A study of mineralization of Wutai gold deposits in Shanxi Province based on the weight of evi-dence-singularity-gray theory
-
摘要:
山西五台地区位于华北陆台中部,是山西省内重要的金矿成矿区域,地质条件复杂,近年来找矿突破较小。在矿产预测中,可以结合证据权快速筛选地质变量,求取权重,计算地质奇异性指数,提取局部地质弱异常;利用灰色理论只需少量信息进行预测的特点,圈定找矿靶区,寻找突破。应用证据权-奇异性-灰色理论方法圈定了研究区预测靶区,靶区内通过已知矿床的验证,提取了4个一级靶区,1个二级靶区,确定了该区域金矿找矿突破口,明确了证据权-奇异性-灰色理论关联分析预测法在矿产预测评价中的重要应用价值和独特的应用效果。
Abstract:Located in the central part of North China Craton, Wutai area is an important area of gold mineralization in Shanxi Prov-ince; nevertheless, complex geological settings of this area lead to rare recent prospecting breakthroughs. In mineral prediction, the geological evidence weight approach can rapidly screen geological variables to calculate weights and anomaly index and extract local weak geological anomalies, whereas the gray theory approach can delineate prospecting targets by using only a small amount of infor-mation. These methods can be jointly utilized to look for a breakthrough. In delineating the prognostic target areas based on verified known deposits, four primary targets and a secondary target in Wutai area were delineated. This Weight-Anomaly-Gray Theory conjoint analysis is believed to be an important application in mineral prediction with unique application effect.
-
Key words:
- Wutai /
- gold deposit /
- nonlinear /
- gray theory /
- singularity /
- metallogenic prediction
-
-
表 1 五台地区证据因子权重
Table 1. Weight of evidence factor in Wutai area
变量名称 W+ W- 含矿地层面积百分比 2.357 -0.311 控(容)矿侵入岩缓冲区 2.613 -0.315 断裂构造密度 0.674 -0.481 化探Au元素异常 2.810 -0.369 化探Ag元素异常 0.190 -0.148 化探Pb元素异常 0.145 -0.142 表 2 研究区已知矿点处的奇异指数无量纲化值比较数列矩阵
Table 2. The singular index study area deposits at the dimensionless value of comparative sequence matrix
矿点
序号Ar
地层侵入岩
缓冲区断裂
密度Au
化探异常Ag
化探异常Pb
化探异常1 1.0000 0.9816 0.3632 0.0193 0.0762 0.3237 2 1.0000 0.9185 0.3734 0.0197 0.0785 0.2989 3 1.0000 0.9816 0.3813 0.0190 0.0942 0.3768 4 1.0000 0.965 0.3135 0.0163 0.0832 0.3514 5 1.0000 0.885 0.3615 0.0162 0.0781 0.3916 6 1.0000 0.8676 0.3108 0.0106 0.0719 0.3329 7 1.0000 0.9724 0.3470 0.0197 0.0374 0.3984 8 1.0000 0.9476 0.3462 0.0108 0.0714 0.3469 9 1.0000 0.9576 0.3068 0.0087 0.076 0.3624 10 1.0000 0.9740 0.2998 0.0069 0.0744 0.3205 11 1.0000 0.9855 0.3249 0.0128 0.066 0.3217 12 1.0000 0.9316 0.3517 0.0051 0.0771 0.3022 13 1.0000 0.9362 0.3224 0.0086 0.0771 0.3323 14 1.0000 0.9240 0.3415 0.0069 0.0819 0.3412 均值 1.0000 0.9449 0.3389 0.0129 0.0745 0.3429 权重 2.3570 2.6130 0.6740 2.8100 0.1900 0.1450 权重后值 2.3570 2.4689 0.2284 0.0363 0.0142 0.0497 -
[1] 赵鹏大.成矿定量预测与深部找矿[J].地学前缘(中国地质大学(北京), 北京大学), 2006, 14(5):1-9. http://www.cnki.com.cn/Article/CJFDTOTAL-YSJW201701015.htm
[2] Zhao P D, Chen J P, Zhang S T, et al. Mineral deposits:geological anomalies with high economic value[C]//Cheng Q, Bonham-Cart-er G F. Proceedings of IAMG'05, 2005:1022-1027.
[3] 詹姆斯. 格莱克著, 张淑誉译. 混沌: 开创新科学[M]. 上海: 上海译文出版社, 1990.
[4] 范海明. 五台山-恒山地区金矿多源信息综合研究[D]. 中国地质大学(北京)硕士学位论文, 2009(1): 5-15.
http://d.wanfangdata.com.cn/Thesis/Y1783891 [5] 范海明.基于适宜性模型的多元信息成矿预测研究——以五台山-恒山地区金矿为例[J].科技创新与生产力, 2013, 6:100-102. doi: 10.3969/j.issn.1674-9146.2013.07.100
[6] Agterberg F P, Bonham-Carter G F, Weight D F. Statistical Pattern Integration for Mineral Exploration[C]//Gaal G, Merriam D F. Computer Applications for Mineral Exploration in Resource Explo-ration. Oxford:Pergamon Press, 1990:1-21.
[7] Chen J P, Wang G W, Hou C B. Quantitative Prediction and Evalu-ation of Mineral Resources Based on GIS:A Case Study in Sanjiang Region, Southwestern China[J]. Natural Resources Research, 2005, 24(1):15-24. https://www.mendeley.com/research-papers/quantitative-prediction-evaluation-mineral-resources-based-gis-case-study-sanjiang-region-southweste/
[8] Cheng Q M. Application of Weights of Evidence Method for Assess-ment of Flowing Wells in the Greater Toronto Area, Canada[J]. Nat-ural Resources Research, 2004, 13(2):77-86. doi: 10.1023/B:NARR.0000032645.46747.48
[9] Emmanuel J M. Carranza Martin Hale Geologically Constrained Probabilistic Mapping of Gold Potential, Baguio District, Philip-pines[J]. Natural Resources Research, 2000, 9(3):237-253. doi: 10.1023/A:1010147818806
[10] Cheng Q M. Singularity modeling of geo-anomalies and recogni-tion of anomalies caused by buried sources[J]. Earth Science:Jour-nal of China University of Geosciences, 2011, 36(2):307-316. http://en.cnki.com.cn/Article_en/CJFDTOTAL-DQKX201102017.htm
[11] Cheng Q M, Agterberg F P, Bonham-Carter G F. A spatial analy-sis method for geochemical anomaly separation[J]. Journal of Geo-chemical Exploration, 1996, 56(3):183-195. doi: 10.1016/S0375-6742(96)00035-0
[12] 陈志军. 多重分形局部奇异性分析方法及其在矿产资源信息提取中的应用[D]. 中国地质大学(北京)博士学位论文, 2007, (1): 35-77.
http://cdmd.cnki.com.cn/Article/CDMD-10491-2007142833.htm [13] 成秋明.成矿过程奇异性与矿产预测定量化的新理论与新方法[J].地学前缘, 2007, 14(5):42-53. http://www.cnki.com.cn/Article/CJFDTOTAL-DXQY200705006.htm
[14] 成秋明, 赵鹏大, 陈建国, 等.奇异性理论在个旧锡铜矿产资源预测中的应用:成矿弱信息提取和复合信息分解[J].地球科学(中国地质大学学报), 2009, 34(2):232-242. http://www.cnki.com.cn/Article/CJFDTOTAL-DQKX200902001.htm
[15] 成秋明.非线性成矿预测理论:多重分形奇异性-广义自相似性-分形谱系模型与方法[J].地球科学(中国地质大学学报), 2006, 31(3):337-348. http://www.cnki.com.cn/Article/CJFDTOTAL-DQKX200603008.htm
[16] 张焱, 周永章.奇异性理论在钦杭成矿带(南段)庞西垌银金矿产资源预测中的应用[J].中南大学学报(自然科学版), 2012, 43(9):3558-3563. http://www.cnki.com.cn/Article/CJFDTOTAL-ZNGD201209036.htm
[17] 李晓晖, 袁峰, 贾蔡, 等.基于地统计学插值方法的局部奇异性指数计算比较研究[J].地理科学, 2012, 32(2):136-140. http://www.cnki.com.cn/Article/CJFDTOTAL-DLKX201202003.htm
[18] 邓聚龙.灰色系统基本方法[M].武汉:华中理工大学出版社, 1992:24-29.
[19] 吕鹏, 陈建平, 蔡如华, 等.基于灰色关联分析预测法的腾冲硅藻土矿床资源评价[J].地质找矿论丛, 2007, 22(1):56-61. http://www.cnki.com.cn/Article/CJFDTOTAL-DZZK200701010.htm
[20] Kang J, Zou Z H. Time Prediction Model for Pipeline Leakage Based on Grey Relational Analysis[J]. Physics Procedia, 2012, 25:2019-2014. doi: 10.1016/j.phpro.2012.03.344
[21] Song Q B, Shepperd Martin. Predicting software project effort:A grey relational analysis based method[J]. Expert Systems with Appli-cations, 2011, 38:7302-7316. doi: 10.1016/j.eswa.2010.12.005
[22] Wang S, Zhang J L. Study on coal mines accidents based on the grey relational analysis[J]. Journal of Coal Science & Engineering (China), 2008, 1(14):81-84. https://link.springer.com/article/10.1007/s12404-008-0017-1
[23] Ip W C, Hu B Q, Wong H, et al. Applications of grey relational method to river environment quality evaluation in China[J]. Jour-nal of Hydrology, 2009, 379:284-290. doi: 10.1016/j.jhydrol.2009.10.013
[24] 麻志勇, 成荣树.用灰色系统对赣西金矿床成矿地质异常进行评价和预测[J].有色金属矿产与勘查, 1994, 3(5):312-316. http://www.cnki.com.cn/Article/CJFDTOTAL-YSJS405.011.htm
[25] 纪瑛瑛, 孙忠实.灰色系统理论在海沟金矿成矿预测中的应用[J].吉林地质, 1999, 18(4):38-42. http://www.cnki.com.cn/Article/CJFDTOTAL-JLDZ199904005.htm
-