmful elements (As, Sb, Hg, etc.). And high resolution WorldView-2 images were used to gauge the distribution of Fe-containing pollutants in waste water and slag slurry of significant tailings reservoirs in protecting against surface runoff and soil pollution. Figures and Tables | References | Related Articles | Metrics

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Three-dimensional geological modeling and deep prospectivity of the Xigou Pb-Zn-Ag-Au deposit, Henan Province JIA Ran, WANG Haoran, WANG Gongwen, WANG Hao, XU Rongda, FENG Zhankui, SONG Yaowu, WANG Xiaoling, PANG Zong 2021, 28(3): 156-169.  DOI: 10.13745/j.esf.sf.2021.1.21 Abstract ( 422 )   HTML ( 15 )   PDF (6308KB) ( 454 )   With decreasing shallow mineral ore deposits in mining zones, more attention is paid to deep prospectivity as three-dimensional geological modeling technology becomes widely used in metallogenic prediction and quantitative resource evaluation. Based on geological mapping and drilling as well as geological data on the stratigraphy, lithology, structure and grade of the sampling site, we performed 3D geological modeling and geostatistical analysis using GOCAD to construct the 3D structual, orebody and stratigraphic models of the Xigou Pb-Zn-Ag-Au deposit. On the basis of the constructed geological models, a 3D attribute model of the deposit was constructed using the discrete smooth interpolation and Kriging interpolation methods, and then three prospecting targets in the mining area were delineated and evaluated. The geological knowledge-based 3D modeling study reveals: (1) The favorable indicators for ore prospecting in the Xigou Pb-Zn-Ag-Au deposit are stratum, structure, gabbro and grade. (2) The prediction method based on 3D geological modeling is scientific and effective. (3) The mid and southeast deep areas of the S139 orebody have good mineral prospecting potentials. This paper provides a reference for future breakthroughs in deep prospecting. Figures and Tables | References | Related Articles | Metrics

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Three-dimensional modeling and comprehensive quantitative mineral resources assessment: A case study of the Haoyaoerhudong gold deposit in Inner Mongolia LI Nan, CAO Rui, YE Huishou, LI Qiang, WANG Yitian, LÜ Xiping, GUO Na, SU Yuanxiang, HAO Jianrui, XIAO Yang, ZHANG Shuai, CHU Wenkai 2021, 28(3): 170-189.  DOI: 10.13745/j.esf.sf.2021.1.23 Abstract ( 381 )   HTML ( 20 )   PDF (8152KB) ( 489 )   The low-grade Haoyaoerhudong gold deposit in the Urad Middle Banner, Inner Mongolia, China is one of the largest gold deposit in the northern margin of the North China Craton. The gold orebodies are hosted by carbonaceous slate in the Bilute Formation of the Mesoproterozoic Bayan Obo Group. To enhance security of national gold mineral reserves, we conducted gold prospecting in the Haoyaoerhudong gold deposit through examinations of ore geology, lithology, metallotectonic system, and mineralization indicators. First we constructed a 3D prediction model for the Haoyaoerhudong gold deposit by 3D modeling. Next, inverted CSAMT data were used to interpret and redefine the structural framework of the orefield, including the Haoyaoerhudong syncline—a major ore-controlling structure. From the above results, predictor variables were extracted—such as the shear zone on the south side of the Haoyaoerhudong syncline, the Bilute carbonaceous slate, and the ore-controlling structure and geochemical and alteration indicators of the east pit—and an integrated 3D geological anomaly model was constructed. Finally, the weight of evidence (WOE) method was used to target the favorable deep gold mineralization areas. Our study demonstrates that the high susceptibility value area is the Halahoghous Formation (H3), into which magmatic rocks intruded and filled from both sides along the larger shear fault zone in the form of dikes while carbonaceous slates provided a chemical barrier for gold orebody. Based on the WOE result, we targeted the favorable deep ore field at the east section of the south side of the Haoyaoerhudong syncline. In addition, contrast analysis of montmorillonite prediction variables using WOE provided quantitative verification to show that geological inference of filling and metasomatism under geological structural controls is one of the most important formation mechanism of the Haoyaoerhudong gold deposit. Figures and Tables | References | Related Articles | Metrics

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Fault and intrusion control on copper mineralization in the Dexing porphyry copper deposit in Jiangxi, China: A perspective from stress deformation-heat transfer-fluid flow coupled numerical modeling XIAO Fan, WANG Kaiqi 2021, 28(3): 190-207.  DOI: 10.13745/j.esf.sf.2021.1.14 Abstract ( 370 )   HTML ( 17 )   PDF (5690KB) ( 303 )   The metallogenic mechanism of porphyry deposit is a typical multiphysics magmatic-hydrothermal process affected by stress deformation, heat transfer and fluid flow. Therefore, it is important to study the metallogenic process of porphyry deposits from the perspective of numerical modeling of metallogenic dynamics to understand the dynamic evolutionary mechanism of porphyry magmatic-hydrothermal system and its ore-forming response. The Dexing porphyry copper deposit, including the Zhushahong, Tongchang and Fujiawu orebodies, is the largest porphyry copper deposit in South China and considered to be a critically important case for studying the mineralization process of large or/and super-large porphyry deposits. Previous studies mainly addressed the ore geology, geochemistry, geochronology, isotope and ore-forming fluids of the Dexing porphyry deposit; however, only a few studies investigated the mineralization processes by numerical modeling of metallogenic dynamics. Therefore, the aim of this study was to explore the fault and intrusion controlls on mineralization in the Dexing porphyry copper deposit through numerical metallogenic modeling. Firstly, based on a geological conceptual model of copper mineralization, a geometric model characterizing the magmatic-hydrothermal system was constructed, which contains variables of shape (lengths of long and short axes) and dip angle of porphyry intrusion as well as dip angle and width of ore controlling fault. Next, based on the analysis of the coupling relationships among stress, fluidic and thermal fields affecting porphyry copper mineralization, the corresponding mathematical-physical equations were derived and a metallogenic dynamic computing model was constructed. Then, a numerical model simulating the metallogenic dynamic process was established by finite element numerical simulation. Finally, by constraining rock properties, boundary and initial conditions, stress deformation-heat transfer-fluid flow coupled numerical simulation was carried out to investigate fault and intrusion control on the copper mineralization. The main conclusions are: (1) small fault width is more likely to result in localized fractures, thereby facilitating fluid dispersion and formation of disseminated or micro-vein porphyry mineralization. (2) Larger volume and smaller dip angle of porphyry intrusion are beneficial to porphyry mineralization. (3) Compared with the Tongchang and Fujiawu orebodies, the smaller Zhushahong orebody has greater ore-forming depth but smaller mineral reserve, as its large dip angle led to faster post-magmatic cooling (therefore limiting its surface expansion), and porphyry intrusion of the nearby Zhushahong orebody limited its expansion space. This study revealed the ore-controlling mechanism of porphyry intrusion and fault structure in the Dexing porphyry copper deposit, helping to further our understanding of its genesis and ore controlling factors. Figures and Tables | References | Related Articles | Metrics

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Exploration of concealed fluorite deposit in shallow overburden areas: A case study in Elimutai, Inner Mongolia, China TANG Li, ZHANG Shouting, WANG Liang, PEI Qiuming, FANG Yi, CAO Huawen, ZOU Hao, YIN Shaobo 2021, 28(3): 208-220.  DOI: 10.13745/j.esf.sf.2021.1.7 Abstract ( 487 )   HTML ( 14 )   PDF (6569KB) ( 430 )   The Chifeng area in Inner Mongolia, China possesses a series of fracture-hosted hydrothermal vein-type fluorite deposits and is considered having a superior economic mineralization potential. In this study, we present an integrated prospecting approach integrating geological, geophysical, geochemical, and remote sensing techniques for exploration of concealed fluorite deposit in shallow overburden areas. The study area in Elimutai in the southern extension of the Shuitou fluorite belt, covered widely by Quarternary sediments, is ideal for such exploration. The fluorite orebodies in the study area show vertical zonation with, from top to bottom, distributions of silicified cap and head, main, and tail orebodies. The silicified cap in Elimutai is characterized by highly silicified breccia, secondary quartzite and quartz stockwork, whereas the head orebody contains fluorite vein. The outcrop of silicified cap is 30-50 m higher in latitude than the head orebody. The WorldView-2 remote sensing image reveals a linear distribution of ore-controlling fractures in the SN-striking northern/central segment and NNE-NE-striking southern segment. The results show the overlapping of mineralized outcrop, low-resistivity anomaly zone (by very low frequency electromagnetic (VLF-EM) analysis), positive Ca anomaly zone (by portable X-ray fluorescence (PXF) analysis), and positive F anomaly zone (by partial extraction geochemistry (PEG) analysis). The multi-anomalies can be used as indicator for the exploration and prediction of ore-controlling fractures and concealed fluorite orebody. In combination with VLF-EM mapping, the mineralized and altered outcrop zone overlaps with the SN-trending VLF low-resistivity anomaly zone, indicating the mineralization potential of the Elimutai area for concealed and semi-concealed fluorite. At the key prediction zone in Elimutai, the drill cores reveals the concealed fluorite ore well, exposing silicified cap, head orebody or narrow fractures. The overall evidence suggests that the deeper level of Elimutai is highly likely to contain the economically significant main fluorite orebody. Figures and Tables | References | Related Articles | Metrics

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Machine learning for mineral prospectivity: A case study of iron-polymetallic mineral prospectivity in southwestern Fujian ZHANG Zhenjie, CHENG Qiuming, YANG Jie, WU Guopeng, GE Yunzhao 2021, 28(3): 221-235.  DOI: 10.13745/j.esf.sf.2021.1.4 Abstract ( 903 )   HTML ( 60 )   PDF (3724KB) ( 762 )   As a rapidly evolving technology in recent years, machine learning (ML) provides a novel approach for mineral prospecting (MP). In this paper, we discuss the progress on the methodology and theory of machine learning and summarize the applications of ML in MP in the areas of pattern recognition/information mining and information integration. We also point out the difficulties and challenges of ML in MP, such as data imbalance, lack of training data, lack of uncertainty evaluation in model selection, feedback feeding, and method selection. Here, we use mineral prospecting of the Makeng-type iron deposit in southwestern Fujian, China as an example to illustrate the process of using the ML method in MP. A complete prediction procedure should include (1) establishing a metallogenic model and identifying ore controlling factors by studying metallogenic systems; (2) building an exploration model and obtaining relevant data by researching exploration systems;(3) establishing a prediction model and extracting predictive factors by researching prediction evaluation systems;(4) obtaining metallogenic probability through information integration of predictive factors using ML models;(5) evaluating uncertainties of prediction performances and results; and (6) delineating prospecting/target areas and estimating resource reserves. Lastly, a future research roadmap for developing big-data based quantitative mineral prospecting theory and methods is proposed, guided by the geological big data and Earth system theory in following the research route of earth system-metallogenic system-exploration system-prediction evaluation system. Figures and Tables | References | Related Articles | Metrics

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Application of SWIR, XRF and thermoelectricity analysis of pyrite in deep prospecting in the Xincheng gold orefield, Jiaodong Peninsula SHAO Xuewei, PENG Yongming, WANG Gongwen, ZHAO Xianyong, TANG Jiayang, HUANG Leilei, LIU Xiaoning, ZHAO Xiandong 2021, 28(3): 236-251.  DOI: 10.13745/j.esf.sf.2021.1.24 Abstract ( 456 )   HTML ( 14 )   PDF (5158KB) ( 446 )   The Jiaodong Peninsula is one of the most important gold mining districts in China, where gold deposits are typically controlled by the NE-trending fault structure involving mainly the Jiaojia, Sanshandao and Zhaoping fault zones, and secondary fault structure involving the Wangershan and Lingbei faults, etc. Much research has been done in the study area with a focus primarily on the surface and shallow metallogenic sections, not on deep metallogensis and quantitative predictions. The Xincheng gold orefield, consisting of the Xincheng, Qujia and Zhaoxian deposits, is one of the super-large gold deposits in the Jiaodong Peninsula. Owing to the Jiaojia fault zone, the scientific research deep drilling in the Zhaoxian mining zone reached below 2500 m, providing us with an excellent opportunity to study the laws of deep mineralization. In this research, utilizing the short-wave infrared (SWIR) characteristics of altered minerals, together with X-ray fluorescence spectrometry (XRF) and pyrite thermoelectricity analysis, we identified altered rocks and typical gold-bearing pyrite from different ore-forming stages. We then performed SWIR 3D quantitative analysis of the main altered mineral muscovite to reveal its ore prospecting characteristics and identify indicators for other altered minerals in the deposit. The results are: (1) The illite crystallinity and the sericite Al-OH absorption wavelength were higher (≥1.2, ≥2205 nm) near the altered rock-type orebody of the Jiaojia main fault structure and lower (0.2-1.2, 2198-2205 nm) far away from the fault structure. (2) Twenty elements were identified by XRF, and principal component and cluster analyses using these elements revealed certain correlation between the Al-OH absorption peak shift and Al, K, Si content change. (3) The pyrite thermoelectric conductivity types are mainly P-type in the structural altered rocks near the Jiaojia main fault and N-type far away from the main fault. In the Xincheng mining district, the top-to-bottom distribution of conductivity types follows the patterns of N-P→P→P-N→N→N-P→P-N and P-N→N-P for the No. I and V orebodies, respectively; whereas P-type is predominant in the Zhaoxian mining district. The denudation degree is generally between 25% and 50% in both mining districts, therefore there are still good prospects for deep prospecting at below 800 m in the Xincheng or below 1500 m in the Zhaoxian mining districts. On the whole, the metallogenic temperatures are mainly between 180-250 ℃ for P-type or 380-460 ℃ for N-type pyrite, and the orebody spatial distribution trend predicted by 3D interpolation modeling using temperature field is consistent with the prediction by 3D orebody grade model. The comprehensive research method in this paper provides new research ideas for deep mineral resource evaluation. The ideas of integrating multi-dimensional information—such as spectroscopic and geochemical data—and visualization of 3D models can be applied in the construction of quantitative mineral models. Figures and Tables | References | Related Articles | Metrics

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Triassic deposits in South China: Geological characteristics, ore-forming mechanism and ore deposit model XIE Guiqing, MAO Jingwen, ZHANG Changqing, LI Wei, SONG Shiwei, ZHANG Rongqing 2021, 28(3): 252-270.  DOI: 10.13745/j.esf.sf.2021.1.26 Abstract ( 516 )   HTML ( 18 )   PDF (4748KB) ( 642 )   South China is characterized by intensive, large-scale Mesozoic metal mineralization. The mechanism of ore formation during the Yanshanian period has been well studied. Recently, plentiful Triassic deposits have been discovered or recognized in South China, however, few studies are focused on their regional distribution pattern and ore deposit model. In this study, the geological characteristics, spatial-temporal distribution pattern and metallogeny of these Triassic deposits are summarized. So far, forty-six deposits of Late Triassic (230-200 Ma) have been discovered, mostly in five regions of South China. These deposits can be subdivided into four types based on mineralization styles. They, showing a zonal distribution from east to west, are the granite-related W-Sn deposits, the intrusion-related distal Au-Sb deposits, the Carlin-type Au deposits, and the MVT Pb-Zn deposits. The granite-related W-Sn deposits are situated to the south of the Carlin-type Au deposits. Multiple mineralization events took place within a single region as overprinting mineralization in the Indosinian and Yanshanian periods is commonly found in all five regions, and overprinting mineralization in the Caledonian and Indosinian periods was found in the Miaoershan-Yuchengling district of western Nanling and in the Laojunshan district of southeastern Yunan Province. Figures and Tables | References | Related Articles | Metrics

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On the ore-forming depth and possible maximum vertical extension of the major type ore deposits QIN Kezhang, ZHAO Junxing, FAN Hongrui, TANG Dongmei, LI Guangming, YU Kelong, CAO Mingjian, SU Benxun 2021, 28(3): 271-294.  DOI: 10.13745/j.esf.sf.2021.1.30 Abstract ( 998 )   HTML ( 85 )   PDF (6391KB) ( 2030 )   Based on a large number of field investigations and comparative studies of typical mineral deposits, and in considerations of the existing problems and practical needs of deep ore prospecting and evaluation, we first review in this paper the depth of ore deposits for the main deposit types, from the ultra-deep magmatic deposits controlled by large-scale magmatic accumulation in the middle-to-lower crust, to the deep, middle and shallow magmatic-hydrothermal deposits controlled by fluid permeability in the middle and upper crust. On this basis, we attempt to explore the maximum vertical extension of the major type ore deposits, and discuss the constrained depth of mineralization, degree of denudation, and possible vertical extension at depth for the copper-nickel (-chromite-PGE) deposits represented by the Bushveld and Voisey’s Bay, the porphyry copper deposits represented by Qulong, the orogenic gold deposits represented by Muruntau, and the Jiaodong gold province. The depth and vertical extension of hypogene mineralization associated with magmatic ore deposit can vary greatly; for example, the depth of mineralization in a layered igneous complex can extend to 20 km, with vertical extension ranging from 6 to 8 km. The maximum depth of magmatic-hydrothermal deposits is at the bottom of the lower crust where fluid penetration occurs. Oroganic gold deposits have the greatest depth, about 12-15 km, followed by pegmatite and granite deposits; porphyry deposits are in the middle, about 2-6 km; and the epithermal Au-Ag deposits have the shallowest depth of less than 1 km to the surface. The corresponding vertical extension of these deposits ranges in 4-7 km, 2-3 km, and 1 km, respectively. The controlling factors and some indicators are reviewed, such as high permeability of ore accumulating structural space, peak of mineralization, and suitable preservation conditions. Future research on the depth of mineralization may focus on such issues including how to determine a reasonable and uniform estimation method for the depth (pressure) of hypogene mineralization, as well as the theoretical basis, judgement markers and comprehensive identification method for determining the maximum depth and vertical extension of deposits. Figures and Tables | References | Related Articles | Metrics

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Modern science and technology in metallogenic and prospecting model studies ZENG Qingdong, DI Qingyun, XUE Guoqiang, WANG Gongwen, JING Linhai 2021, 28(3): 295-308.  DOI: 10.13745/j.esf.sf.2021.1.3 Abstract ( 486 )   HTML ( 16 )   PDF (3432KB) ( 724 )   To ensure sustainable development of resources, exploration and exploitation of deep underground resources is an important strategic choice for many countries. Whether there are high-quality mineral resources underground is the premise of deep prospecting. While an ideal metallogenic model has great theoretical significance for guiding the construction of prospecting model, establishing a reasonable prospecting model has great practical significance for guiding deep ore prospecting. With the continuing development of modern science and technology, various new technologies have been used in geological research and exploration. Presently, some new techniques such as mineral in-situ U-Pb dating and in-situ compositional and isotopic analyses have played an important role in the study of metallogenic models, guiding researchers with renewed focus to building new metallogenic models; and some geophysical and geochemical exploration techniques also play an important role in model building by providing a more reliable basis for deep ore exploration. The application of modern science and technology such as metallogenic theory, integrated geophysical-geochemical analysis, etc., is the present and future trend in mineral prospecting. Figures and Tables | References | Related Articles | Metrics

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Construction and demonstration of an ore prospecting model for the Lala copper deposit in Huili, Sichuan CHEN Hui, LIN Lujun, PANG Zhenshan, CHENG Zhizhong, XUE Jianling, TAO Wen, MA Yixing, GONG Lingming, SHEN Hongtao 2021, 28(3): 309-327.  DOI: 10.13745/j.esf.sf.2021.1.29 Abstract ( 373 )   HTML ( 19 )   PDF (13886KB) ( 551 )   The prediction theory and methodology of ore prospecting were developed from an in-depth study of 129 typical deposits in China. The prediction method was verified to be effective, especially for initial ore prospecting. Using this method, a geological model of ore prospecting can be established by combining the internal (geochemical characteristics of elements) and external (types of geological processes) control factors for mineralization. The main components of the prediction model include the metallogenic geological body, structure and structural plane and the characteristics of the metallogenic process. This paper takes the Lala copper deposit in the Huili area, Sichuan Province, as a typical example to illustrate in detail the application of this method in deep ore prospecting of hydrothermal deposits. The Huili area is located in the western margin of the Yangtze Plate, where the regional metallogenic geological conditions are superior and a series of unique Fe-Cu deposits were formed due to the superposition of multi-period tectonic events. In recent years, great prospecting breakthroughs and progress have been made in the deep and peripheral areas of the Lala copper deposit. In this paper, we determined that the early ore-forming geological body is the ore hosting volcanic rock (albitite of the Hekou Group), and the main metallogenic structural control is the interface between basic (intermediate) volcanic and sedimentary rocks and the possible volcanic vent. In the period of hydrothermal superposition, the metallogenic geological body was speculated to be a deep concealed intrusion, and the metallogenic structural controls are mainly folds, faults and fissures. On the basis of summarizing the mineralization characteristics, a geological model of ore prospecting in the Lala copper deposit was established. Together with the results of geological and geophysical explorations, the southern part of Hongnipo was delineated as the ore prospecting target area where a thick, large orebody was later found by drilling verification, which opened up the regional prospecting space. Figures and Tables | References | Related Articles | Metrics

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A geochemical method for finding concealed ore deposits in bedrock outcrop area: Application of tectono-geochemical survey CHENG Zhizhong, YUAN Huixiang, PENG Linlin, LU Guo’an, JIA Xiangxiang, BING Mingming, LIN Chenggui 2021, 28(3): 328-337.  DOI: 10.13745/j.esf.sf.2021.1.20 Abstract ( 704 )   HTML ( 21 )   PDF (3296KB) ( 546 )   Tectono-geochemical survey is effective for collecting information on deep mineralization in bedrock outcrop area. In this article, the basic concepts and the development of tectono-geochemistry are systematically introduced. We propose a multi-point sampling method particularly useful for collecting rock (tectonic rock) samples associated with deep mineralization to ensure proper sample representation and data uniformity. Specifically, within each sampling unit of a survey grid, multiple “sub-samples” are collected mainly from fracture zones, fissures, altered rocks and mineralized rocks, and combined into one sample. For example, in a 1∶50000 tectono-geochemical survey carried out in the Xihe area of Gansu Province, 6-8 “sub-samples” were collected in each 500 m×500 m sampling unit and altogether 2967 samples were obtained from the survey grid. In the final analysis, 19 elements were analyzed, including Au, Ag, Pb and Zn, and the location of Au geochemical anomaly was more accurately determined. The Au orebodies were subsequently discovered through exploration. In another 1∶10000 survey in the periphery of the Jiangxi Yanbei tin (Sn) deposit, we collected 4620 sub-samples from fracture and fissure, using 100 m×100 m grid sampling unit, which resulted in 934 samples for the final analysis to delineate the geochemical anomalies of Sn and other elements. The delineated Sn geological anomaly was verified by drilling and the deep conceal tin orebodies were found. The above results show that the tectono-geochemical survey of different scales can have fruitful application in the discovery of concealed deposits in the bedrock outcrop area, such as in finding Carlin type gold deposits in Southeast Yunnan and volcanic rock covered deposits in the southeast coastal region. Figures and Tables | References | Related Articles | Metrics

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Cobalt occurrence and ore-forming process in the Chambishi deposit in the Zambian Copperbelt, Central Africa LU Yiguan, TU Jiarun, SUN Kai, QIN Peng, WANG Huaqing, HE Shengfei, ZHANG Hang, GONG Penghui, GUO Shuo, FANG Ke, HE Wenyan 2021, 28(3): 338-354.  DOI: 10.13745/j.esf.sf.2021.1.25 Abstract ( 474 )   HTML ( 15 )   PDF (4966KB) ( 446 )   The Chambishi Cu-Co deposit is one of the important giant Cu-Co deposits in Copperbelt province, Zambia, Central Africa, consisting the Main, West and Southeast orebodies. Its ore-bearing horizon is mainly the Mindola and Kitwe formations of the Lower Roan group, and its lithology includes argillaceous slate, argillaceous quartzite, slate, quartz sandstone, etc. The existing data on the cobalt occurrence mode is relatively weak and the genesis of Co-bearing minerals is not well understood, which directly hinders cobalt prospecting in the deposit. Focusing on the Co-rich minerals in this study, we conducted EPMA, Micro-XRF and S isotope analyses to investigate the Co occurrence modes and formation mechanism of Co-bearing minerals, in the Chambishi deposit, aiming to provide a theoretical basis for the future exploration of Co resources in the region. Our study shows that cobalt occurs as stand-alone minerals (mainly carrollite and linnaeite) or in Co-bearing minerals via isomorphism. In pyrite (Py2) and pyrrhotite formed from hydrothermal fluid, the cobalt content was up to 4.9% and 1.5%, respectively. Cobalt enrichment via isomorphism is evident by the inverse proportion between Co and Fe contents and by the relatively even distribution of Co components in the Co-bearing minerals. Moreover, the Co/Ni ratio in pyrite and pyrrhotite differs between the Chambishi deposit and skarn or other deposit types. Together with the hydrogen and oxygen isotope studies of fluid inclusions in the hydrothermal mineralization stage, it is implied that the Co-rich ore-forming fluid might not be magmatic-hydrothermal fluid but medium-high temperature metamorphic-hydrothermal fluid. The δ34S values of bornite from the West orebody and pyrrhotite from the Southeast orebody were 6‰-6.9‰ and 7.2‰-12.6‰, respectively, indicating that thermochemical sulfate reduction is the main formation mechanism of reductive sulfur in the Chambishi deposit; the similar δ34S values is also an indication of late metamorphism in the sulfide minerals. Based on this and previous studies, we suggest that the main mineralization stage of cobalt is closely related to the Lufilian orogeny. During the orogenic process, Co, Cu and other metal elements tend to enrich in the medium-high temperature metamorphic hydrothermal fluid. The hinge area formed by a NE-SW compression and the connecting area of specific strike faults can be the favorable prospecting targets for cobalt, and the pyrite-pyrrhotite assemblage in the hydrothermal veins can be used as mineral markers for cobalt prospecting. Figures and Tables | References | Related Articles | Metrics

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Estimation of the extend of granitoid exhumation in the Weiya-Tianhu area: Insight into ore prospecting in the Central Tianshan region, Xinjiang LI Jilin, CHEN Zhengle, ZHOU Taofa, HAN Fengbin, ZHANG Wengao, HUO Hailong, LIU Bo, ZHAO Tongyang, HAN Qiong, LI Ping, ZHENG Jiaxing, CHEN Guimin 2021, 28(3): 355-378.  DOI: 10.13745/j.esf.sf.2021.1.9 Abstract ( 248 )   HTML ( 6 )   PDF (5620KB) ( 220 )   The Weiya-Tianhu granitoid area is located on the Central Tianshan Terrane, Xinjiang, southeast of the Central Asian Orogenic Belt (CAOB), where Late Paleozoic-Early Mesozoic magmatic activities were widespread and the strategic key mineral Weiya V-Ti magnetite is produced. This paper reports the detailed petrographic observations of the region. Based on these observations, the compositions of amphiboles and biotites from the Weiya, Tianhu, and Shaquanzinan granitoids were obtained by electron microprobe analysis (EMPA) to constrain the crystallization controlling factors for the three granitoids. The constrained controlling factors such as temperature, pressure, oxygen fugacity, water content and Fe provide references for analyzing the physicochemical conditions of magmatic mineralization and ore prospecting in the region. The EMPA data show that the amphiboles are rich in Mg, Ca and Na, poor in K, and belong to calcic amphiboles. The biotites have the characteristics of high Mg, Ti, Al and K contents and low Si and Na contents, which suggests a magnesia origin. The chemical compositions of amphiboles and biotites revealed their host magma to be the calc-alkaline orogenic rock series from a hybrid crustal-mantle source, attributed probably to partial melting of mantle wedge and continental crust under the tectonic setting of plate subduction. The crystallization temperature and pressure of the Shaquanzinan quartz diorite, Weiya monzonitic granites and moyites, and Tianhu granodiorites, calculated by geothermometric method, were 651-753 ℃ and 31-79 MPa, 762-833 ℃ and 85-215 MPa, 668-812 ℃ and 31-117 MPa, respectively. The magmatic oxygen fugacity lgf(O2) in the three granitoids at crystallization varied from -15.7 to -9.4, with high water content in the melt during amphibole crystallization. Therefore, it is suggested that the granitoids in the region have the characteristics of high temperature, low pressure, high oxygen fugacity, water-rich and high Fe index, which are beneficial to elemental enrichment in ore-forming fluid and hence favoring Fe mineralization. The intrusive depth of these granitoids was further assessed by Al-in-hornblende barometry. The results show that the extend of granitoid exhumation is between 2.2-5.5 kilometers in the region, where the rates of uplifting and exhumation differ significantly. Together with the known ore distribution on land surface, it is proposed that Fe prospectivity is highly favorable at depth in the Tianhu granodiorite area. Figures and Tables | References | Related Articles | Metrics

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The Ag-Sn-Cu polymetallic minerogenetic series and prospecting direction in the western Gangdese belt, Tibet ZHENG Youye, CI Qiong, GAO Shunbao, WU Song, JIANG Xiaojia, CHEN Xin 2021, 28(3): 379-402.  DOI: 10.13745/j.esf.sf.2021.1.19 Abstract ( 312 )   HTML ( 9 )   PDF (8093KB) ( 350 )   The Gangdese belt is the largest copper polymetallic metallogenic belt in China. A historical breakthrough has been made in porphyry-copper polymetallic prospecting by the discovery of a series of large-giant deposits, including the Qulong and Jiama deposits, in the eastern Gangdese belt. In contrast, very little geological research has been done in the western Gangdese belt due to the complex tectonic background and poor road conditions. The western Gangdese belt has different crustal structure and properties from its eastern counterpart, where heterogeneous mantle properties, crust-mantle interaction, and the large volcanic rock cover led to great uncertainty and controversy over its genetic type and ore prospecting potential. In this contribution, with the substantial support of the Ministry of Science and Technology and the China Geological Survey, we made great progress or breakthroughs in clarifying the regional metallogenesis and in the discovery of new rock types, mineral species and deposits, through the application of the geo-anomaly theory developed by academician Zhao Pengda, and through a series of technological innovations, target selection, and target explorations. We discovered a number of Ag-Sn-Au-Cu-Pb-Zn-W deposits with medium to large prospecting prospects, such as the Bangbule Pb-Zn-Ag-Cu, Balong Ag-Pb-Zn-Sn, Dajiacuo Ag-Pb-Zn, Nuocang Pb-Zn-Ag-W, and Sangmola Sn-Au deposits. We also found very different metallogenic processes of the eastern and western Gangdese belt. In the western Gangdese belt, in addition to the traditional porphyry Cu-Mo-Au and skarn Fe-Pb-Zn-Cu(Ag) deposits, the continental (sub-)volcanic rock-related epithermal Ag-Sn(Au) polymetallic deposits (especially Ag-Sn or independent Ag deposits) have the highest prospecting potentials. This deposit type is mainly controlled by the coupling of ancient basement, thrust-nappe structure, sub-volcanic structure, sub-volcanic rocks, and late Paleozoic terrane. The geochemical anomaly elements are mainly Ag, Pb, Zn, Sn, Cu, Au, As, Sb, Mn, and so on, among which the rich elements Ag, Sn and Au have characteristic geochemical anomalies, therefore they can be distinguished from simple skarn and magmatic-hydrothermal deposits. These deposits are closely related to the stage and genesis of volcanic magmatic activities, and mainly distributed in the Gangdese volcanic magmatic arc, and arc-back fault uplift zone. Thus, six metallogenic series were recognized as (1) the porphyry Cu-Au series related to late Triassic arc magmatism; (2) the skarn-epithermal Fe-Ag-Pb-Zn (Sn) series to early Cretaceous arc magmatism; (3) the skarn Fe-Cu-Pb-Zn(Ag) series to late Cretaceous magmatism; (4) the porphyry skarn Fe-Cu-Mo-Pb-Zn(Ag) series to Paleocene Eocene intermediate acid intrusive rocks; (5) the epithermal Ag-Pb-Zn(Sn-Au) series to Paleocene continental (sub-)volcanic rocks; and (6) the porphyry skarn epithermal Cu-Mo-Au-Pb-Zn-Ag series to Miocene magmatism. These metallogenic series define the mineral species, prospecting types, and prospecting direction of the western Gangdese, and objectively demonstrate its resource potential. According to the mineralization condition, distribution of known deposits, and prospecting potentials, five ore clusters were further delineated in the western Gangdese. They are the Longgeer Pb-Zn-Fe-Cu, Nixiong-Ria Fe-Cu, Zhunuo-Luobuzhen Cu-Mo-Au, Chagele-Nuocang Ag-Sn-Pb-Zn-Cu-Mo, and Rebuka Ag-Sn-Pb-Zn-Pb-Zn ore clusters. In particular, the ore-rich Zhunuo-Luobuzhen and Chagele-Nuocang areas show great prospecting potentials. They will become the most important Cu and Ag-Sn polymetallic exploration bases in the western Gangdese belt, hereto providing a decision-making basis and direction for further prospecting and exploration in the region. Figures and Tables | References | Related Articles | Metrics

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Influencing factors of mineral resources development in the economically underdeveloped regions of China: Assessment of the Wumeng Mountain area using the Geodetector tool ZHANG Yuhan, ZHANG Shouting, ZHAO Yu 2021, 28(3): 403-411.  DOI: 10.13745/j.esf.sf.2021.1.12 Abstract ( 512 )   HTML ( 8 )   PDF (2074KB) ( 139 )   After the eradication of absolute poverty in China in 2020, alleviating relative poverty will become the core task of poverty alleviation and development in the future. The country’s relatively poor areas possess rich mineral resources, but the resource advantage has not been effectively transformed into economic gains due to the fragile natural environments and low industrialization in these areas. Here we describe an indicator system based on a systematic analysis of the influencing factors for mineral resources development in the relatively poor areas. The influencing factors inlude mineral resources reserves, capital investment, indexes of ecological-environmental importance, traffic dominance, water shortage, industrialization level and topographic relief. Using the Geodetector tool, we analyzed the spatial distribution of mineral resources in the Wumeng Mountain area to assess the influence of each factor. The results show that resource reserve is the most direct determining factor of mineral resources development, controlling basically the spatial distribution of mineral resources development activities in the Wumeng Mountain area; investment in fixed assets comes in second, followed by indexes of ecological-environmental importance and topographic relief, as each has an influence coefficient of about 0.44; traffic dominance has slightly lower influence coefficient than the above three indicators, whereas water shortage and industrialization level have weak impacts. Accordingly, we suggest the following measures for developing mineral resources in the relatively poor areas: Strengthen basic geological survey and mineral exploration; Further tap into the potential of mineral resources; Implement preferential policies in special fund arrangement; Encourage and guide mining investment; Vigorously support green development of mining industry; Strengthen transportation infrastructure; and Promote transformation of resource advantage into economic development advantage. Figures and Tables | References | Related Articles | Metrics

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Key elements and human health: Is China’s arable land selenium-deficient? WANG Xueqiu, LIU Qingqing, LIU Hanliang, HU Qinghai, WU Hui, WANG Wei 2021, 28(3): 412-423.  DOI: 10.13745/j.esf.sf.2021.1.13 Abstract ( 741 )   HTML ( 14 )   PDF (3943KB) ( 655 )   Everything on Earth, living or non-living, is made from one or a combination of the 92 naturally occurring chemical elements. Life survival depends on the bioavailability of these essential elements at appropriate concentrations and proportions. A comparison between the element concentration in human blood and the corresponding baseline element concentration in arable soil shows a very good correlation for 40-50 key elements. The essential element selenium (Se) has a dual character, that both Sn deficiency and excess are harmful for human health. Previous researches concluded that Se deficiency was predominant in China. In this work, we collected the China geochemical baseline data from 3382 grid sampling sites covering the entire country. We found the proportion of Se deficient area to be 21.1% according to the WHO limit (0.1 mg/kg) or 31.6% by the Chinese guideline standard (0.125 mg/kg). The Se-deficient regions are distributed in Tibet and Inner Mongolia where grain crops are scarcely produced. No Se deficiency is observed in the arable plains of the 9 major grain producing regions except the Hetao plain. Specifically, Selenium is enriched (>0.4 mg/kg) in the Pearl delta, Guangxi, Chengdu, and middle and lower Yangtze plains; between marginal and appropriate levels (0.125-0.4 mg/kg) in the Sanjiang, Northern, Northeastern and Guanzhong (Central Shaanxi) plains; and deficient (<0.125 mg/kg) in the Hetao plain. The study shows that the spatial distribution of Se-poor soils is geographically situated in a discrete NE-SW-trending belt from the eastern part of Inner Mongolia to the Qinghai-Tibet Plateau, controlled mainly by geological background, parent rocks, soil types and geographical landscapes. Figures and Tables | References | Related Articles | Metrics