Three−Dimensional Metallogenic Prediction with Integration of Structural Reconstruction at the Dayingezhuang Gold Deposit, Northwestern Jiaodong Peninsula
-
摘要:
矿床在形成后常被构造改造，但现有三维成矿预测中对其关注较少。笔者选择胶东半岛大尹格庄构造蚀变岩型金矿为研究对象，采用基于不规则三角网（TIN）的构造复原方法还原被断裂错断的矿体与控矿断裂的三维结构，开展复原前后的矿化空间/控矿因素对比分析并实现深边部三维成矿预测。结果表明，构造复原方法消除了断裂和矿体被错断产生的空间距离及倾角变化；复原后的矿化分布具有更强的空间自相关性，被错断区域的矿化分布由分散变为连续。此外，相同参数下，复原后的预测模型比复原前模型具有更高的性能，说明对复原后的矿化分布和控矿指标之间的关联关系表达更加显著。因此，顾及构造改造的三维成矿预测有利于预测结果的准确性，可为大尹格庄矿床深部找矿工作提供可靠参考。
Abstract:Mineral deposits are often deformed after mineralization, which is, however, less concerned in the current three−dimensional (3D) prospectivity modeling. This paper selected the Dayingezhuang structural altered rock type gold deposit as a case study and used a structural restoration method based on triangular irregular network (TIN) to reconstruct 3D orebody and ore−controlling fault, analyzed and compared the mineralization structure and ore−controlling factors before and after restoration and finally completed the 3D mineral prospectivity at depth. The results show that the structural restoration method can eliminate the variation of spatial distance and dip angle of fault and orebody caused by deformation. The reconstructed mineralization distribution has a stronger spatial autocorrelation feature that is shown as the change of scattered mineralization distribution to spatially continuous at the offset parts. In addition, the reconstructed prediction model has higher performance than that without restoration under the same parameters, indicating that the correlation between the mineralization distribution and ore control factors is more significant. Therefore, the three−dimensional metallogenic prediction modeling with integration of structural reconstruction has improved the propectivity accuracy and can provide a reliable reference for deep prospecting in the Dayingezhuang deposit.
-
Key words:
- TIN /
- structural reconstruction /
- 3D prospectivity modeling /
- Dayingezhuang gold deposit
-
-
图 2 大尹格庄矿床地质简图（Yang et al.，2016）
Figure 2.
表 1 大尹格庄金矿矿体预测概念模型表
Table 1. Conceptual model for gold prediction of the Dayingezhuang gold deposit
地质体 控矿地质因素 地质意义 表达形式 矿化分布 自身空间分布（IOre） 反映金的品位（Au）和金属量（AuMet）的空间结构。 建模：克立格法等
表达：栅格模型
指标：IOre招平主断裂面 距离场（dF） 反映成矿流体从断裂面向两侧的流动程度。 建模：距离分析
表达：栅格模型
指标：dF形态起伏
（waF、wbF）反映断裂面形态起伏变化对矿化的控制作用。 建模：形态分析
表达：栅格模型
指标：waF、wbF坡度分析（gF） 反映断裂面对含矿流体的圈闭和矿质沉淀的控制作用。 建模：形态分析
表达：栅格模型
指标：gF陡缓变化（cF） 反映断裂面由陡变缓/由缓变陡部位对矿化的控制作用 建模：形态分析
表达：栅格模型
指标：cF
下载: 导出CSV
表 2 复原前后变异函数拟合参数表
Table 2. Parameters for fitting the variance functionbefore/after the reconstruction
成矿空间 块金值C0 基台值C 空间相关度
C0/ C0+C变程a（m） 复原前 0.38 0.63 0.38 113.82 复原后 0.28 0.75 0.27 122.86
下载: 导出CSV
表 3 复原前后各向异性椭球体参数表
Table 3. Anisotropic ellipsoidal parameters before/after the reconstruction
成矿
空间方位
（°）倾伏角
（°）倾角
（°）主轴/
次主轴主轴/
次轴复原前 209.64 –5.93 39.67 1.47 3.26 复原后 201.02 –3.22 35.03 1.37 3.07
下载: 导出CSV
-
[1] 陈进, 毛先成, 刘占坤, 等. 基于随机森林算法的大尹格庄金矿床三维成矿预测[J]. 大地构造与成矿学, 2020a, 44(02): 231-241
CHEN Jin, MAO Xiancheng, LIU Zhankun, et al. Three-dimensional Metallogenic Prediction Based on Random Forest Classification Algorithm for the Dayingezhuang Gold Deposit[J]. Geotectonica et Metallogenia, 2020a, 44(02): 231-241.
[2] 陈进, 毛先成, 邓浩. 山东大尹格庄金矿床深部三维定量成矿预测[J]. 地球学报, 2020b, 41(02): 179-191
CHEN Jin, MAO Xian-cheng, DENG Hao. 3D Quantitative Mineral Prediction in the Depth of the Dayingezhuang Gold Deposit, Shandong Province[J]. Acta Geoscientica Sinica, 2020b, 41(02): 179-191.
[3] 陈建平, 吕鹏, 吴文, 等. 基于三维可视化技术的隐伏矿体预测[J]. 地学前缘, 2007, 14(05): 54-62.
CHEN Jianping, LV Peng, WU Wen, et al. A 3D method for predicting blind orebodies, based on a 3D visualization model and its application[J]. Earth Science Frontiers, 2007, 14(5): 054-062.
[4] 邓浩, 郑扬, 陈进, 等. 基于深度学习的山东大尹格庄金矿床深部三维预测模型[J]. 地球学报, 2020, 41(02): 157-165 doi: 10.3975/cagsb.2020.020501
DENG Hao, ZHENG Yang, CHEN Jin, et al. Deep Learning-based 3D Prediction Model for the Dayingezhuang Gold Deposit, Shandong Province[J]. Acta Geoscientica Sinica, 2020, 41(02): 157-165. doi: 10.3975/cagsb.2020.020501
[5] 邓浩, 魏运凤, 陈进, 等. 基于注意力卷积神经网络的焦家金矿带三维成矿预测及构造控矿因素定量分析[J]. 中南大学学报(自然科学版), 2021, 52(09): 3003-3014
DENG Hao, WEI Yunfeng, CHEN Jin, et al. Three-dimensional prospectivity mapping and quantitative analysis of structural ore-controlling factors in Jiaojia Au ore-belt with attention convolutional neural networks[J]. Journal of Central South University(Science and Technology), 2021, 52(09): 3003-3014.
[6] 李洪奎, 禚传源, 耿科, 等. 郯-庐断裂带陆内伸展构造: 以沂沭断裂带的表现特征为例[J]. 地学前缘, 2017, 24(02): 73-84
LI Hongkui, ZHOU Chuanyuan, GENG Ke, et al. Intra-continental extensional tectonics of the Tan-Lu fault zone: an example from the appearance characteristics of the Yishu fault zone[J]. Earth Science Frontiers, 2017, 24(02): 73-84.
[7] 毛先成, 王琪, 陈进, 等. 胶西北金矿集区深部成矿构造三维建模与找矿意义[J]. 地球学报, 2020, 41(02): 166-178 doi: 10.3975/cagsb.2020.020702
MAO Xian-cheng, WANG Qi, CHEN Jin, et al. Three-dimensional Modeling of Deep Metallogenic Structure in Northwestern Jiaodong Peninsula and Its Gold Prospecting Significance[J]. Acta Geoscientica Sinica, 2020, 41(02): 166-178. doi: 10.3975/cagsb.2020.020702
[8] 邱芹军, 马凯, 朱恒华, 等. 基于BERT的三维地质建模约束信息抽取方法及意义. 西北地质, 2022, 55(4): 124−132.
QIU Qinjun, MA Kai, ZHU Henghua, et al. BERT-based Method and Significance of Constraint Information Extraction for 3D Geological Modelling. Northwestern Geology, 2022, 55(4): 124-132.
[9] 宋明春, 李杰, 李世勇, 等. 鲁东晚中生代热隆-伸展构造及其动力学背景[J]. 吉林大学学报(地球科学版), 2018, 48(04): 941-964
SONG Mingchun, LI Jie, LI Shiyong, et al. Late Mesozoic Thermal Upwelling-Extension Structure and Its Dynamics Background in Eastern Shandong Province[J]. Journal of Jilin University(Earth Science Edition), 2018, 48(04): 941-964.
[10] 肖克炎, 李楠, 孙莉, 等. 基于三维信息技术大比例尺三维立体矿产预测方法及途径[J]. 地质学刊, 2012, 36(03): 229-236 doi: 10.3969/j.issn.1674-3636.2012.03.229
XIAO Ke-yan, LI Nan, SUN Li, et al. Large scale 3D mineral prediction methods and channels based on 3D information technology[J]. Journal of Geology, 2012, 36(03): 229-236. doi: 10.3969/j.issn.1674-3636.2012.03.229
[11] 徐述平, 杨立强, 张蜀冀, 等. 胶东招平断裂带金矿成矿指示元素特征及找矿应用[J]. 黄金科学技术, 2010, 18(05): 7-11 doi: 10.3969/j.issn.1005-2518.2010.05.002
XU Shuping, YANG Liqiang, ZHANG Shuji, et al. Metallogenic Indication Element Characteristics and Application of Gold De-posit in Zhaoyuan-Pingdu Fault Zone[J]. Gold Science and Technology, 2010, 18(05): 7-11. doi: 10.3969/j.issn.1005-2518.2010.05.002
[12] 杨立强, 邓军, 王中亮, 等. 胶东中生代金成矿系统[J]. 岩石学报, 2014, 30(09): 2447-2467
YANG Liqiang, DENG Jun, WANG Zhongliang, et al. Mesozoic gold metallogenic system of the Jiaodong gold province, eastern China[J]. Acta Petrologica Sinica, 2014, 30(9): 2447-2467.
[13] 赵鹏大. 成矿定量预测与深部找矿[J]. 地学前缘, 2007, 14(05): 1-10 doi: 10.3321/j.issn:1005-2321.2007.05.001
ZHAO Pengda. Quantitative miniral prediction and deep mineral exploration[J]. Earth Science Frontiers, 2007, 14(05): 1-10. doi: 10.3321/j.issn:1005-2321.2007.05.001
[14] Bray E, John D, Cousens B. Petrologic, tectonic, and metallogenic evolution of the southern segment of the ancestral Cascades magmatic arc, California and Nevada[J]. Geosphere, 2014, 10(1): 1-39. doi: 10.1130/GES00944.1
[15] Chen J, Jiang L, Peng C, et al. Quantitative resource assessment of hydrothermal gold deposits based on 3D geological modeling and improved volume method: Application in the Jiaodong gold Province, Eastern China[J]. Ore Geology Reviews, 2022, 105282.
[16] Deng J, Yang L, Li R, et al. Regional structural control on the distribution of world-class gold deposits: An overview from the Giant Jiaodong Gold Province, China[J]. Geological Journal, 2019, 54: 378-391. doi: 10.1002/gj.3186
[17] Hronsky J M A. Deposit-scale structural controls on orogenic gold deposits: an integrated, physical process-based hypothesis and practical targeting implications[J]. Mineralium Deposita, 2019, 55(2): 197-216.
[18] Huston D L, Blewett R S, Champion D C. Australia through time: A summary of its tectonic and metallogenic evolution[J]. Episodes, 2012, 35(1): 23-43. doi: 10.18814/epiiugs/2012/v35i1/004
[19] Jiang N, Guo J, Fan W, et al. Archean TTGs and sanukitoids from the Jiaobei terrain, North China craton: Insights into crustal growth and mantle metasomatism[J]. Precambrian Research, 2016, 281: 656-672. doi: 10.1016/j.precamres.2016.06.019
[20] Lebrun E, Miller J, Thebaud N, et al. Structural Controls on an Orogenic Gold System: The World-Class Siguiri Gold District, Siguiri Basin, Guinea, West Africa[J]. Economic Geology, 2017, 112(1): 73-89. doi: 10.2113/econgeo.112.1.73
[21] Liu L M, Peng S L. Key strategies for predictive exploration in mature environment: model innovation, exploration technology optimization and information integration[J]. Journal of Central South University of Technology(English Edition), 2005, (02): 186-191.
[22] Liu Z K, Mao X C, Wang F Y, et al. Deciphering anomalous Ag enrichment recorded by galena in Dayingezhuang Au (-Ag) deposit, Jiaodong Peninsula, Eastern China[J]. Transactions of Nonferrous Metals Society of China, 2021a, 31(12): 3831-3846. doi: 10.1016/S1003-6326(21)65768-0
[23] Liu Z K, Chen J, Mao X C, et al. Spatial Association Between Orogenic Gold Mineralization and Structures Revealed by 3D Prospectivity Modeling: A Case Study of the Xiadian Gold Deposit, Jiaodong Peninsula, China[J]. Natural Resources Research, 2021b, 30: 3987-4007. doi: 10.1007/s11053-021-09956-9
[24] Lu Y, Liu L, Xu G. Constraints of deep crustal structures on large deposits in the Cloncurry district, Australia: Evidence from spatial analysis[J]. Ore Geology Reviews, 2016, 79: 316-331. doi: 10.1016/j.oregeorev.2016.05.022
[25] Mao X, Ren J, Liu Z, et al. Three-dimensional prospectivity modeling of the Jiaojia-type gold deposit, Jiaodong Peninsula, Eastern China: A case study of the Dayingezhuang deposit[J]. Journal of Geochemical Exploration, 2019, 203: 27-44. doi: 10.1016/j.gexplo.2019.04.002
[26] Song M, Li S, Santosh M, et al. Types, characteristics and metallogenesis of gold deposits in the Jiaodong Peninsula, Eastern North China Craton[J]. Ore Geology Reviews, 2015, 65: 612-625. doi: 10.1016/j.oregeorev.2014.06.019
[27] Wang J, Mao X, Peng C, et al. Three-Dimensional Refined Modelling of Deep Structures by Using the Level Set Method: Application to the Zhaoping Detachment Fault, Jiaodong Peninsula, China[J]. Mathematical Geosciences, 2022, 55(2): 229-262.
[28] Xie S, Xie H, Wang S, et al. Ca. 2. 9 Ga granitoid magmatism in eastern Shandong, North China Craton: Zircon dating, Hf-in-zircon isotopic analysis and whole-rock geochemistry[J]. Precambrian Research, 2014, 255: 538-562. doi: 10.1016/j.precamres.2014.09.006
[29] Yang L Q, Deng J, Goldfarb R J, et al. 40Ar/39Ar geochronological constraints on the formation of the Dayingezhuang gold deposit: New implications for timing and duration of hydrothermal activity in the Jiaodong gold province, China. Gondwana Research, 2014, 25(4): 1469-1483.
[30] Yang L Q, Deng J, Wang Z L, et al. Relationships between gold and pyrite at the Xincheng gold deposit, Jiaodong Peninsula, China: Implications for gold source and deposition in a brittle epizonal environment[J]. Economic Geology, 2016, 111: 105-126. doi: 10.2113/econgeo.111.1.105
[31] Yu S Y, Deng H, Liu Z K, et al. Identifying multivariate geochemical anomalies via tensor dictionary learning over spatial-elemental dimensionalities[J]. Computers & Geosciences, 2022, 165: 105153.
[32] Yu X, Shan W, Xiong Y, et al. Deep structural framework and genetic analysis of gold concentration areas in the Northwestern Jiaodong Peninsula, China: A new understanding based on high-resolution reflective seismic survey[J]. Acta Geol Sin-Engl, 2018, 92(5): 1823-1840. doi: 10.1111/1755-6724.13679
[33] Zuo R, Carranza E. Support vector machine: A tool for mapping mineral prospectivity[J]. Computers&Geosciences, 2011, 37(12): 1967-1975.
-
图(13)
表(3)
计量
- 文章访问数: 485
- PDF下载数: 91
- 施引文献: 0