Genesis, metallogenic model, and prospecting prediction of the Nibao gold deposit in the Guizhou Province, China

Song, Weifang; Zheng, Lulin; Liu, Jianzhong; Cao, Shengtao; Xie, Zhenglei

doi:10.1007/s11631-022-00575-6

Cited by 9 publications

(12 citation statements)

References 31 publications

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“…Following the decratonization of the NCC, the Luxi district transitioned to a stable marine sedimentary environment [38,39]. The Neoproterozoic Tumen group formed in the vicinity of the Tan-Lu fault zone while extensive Paleozoic strata consisting of carbonate, shale, and clastic rocks are widely exposed in the Luxi district [15,33,40]. During the Mesozoic, with the decratonization of the NCC, the Luxi district underwent a process of fault basin formation, terrestrial volcanic-sedimentary rock construction, and intrusive rock emplacement [33,41,42] overlain by Cenozoic strata.…”

Section: Geological Settingmentioning

confidence: 99%

“…The stratigraphy of the Tongjing ore district primarily consists of the Neoarchaean Taishan group, Neoproterozoic Tumen group, and Cambrian sequences (Figures 2 and 3a). The Taishan group is overlain by the Tumen group (Tongjiazhuang formation) in an unconformable contact (Figure 3a) and both are concealed strata [15]. The Tongjiazhuang formation is composed of alternating layers of sandstone and shale with thin-bedded limestone exhibiting localized skarnization (Figure 3a).…”

Section: Deposit Geologymentioning

confidence: 99%

“…The ore district extensively exposes the Cambrian sequences (Changqing and Jiulong groups) which serve as the primary host rocks for mineralization (Figures 2 and 3a; [49]). The Changqing group (Zhushadong and Mantou formations) and Jiulong group (Zhangxia and Gushan formations) consist mainly of sandstone and shale intercalated with thick-bedded dolomite and (dolomitic) limestone (Figure 3a; [15]). These strata extend in a NW-SE (300 • ) direction and dip 10-30 • SW [5].…”

Section: Deposit Geologymentioning

confidence: 99%

“…The Yi'nan Tongjing Au-Cu deposit, located in the central-southern part of the Luxi district (Figures 1b and 2), constitutes a typical skarn deposit that provides a promising avenue to explore the interplay between magmatic/hydrothermal fluid evolution and Au-Cu mineralization. It has attracted significant scholarly attention and represents an exemplary Au-Cu deposit in the Luxi district [5,[14][15][16][17][18][19][20][21]. Despite past research efforts, a comprehensive understanding of the evolution path of ore-forming fluids and crucial information pertaining to the physicochemical conditions of mineralization is still lacking.…”

Section: Introductionmentioning

confidence: 99%

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Genesis of the Yi’nan Tongjing Gold–Copper Skarn Deposit, Luxi District, North China Craton: Evidence from Fluid Inclusions and H–O Isotopes

Cai,

Liu,

Zhang

et al. 2023

Minerals

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The Luxi district presents an exceptional research area for the investigation of the significant role played by magma exsolution fluids in the mineralization process of Au–Cu deposits. A particularly noteworthy occurrence within this region is the Yi’nan Tongjing Au–Cu skarn deposit, situated in the central-southern part of the Luxi district. This deposit primarily occurs in the contact zone between the early Cretaceous Tongjing complex and the Proterozoic to Cambrian sequences. The ore formation process observed in this deposit can be categorized into three distinct stages: (I) thermal metamorphism, (II) prograde alteration, and (III) retrograde alteration. The retrograde alteration stage is further divided into four sub-stages: late skarn (III-1), oxide (III-2), sulfide (III-3), and late quartz-calcite (III-4). It is primarily during the III-3 sub-stage that gold mineralization occurs. Petrographic analysis has identified three types of fluid inclusions (FIs) within garnet, quartz, and calcite grains. These include liquid-rich two-phase aqueous FIs, vapor-rich two-phase aqueous FIs, and halite-bearing multi-phase FIs. The homogenization temperatures of fluid inclusions from stages II, III-3, and III-4 range between 430–457 °C, 341–406 °C, and 166–215 °C (first to third quartiles), respectively. The garnet samples from stage II exhibit hydrogen and oxygen isotope compositions (δ18OH2O = 6.8‰ and δD = −73‰) that are indicative of a typical magma source. However, the hydrogen and oxygen isotopes of sub-stages III-1, III-2, and III-3 (δ18OH2O = 7.32‰ to 9.74‰; δD = −107‰ to −81.9‰) fall below the magma water box while the hydrogen and oxygen isotope values of III-4 (δ18OH2O = −5.3‰ to −0.9‰ and δD = −103.8‰ to −67‰) tend to move towards the meteoric water line. Furthermore, the ore-forming fluid displays characteristics of a mixture between the crustal and mantle fluids. The Tongjing complex occurred along a weakened fault zone, initiating a process of thermal metamorphism upon contact with the wall rock. This thermal metamorphism resulted in the formation of diverse assemblages, including hornfels, reaction skarns, and skarnoids. Subsequently, the upward movement of ore-forming fluids triggered exsolution which led to the establishment of a high-temperature, medium-salinity NaCl–H2O system with a single phase at depths ranging from 1–3 km. This marked the formation of the prograde alteration stage. Afterward, the ore-forming fluid underwent water–rock interactions and the admixture of meteoric water at a depth of 1–2 km. These processes facilitated phase separation, commonly referred to as boiling, resulting in the transformation of the ore-forming fluid into higher salinity fluids and lower-density gases. This evolutionary transition ultimately induced the precipitation and liberation of gold and copper from the fluid.

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Section: Geological Settingmentioning

confidence: 99%

Section: Deposit Geologymentioning

confidence: 99%

Section: Deposit Geologymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Genesis of the Yi’nan Tongjing Gold–Copper Skarn Deposit, Luxi District, North China Craton: Evidence from Fluid Inclusions and H–O Isotopes

Cai,

Liu,

Zhang

et al. 2023

Minerals

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“…The early metallogenic prediction model is mainly a comprehensive summary of the theory and method of metallogenic prediction. Since the 1970s, many geologists have carried out a lot of research and practice on the aspects of mining area evaluation, total resource evaluation, computer programs, and evaluation methods, and they have gradually formed the theory and method system of quantitative evaluation of mineral resources [3][4][5][6][7][8][9]. In the past 30 years, with the development of computers and GIS combined with traditional methods, spatial information fusion models have been widely used in mineral quantitative prediction.…”

Section: Introductionmentioning

confidence: 99%

Prediction of Au-Polymetallic Deposits Based on Spatial Multi-Layer Information Fusion by Random Forest Model in the Central Kunlun Area of Xinjiang, China

Zhang,

Ye,

Xie

et al. 2023

Minerals

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In recent years, there has been a growing emphasis on combining intelligent prospecting algorithms, such as random forest, with extensive geological and mineral data for the purpose of quantitatively predicting exploration geochemistry. This approach holds significant importance for enhancing the accuracy of target delineation. The central Kunlun area in Xinjiang possesses highly favorable ore-forming geological conditions, offering excellent prospects for mineral exploration. However, the depletion of shallow deposits coupled with a decade-long gap in geological exploration have presented increasing challenges in the quest to discover substantial metal resources. Consequently, there is now a severe shortage of reserve assets in the region, prompting an urgent need for the implementation of new theories, methods, and technologies in mineral resource investigation and evaluation efforts. The researchers used geological and regional geochemical data to construct a random forest metallogenic discriminant model for predicting the mineralization of gold polymetallic minerals in the central Kunlun area of Xinjiang and delineating the metallogenic target area. Two different sampling methods were compared to quantitatively predict gold polymetallic mineral resources. The results indicate that the selected training samples offer higher prediction accuracy and reliability by fully capturing the complex information of the original data. The random forest model using select training samples has valuable applications in metallogenic prospect prediction and potential division due to its ability to consider the actual exploration cost and identify small areas with high potential and a high proportion of ore. This study significantly improves prediction accuracy, reduces exploration risk, and expands the use of machine learning algorithms in mathematical geology in the central Kunlun area of Xinjiang.

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Trace critical metal systems

Müller,

Groves,

Santosh

2025

Metallic Mineral Resources

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Genesis, metallogenic model, and prospecting prediction of the Nibao gold deposit in the Guizhou Province, China

Cited by 9 publications

References 31 publications

Genesis of the Yi’nan Tongjing Gold–Copper Skarn Deposit, Luxi District, North China Craton: Evidence from Fluid Inclusions and H–O Isotopes

Genesis of the Yi’nan Tongjing Gold–Copper Skarn Deposit, Luxi District, North China Craton: Evidence from Fluid Inclusions and H–O Isotopes

Prediction of Au-Polymetallic Deposits Based on Spatial Multi-Layer Information Fusion by Random Forest Model in the Central Kunlun Area of Xinjiang, China

Trace critical metal systems

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