山东招远大尹格庄金矿深部三维可视化建模与定位预测
Three-Dimensional Visual Modeling and Location Prediction of Deep Dayingezhuang Gold Deposit in Zhaoyuan, Shandong
DOI: 10.12677/ME.2020.82020, PDF,    国家自然科学基金支持
作者: 李洪奎, 石 冰, 陈国栋, 张玉波, 梁太涛, 韩学林:山东省地质科学研究院,山东 济南;自然资源部金矿成矿地质过程与资源利用重点实验室,山东 济南;毛先成:中南大学地球科学与信息物理学院,湖南 长沙;汤 磊:招金矿业股份有限公司,山东 招远
关键词: 深部成矿三维建模可视化定位预测构造重建金矿床招远大尹格庄Deep Mineralization Three-Dimensional Modeling Visualization Oriental Prognosis Tectonic Reconstruction Gold Deposit Dayingezhuang in Zhaoyuan
摘要: 山东招远大尹格庄金矿床位于华北板块之胶北隆起区内的招远–平度断裂带(简称招平断裂)中。招平断裂带是沿玲珑花岗岩体和前寒武纪结晶基底岩系的侵入接触带而发展、承生、并经多期构造叠加的一条北东向断裂,既属控矿构造,又是导矿和容矿构造,大尹格庄金矿床主要产于招平断裂下盘的碎裂状玲珑花岗岩中,在其上盘的基底岩系中亦有分布,为一典型的破碎带蚀变岩型金矿床。本文以大尹格庄金矿田为研究对象,引入三维地质建模(3DGM)及三维可视化技术,研究探索隐伏矿体预测的三维化、定量化及可视化技术,重点突破了复杂地质体三维形态分析、控矿地质因素场模拟、成矿信息三维定量提取等关键技术,初步形成了隐伏矿体三维可视化预测的方法。依据勘探工程数据、矿体圈定规范和成矿地质规律并结合已知的地震、重力、大地电磁等方法获得的各类数据作为研究深部地质构造的基本资料,对深部成矿构造进行了三维重构,对大尹格庄金矿深部进行了矿化空间分析和三维成矿信息提取,开展了三维定量成矿预测,在此基础上建立了三维定量成矿预测模型。在大尹格庄金矿田共圈定了I、II和Ⅲ号三个可视化立体找矿靶区,为今后深部工作优选区位提供了方向。
Abstract: The Dayingezhuang gold deposit in Zhaoyuan Shandong is located in the Zhaoyuan-Pingdu Fault Zone (Zhaoping Fault for short) in the Jiaobei uplift area of the North China Plate. Zhaoping Fault Zone is a NE-trending fault developed along the intrusive contact zone of Linglong granite body and Precambrian crystalline basement rock series and subjected multiphase tectonic superposition. It is not only an ore-controlling structure, but also an ore-conducting and ore-bearing structure. The Dayingezhuang gold deposit is a typical fractured zone altered rock type gold deposit, which mainly occurs in the cataclastic Linglong granite of the Zhaoping fractured footwall and is also distributed in the upper wall basement series. Targeting Dayingezhuang gold field as the research object, this paper introduced the three-dimensional geological modeling (3-DGM) and three-dimensional (3-D) visualization technology, to study and explore the 3-D, quantitative and visualization technology of concealed ore body prediction. Therefore, the key technologies such as 3-D morphological analysis of complex geological bodies, simulation of ore-controlling geological factor field, and 3-D quantitative extraction of metallogenic information have been made breakthrough. Also, the method of 3-D visual prediction of concealed ore body is preliminarily formed. Based on exploration engineering data, contouring specification and ore-forming geological regularity and combined with all kinds of data obtained from the known seismic, gravity, magnetotelluric method as the basic data of the deep geological structure research, the deep mineralization structure was reconstructed in 3-D, and the deep mineralization space and 3-D ore-forming information were analyzed and extracted. Further, the 3-D quantitative ore-forming prediction has been carried out. And on this basis, the 3-D quantitative metallogenic prognosis model is established. Finally, two visualized and stereoscopic prospecting targets I and II are delineated in the Dayingezhuang gold mine, which provided information for the optimal location of deep work in the future.
文章引用:李洪奎, 毛先成, 汤磊, 石冰, 陈国栋, 张玉波, 梁太涛, 韩学林. 山东招远大尹格庄金矿深部三维可视化建模与定位预测[J]. 矿山工程, 2020, 8(2): 142-155. https://doi.org/10.12677/ME.2020.82020

参考文献

[1] Boissonnat, J.D. (1988) Shape Reconstruction from Planar Cross Sections. Computer Vision, Graphics, and Image Processing, 44, 1-29. [Google Scholar] [CrossRef
[2] Houlding, S.W. (1994) 3D Geoscience Modeling: Computer Techniques for Geological Characterization. Springer-Verlag, Berlin, 1-309. [Google Scholar] [CrossRef
[3] Hu, Y., Yu, X.-H. and Li, S.-L. (2014) Improving the Accuracy of Geological Model by Using Seismic forward and Inverse Techniques. Petroleum Exploration and Development, 41, 208-216. [Google Scholar] [CrossRef
[4] Huang, J., Smola, A.J., Gretton, A., et al. (2006) Correcting Sample Selection Bias by Unlabeled Data. In: Advances in Neural Information Processing Systems 19, Proceedings of the Twentieth Annual Conference on Neural Information Processing Systems, MIT Press, Cambridge, MA.
[5] 毛先成. 三维数字矿床与隐伏矿体立体定量预测研究[D]: [博士学位论文]. 长沙: 中南大学, 2006: 1-18.
[6] 叶天竺, 肖克炎, 严光生. 矿床模型综合地质信息预测技术研究[J]. 地学前缘, 2007, 14(5): 11-19.
[7] 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]. 地质学报, 2012, 36(3): 229-236.
[8] 李洪奎, 耿科, 禚传源, 梁太涛, 等. 胶东金矿构造环境与成矿作用[M]. 北京: 地质出版社, 2016: 1-8.
[9] 毛先成, 邹艳红, 陈进, 等. 隐伏矿体三维可视化预测[M]. 长沙: 中南大学出版社, 2011: 1-33.
[10] 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(5): 54-61.
[11] 李洪奎, 李逸凡, 耿科, 禚传源. 山东鲁东碰撞造山型金矿成矿作用探讨[J]. 大地构造与成矿学, 2011, 35(4): 533-542.
[12] 李洪奎, 禚传源, 耿科, 梁太涛. 胶东金矿成矿构造背景探讨[J]. 山东国土资源, 2012, 28(1): 5-13.
[13] 李洪奎, 李大鹏, 郭宝奎, 耿科, 禚传源. 胶东地区中生代碰撞后到造山后岩浆活动格架[J]. 岩石学报, 2015, 31(5): 2341-2352.
[14] 李洪奎, 李逸凡, 耿科, 禚传源, 梁太涛. 山东鲁东地区中生代构造-岩浆事件与金矿成矿作用[J]. 地球科学前沿, 2013, 3(3): 141-154.
[15] 李逸凡, 李洪奎. 招远大尹格庄金矿微量元素特征及其意义[J]. 山东国土资源, 2014, 30(11): 13-19.
[16] 李洪奎, 禚传源, 单伟. 山东招远–平度断裂带二维地震剖面研究及其地质意义[J]. 地球科学前沿, 2015, 5(1): 12-21.
[17] 李逸凡, 李洪奎, 汤启云, 禚传源. 山东旧店金矿黄铁矿标型特征及其地质意义[J]. 黄金科学技术, 2015, 23(2): 45-50.
[18] 李洪奎, 禚传源, 单伟, 耿科, 梁太涛. 山东旧店金矿金矿物特征及其意义[J]. 山东国土资源, 2015, 31(5): 1-8.
[19] 严加永, 吕庆田, 孟贵祥, 等. 三维可视化及物探新技术在矿山接替资源勘查中的应用——以铜陵狮子山矿田为例[J]. 地球学报, 2008, 29(1): 116-120.
[20] 武强, 徐华. 三维地质建模与可视化方法研究[J]. 中国科学: 地球科学, 2004, 34(1): 54-60.
[21] 戴雪灵. 山东招远大尹格庄金矿成岩-成矿机理研究[D]: [硕士学位论文]. 长沙: 中南大学, 2012: 1-14.
[22] 李子英, 张瑞忠, 周春生, 等. 胶东大尹格庄金矿床控矿构造系统[J]. 金属矿山, 2010(3): 86-90.
[23] 刘庚寅, 杨斌, 陈艳, 等. 大尹格庄金矿成矿作用与隐伏矿体找矿标志分析[J]. 矿床地质, 2010, 29(1): 967-968.
[24] 刘海英. 多种克里格方法在固矿储量估算中的应用研究[D]: [硕士学位论文]. 武汉: 中国地质大学(武汉), 2010: 21-32.
[25] 徐述平. 招平断裂带金矿勘查模型与成矿预测[D]: [博士学位论文]. 北京: 中国地质大学(北京), 2009: 1-22.