Multiple-map step effect and optimization of various experimental correction methods based on geochemical data
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摘要:
在处理整图幅地球化学数据、编制大范围地球化学图件时, 需要多图幅数据拼接成图, 不同图幅交界处易出现台阶效应。目前与系统误差相关的文献多为单一方法校正评价某一地区化探数据台阶效应, 很少进行多种方法的比较优化。以青海省沟里地区园以幅、巴加别里赤尔幅、沟里乡幅和智益幅为例, 使用分幅标准化法、归一化法和衬度法对4图幅范围的1∶5万水系沉积物地球化学数据进行了系统误差校正和方法优选, 为岩屑介质化探数据系统误差处理提供有效的方法参考。结果表明, 这3种方法对于处理系统误差均有较为明显的效果, 校正后相邻图幅间的背景差异基本消除, 台阶效应有效弱化, 地球化学区域分带连续, 强异常均被适当压抑, 弱异常被适当增强而从背景中突显。但同一元素用不同方法校正后异常面积、异常形态、与矿床(点)吻合度等存在差异。分幅标准化法和归一化法校正后异常与已知矿床(点)的吻合率均为75%, 异常均匀分布于全区, 但个别矿致异常被弱化, 且无法避免无效异常的影响。衬度法校正效果良好, 能有效地压抑高背景区非矿异常并强化低背景区矿致异常, 异常与矿床(点)吻合度为87.5%, 无效异常的干扰较小, 与地质背景契合度最高。结合研究区实体地质体条件的研究表明, 衬度法更适合沟里地区不同图幅水系沉积物地球化学测量数据系统误差的校正, 可在西北地区类似地形、地貌条件的化探数据处理工作中选择应用。
Abstract:It is necessary to plat the multiple-map sheet data sets into a single map when processing the geochemical data from the entire map sheet and compiling a large-scale geochemical map, but step effects might readily arise where different map sheets converge. There are currently few papers that compare and optimize various methods, and most systematic error-related studies focus on a specific way to correct and assess the step effect of geochemical data in a particular area. With the map sheet from the Yuanyi, Bajiabielichier, Goulixiang, and Zhiyi in Gouli region of Qinghai Province as a case study, this paper applies the framing standardization method, normalized method, and contrast method to perform systematic error correction and method optimization on 1∶50 000 stream sediment geochemical data and provides the effective method reference for the systematic error processing of the geochemical prospecting data of the rock cuttings. The results indicate that these three methods have distinct effects on systematic error correction.After the original data are corrected, the background difference between adjacent map sheets is basically eliminated, the step effect is effectively weakened, the geochemical zoning is continuous, the strong anomalies are appropriately suppressed, and the weak anomalies are appropriately enhanced and represented in the background. After the same element is corrected with various methods, there are differences in the anomalous area, form of anomalies, and goodness of fit with the mineral deposit (point). The goodness of fit between anomalies and known deposits (points) after correction with the framing standardization method and normalized method is 75%; the anomalies are evenly distributed throughout the region, but individual ore-induced anomalies are weakened, and the influence of invalid anomalies cannot be avoided. The nonmineral anomaly in the high background area can be effectively suppressed by the contrast method, and the mineral-induced anomaly in the low background area can be strengthened. The anomaly's goodness of fit with the deposit (point) is 87.5%, the invalid anomaly's influence is minimal, and the geological background has the maximum goodness of fit. Combined with the study on the physical geological body conditions in the region of interest, the contrast method is more suitable for the correction of systematic errors in stream sediment geochemical survey data on different map sheets in the Gouli Region and can be selected and applied in geochemical data processing under similar topographic and geomorphic conditions in Northwest China.
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Key words:
- step effect /
- systematic error /
- framing standardization method /
- normalized method /
- contrast method
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图 1 东昆仑地区区域地质简图及研究区位置(据文献[18]修改)
Figure 1. Generalized geologic map of East Kunlun region and location of the study area
图 2 研究区地质图
1.第四系冲洪积物; 2.第四系残坡积物; 3.鄂拉山组; 4.洪水川组; 5.大干沟组; 6.浩特洛洼组; 7.纳赤台群; 8.万宝沟岩群; 9.小庙组; 10.金水口岩群; 11.中印支期正长花岗岩; 12.中印支期花岗闪长岩; 13.中印支期二长花岗岩; 14.晚华力西期二长花岗岩; 15.晚华力西期石英闪长岩; 16.晚加里东期花岗闪长岩; 17.中加里东期花岗闪长岩; 18.早加里东期英云闪长岩; 19.大型金矿; 20.小型金矿; 21.金矿点; 22.铜矿点; 23.多金属矿点; 24.铜铁矿点; 25.铁矿点; 26.逆断层; 27.断层; 28.性质不明断层; 29.地质界线
Figure 2. Geological map of the study area
图 3 Au、Ag元素原始含量对数直方图
Figure 3. Logarithmic histograms of the original content of Au and Ag
图 4 Au、Ag元素剔值后含量对数直方图
Figure 4. Logarithmic histograms of the content of Au and Ag after elimination of value
图 5 校正前Au元素等值线图
a.原始数据集编制的Au等值线图；b.剔值后数据集编制的Au等值线图；1.阿斯哈金矿床; 2.叶陇沟金矿点; 3.按纳格金矿床; 4.尕之麻金矿点; 5.果龙洼金矿床; 6.园以金矿点; 7.德龙金矿床; 8.达里吉格塘金矿点
Figure 5. Contour maps of the Au element before correction
图 6 校正前Ag元素等值线图
a.原始数据集编制的Ag等值线图；b.剔值后数据集编制的Ag等值线图
Figure 6. Contour maps of the Ag element before correction
图 7 Au元素原始异常图
a.迭代替换后数据集编制的Au异常图; b.剔值后数据集编制的Au异常图；矿床(点)名称1~8同图 5
Figure 7. Original anomaly maps of the Au element
图 8 Ag元素原始异常图
a.迭代替换后数据集编制的Ag异常图; b.剔值后数据集编制的Ag异常图
Figure 8. Original anomaly maps of the Ag element
图 9 Au元素校正等值线图对比
a.误差校正前；b.分幅标准化法校正后；c.归一化法校正后；d.衬度法校正后；矿床(点)1~8同图 5
Figure 9. Comparison of contour maps of Au after correction
图 10 Ag元素校正等值线图对比
a.误差校正前；b.分幅标准化法校正后；c.归一化法校正后Ag；d.衬度法校正后
Figure 10. Comparison of contour maps of Ag after correction
图 11 Au元素校正异常图对比
a.误差校正前；b.分幅标准化法校正后；c.归一化法校正后；d.衬度法校正后；矿床(点)名称1~8同图 5
Figure 11. Comparison of anomaly maps of Au after correction
图 12 Ag元素校正异常图对比
a.误差校正前；b.分幅标准化法校正后；c.归一化法校正后；d.衬度法校正后
Figure 12. Comparison of anomaly maps of Ag after correction
表 1 研究区原始数据统计特征
Table 1. Statistical characteristics of the original data of the study area
wB/10-9 项目 N 极大值 极小值 平均值 标准差 方差 偏度 峰度 Au 8 950 249.8 0.5 2.05 4.17 17.42 35.22 1 790.38 Ag 8 950 5 000.0 11.0 63.80 101.39 10 280.45 23.56 858.44 
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表 2 研究区处理后数据统计特征
Table 2. Statistical characteristics of processed data of the study area
wB/10-9 方法 项目 N 极大值 极小值 平均值 标准差 方差 偏度 峰度 剔值法 Au 8 454 4.4 0.5 1.62 0.93 0.86 1.04 0.31 Ag 8 283 117.0 11.0 50.20 22.32 497.98 0.74 0.23 迭代替换法 Au 8 950 5.5 0.5 1.82 1.23 1.51 1.39 1.39 Ag 8 950 11.0 157.5 57.37 33.37 1 113.55 1.44 1.83
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表 3 分析室数据统计特征
Table 3. Statistical characteristics of the data of the analysis rooms
wB/10-9 图幅 项目 N 极小值 极大值 平均值 标准差 方差 偏度 峰度 圆以幅 Au 2 287 0.5 7.1 2.37 1.58 2.51 1.28 1.30 Ag 2 287 12.0 101.0 41.95 19.74 389.65 0.92 0.82 巴加别里赤尔幅 Au 2 385 0.5 3.8 1.39 0.82 0.68 1.45 1.60 Ag 2 385 16.0 187.0 70.11 39.13 1 530.87 1.37 1.51 沟里乡幅 Au 2 124 0.5 5.4 1.85 1.19 1.43 1.25 1.09 Ag 2 124 11.0 94.9 43.15 17.26 297.97 0.42 0.42 智益幅 Au 2 154 0.5 5.0 1.71 1.11 1.23 1.50 1.64 Ag 2 154 24.0 218.0 77.11 47.08 2216.24 1.54 1.86
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表 4 标准化转换后视含量统计特征
Table 4. Statistical characteristics of visual content after standardized conversion
项目 N 平均值 标准差 方差 偏度 峰度 Au 8 950 0 1 1 1.37 1.41 Ag 8 950 0 1 1 1.07 1.16
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表 5 归一化转换后视含量数据统计特征
Table 5. Statistical characteristics of visual content data after the normalization transformation
wB/10-9 项目 N 极大值 平均值 标准差 方差 偏度 峰度 Au 8 950 1 0.28 0.24 0.06 1.37 1.37 Ag 8 950 1 0.33 0.23 0.05 1.04 0.88
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表 6 台阶A、B迭代替换后数据统计特征
Table 6. Statistical characteristics of data after iterative replacement of step A and B
wB/10-9 项目 N 极小值 极大值 平均值 标准差 方差 偏度 峰度 台阶A Au 4 412 0.5 6.3 2.12 1.41 1.99 1.27 1.20 Ag 4 412 11.0 98.1 42.51 18.54 43.65 0.69 0.61 台阶B Au 4 539 0.5 4.4 1.54 0.97 0.94 1.50 1.69 Ag 4 539 11.0 201.0 73.23 42.72 1824.64 1.46 1.68
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表 7 衬度变换后数据统计特征
Table 7. Statistical characteristics of the data after contrast transformation
wB/10-9 项目 N 极小值 极大值 平均值 标准差 方差 偏度 峰度 Au 8 950 0.5 5.41 1.82 1.18 1.39 1.38 1.43 Ag 8 950 11.0 159.37 58.12 29.97 898.27 1.27 1.78
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表 8 不同校正方法圈定异常对比
Table 8. Comparison of anomalies determined with different correction methods
元素 方法 异常个数/个 异常面积/km2 异常面积占研究区面积比例/% 具三级浓度分带异常数量/个 具三级浓度分带异常占总异常比例/% 矿床(点)总数/个 落入异常的矿床(点)数量/个 落入异常的矿床(点)比例/% Au 校正前迭代替换数据集 38 60.36 3.55 25 66 8 6 75 校正前剔值数据集 37 43.62 2.57 31 84 8 4 50 分幅标准化法 43 51.13 3.01 26 60 8 6 75 归一化法 46 54.07 3.18 28 61 8 6 75 衬度法 43 60.28 3.55 26 60 8 7 87.5 Ag 校正前迭代替换数据集 44 82.39 4.85 16 36 校正前剔值数据集 44 97.44 5.73 33 75 分幅标准化法 39 64.14 3.77 34 87 归一化法 40 65.58 3.86 32 80 衬度法 46 76.29 4.49 34 74
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[1] 杨宝荣, 张里斌, 马忠贤, 等. 青海沟里地区金矿床地质背景研究[J]. 矿产勘查, 2018, 9(10): 1920-1925. doi: 10.3969/j.issn.1674-7801.2018.10.009Yang B R, Zhang L B, Ma Z X, et al. Study on metallogenic geological background of gold deposits in Gouli area, Qinghai[J]. Mineral Exploration, 2018, 9(10): 1920-1925(in Chinese with English abstract). doi: 10.3969/j.issn.1674-7801.2018.10.009 [2] Xie S Y, Cheng Q M, Xing X T, et al. Geochemical multifractal distribution patterns in sediments from ordered streams[J]. Geoderma, 2010, 160(1): 36-46. doi: 10.1016/j.geoderma.2010.01.009 [3] 戴慧敏, 赵君, 杨忠芳, 等. 基于地球化学背景的多图幅系统误差校正: 以区域地球化学调查数据Au元素为例[J]. 地球学报, 2014, 35(5): 648-654. https://www.cnki.com.cn/Article/CJFDTOTAL-DQXB201405019.htmDai H M, Zhao J, Yang Z F, et al. Multi-map systematic error correction method based on geochemical background: A case study on gold of regional geochemical survey[J]. Acta Geoscientica Sinica, 2014, 35(5): 648-654(in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-DQXB201405019.htm [4] 应祥熙. "标准正态转换法"用于化探数据特征的"反推"以及系统误差的调平[J]. 地质与勘探, 2006, 42(5): 84-89. doi: 10.3969/j.issn.0495-5331.2006.05.016Ying X X. Using "conversion method of standard normal distribution" to "deduction" of geochemical prospecting data and revise of system error[J]. Geology and Prospecting, 2006, 42(5): 84-89(in Chinese with English abstract). doi: 10.3969/j.issn.0495-5331.2006.05.016 [5] 纪宏金, 连长云, 杜庆丰. 地球化学数据的标准化与衬度变换[J]. 物探化探计算技术, 1993, 15(1): 19-25. https://www.cnki.com.cn/Article/CJFDTOTAL-WTHT199301003.htmJi H J, Lian C Y, Du Q F. Standardization and contrast transformation for chemical data[J]. Computing Techniques for Geophysical and Geochemical Exploration, 1993, 15(1): 19-25(in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-WTHT199301003.htm [6] 陈永清, 纪宏金. 标准化区域地球化学图的编制方法及应用效果[J]. 长春地质学院学报, 1995, 25(2): 216-221. https://www.cnki.com.cn/Article/CJFDTOTAL-CCDZ502.017.htmChen Y Q, Ji H J. The compiling method of standardized geochemical map and its application effects[J]. Journal of Changchun University of Earth Sciences, 1995, 25(2): 216-221(in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-CCDZ502.017.htm [7] 陈建国, 郭晓兰, 刘春华. 区域地球化学图件拼接中的图幅平差法[J]. 地球科学: 中国地质大学学报, 1997, 22(6): 61-64. https://www.cnki.com.cn/Article/CJFDTOTAL-DQKX706.012.htmChen J G, Guo X L, Liu C H. Map adjustment method for merging geochemical map[J]. Earth Science: Journal of China University of Geosciences, 1997, 22(6): 61-64(in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-DQKX706.012.htm [8] 陈明, 李金春. 化探背景与异常识别的问题与对策[J]. 地质与勘探, 1999, 35(2): 25-29. https://www.cnki.com.cn/Article/CJFDTOTAL-DZKT902.007.htmChen M, Li J C. Problem and countermeasure of recognition of geochemical background and anomaly[J]. Geology and Prospecting, 1999, 35(2): 25-29(in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-DZKT902.007.htm [9] 纪宏金, 林瑞庆, 周永昶. 关于若干化探数据处理方法的讨论[J]. 地质与勘探, 2001, 37(4): 56-59. doi: 10.3969/j.issn.0495-5331.2001.04.016Ji H J, Lin R Q, Zhou Y X. A discussion about some data processing methods in geochemical exploration[J]. Geology and Prospecting, 2001, 37(4): 56-59(in Chinese with English abstract). doi: 10.3969/j.issn.0495-5331.2001.04.016 [10] 纪宏金, 时艳香, 代永刚, 等. 基于边界极限原理的多图幅系统误差校正方法[J]. 物探化探计算技术, 2005, 27(2): 154-155. doi: 10.3969/j.issn.1001-1749.2005.02.016Ji H J, Shi Y X, Dai Y G, et al. A multi-map systemic error correction method based on border limiting principle[J]. Computing Techniques for Geophysical and Geochemical Exploration, 2005, 27(2): 154-155(in Chinese with English abstract). doi: 10.3969/j.issn.1001-1749.2005.02.016 [11] 时艳香, 纪宏金, 陆继龙. 地球化学数据的定和化及其在系统误差校正中的应用[J]. 物探化探计算技术, 2005, 27(1): 48-50, 98. https://www.cnki.com.cn/Article/CJFDTOTAL-WTHT200501011.htmShi Y X, Ji H J, Lu J L. Application of geochemical data and its application systematic error correction[J]. Computing Techniques for Geophysical and Geochemical Exploration, 2005, 27(1): 48-50, 98(in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-WTHT200501011.htm [12] 刘大文. 区域地球化学数据的归一化处理及应用[J]. 物探与化探, 2004, 28(3): 273-275, 279. doi: 10.3969/j.issn.1000-8918.2004.03.024Liu D W. The normalization of regional geochemical data and its application[J]. Geophysical & Geochemical Exploration, 2004, 28(3): 273-275, 279(in Chinese with English abstract). doi: 10.3969/j.issn.1000-8918.2004.03.024 [13] 代永刚, 郝立波, 陆继龙. 区域化探中多图幅系统误差的校正[J]. 吉林大学学报: 地球科学版, 2005, 35(1): 128-130. https://www.cnki.com.cn/Article/CJFDTOTAL-CCDZ20050100P.htmDai Y G, Hao L B, Lu J L. The systemic error correction of maps in regional geochemical prospecting[J]. Journal of Jilin University: Earth Science Edition, 2005, 35(1): 128-130(in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-CCDZ20050100P.htm [14] 周永恒, 李守义, 张璟, 等. 基于地质背景分析的区域化探数据系统误差校正[J]. 吉林大学学报: 地球科学版, 2011, 41(3): 753-758. https://www.cnki.com.cn/Article/CJFDTOTAL-CCDZ201103017.htmZhou Y H, Li S Y, Zhang J, et al. The systemic error correction of regional geochemical mapping data based on geological background analysis[J]. Journal of Jilin University: Earth Science Edition, 2011, 41(3): 753-758(in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-CCDZ201103017.htm [15] 刘强, 李伟, 王长琪. 黄土覆盖区地球化学数据采集及采样单元之间误差校正方法研究: 以内蒙古敖汉旗为例[J]. 地质与资源, 2014, 23(6): 587-592. https://www.cnki.com.cn/Article/CJFDTOTAL-GJSD201406019.htmLiu Q, Li W, Wang C Q. Geochemical data collection and error correction for sampling in loess covered areas: A case study of Aohan County, Inner Mongolia[J]. Geology and Resources, 2014, 23(6): 587-592(in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-GJSD201406019.htm [16] 王晖, 陈继平, 胡奎, 等. 多批次数据地球化学图件编制的系统误差校正方法[J]. 现代矿业, 2017, 33(9): 63-65, 76. doi: 10.3969/j.issn.1674-6082.2017.09.013Wang H, Chen J P, Hu K, et al. Correction method of systematic error in preparation of geochemical map of multiple batches of data[J]. Modern Mining, 2017, 33(9): 63-65, 76(in Chinese with English abstract). doi: 10.3969/j.issn.1674-6082.2017.09.013 [17] 韩登辉, 高顺宝, 郑有业, 等. 地球化学数据含量—面积多重分形方法中台阶效应的处理方法[J]. 物探与化探, 2020, 44(6): 1420-1428. https://www.cnki.com.cn/Article/CJFDTOTAL-WTYH202006020.htmHan D H, Gao S B, Zheng Y Y, et al. A processing technique of step effect in concentration-area multifractal method[J]. Geophysical & Geochemical Exploration, 2020, 44(6): 1420-1428(in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-WTYH202006020.htm [18] 史长义. 勘查数据分析(EDA)技术的应用[J]. 地质与勘探, 1993, 29(11): 52-58. https://www.cnki.com.cn/Article/CJFDTOTAL-DZKT199311010.htmShi C Y. Application of the exploratory data analysis technique[J]. Geology and Prospecting, 1993, 29(11): 52-58(in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-DZKT199311010.htm [19] 赵禹, 赵玉岩, 郝立波, 等. 利用快速聚类分析分区确定化探背景上限的方法[J]. 物探化探计算技术, 2014, 36(4): 487-491. doi: 10.3969/j.issn.1001-1749.2014.04.20Zhao Y, Zhao Y Y, Hao L B, et al. Subregion determine of upper limit of geochemical background using K-means cluster analysis method[J]. Computing Techniques for Geophysical and Geochemical Exploration, 2014, 36(4): 487-491(in Chinese with English abstract). doi: 10.3969/j.issn.1001-1749.2014.04.20 [20] Cao M X, Lu L J. Application of the multivariate canonical trend surface method to the identification of geochemical combination anomalies[J]. Journal of Geochemical Exploration, 2015, 153: 1-10. doi: 10.1016/j.gexplo.2014.11.006 [21] Shahi H, Ghavami R, Kamkar-Rouhani A, et al. Application of fourier and wavelet approaches for identification of geochemical anomalies[J]. Journal of African Earth Sciences, 2015, 106: 118-128. doi: 10.1016/j.jafrearsci.2015.03.017 [22] 袁玉涛. 化探数据处理方法对比研究: 以乌日尼图钨钼矿床为例[D]. 北京: 中国地质大学(北京), 2015.Yuan Y T. Comparative study on the geochemical exploration data processing method: A case of Wurinitu W-Mo Deposit[D]. Beijing: China University of Geosciences(Beijing), 2015(in Chinese with English abstract). [23] Tian M, Wang X Q, Nie L S, et al. Recognition of geochemical anomalies based on geographically weighted regression: A case study across the boundary areas of China and Mongolia[J]. Journal of Geochemical Exploration, 2018, 190: 381-389. doi: 10.1016/j.gexplo.2018.04.003 [24] Wang W L, Cheng Q M, Zhang S Y, et al. Anisotropic singularity: A novel way to characterize controlling effects of geological processes on mineralization[J]. Journal of Geochemical Exploration, 2018, 189: 32-41. http://smartsearch.nstl.gov.cn/paper_detail.html?id=df9918380ad49ac6e02399647fa1b873 [25] Tian M, Wang X Q, Nie L S, et al. Spatial distributions and the identification of ore-related anomalies of Cu across the boundary area of China and Mongolia[J]. Journal of Geochemical Exploration, 2019, 197: 37-47. http://www.researchgate.net/publication/329119208_Spatial_distributions_and_the_identification_of_ore-related_anomalies_of_Cu_across_the_boundary_area_of_China_and_Mongolia [26] 左仁广. 勘查地球化学数据挖掘与弱异常识别[J]. 地学前缘, 2019, 26(4): 67-75. https://www.cnki.com.cn/Article/CJFDTOTAL-DXQY201904010.htmZuo R G. Exploration geochemical data mining and weak geochemical anomalies identification[J]. Earth Science Frontiers, 2019, 26(4): 67-75(in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-DXQY201904010.htm [27] 成秋明, 张生元, 左仁广, 等. 多重分形滤波方法和地球化学信息提取技术研究与进展[J]. 地学前缘, 2009, 16(2): 185-198. https://www.cnki.com.cn/Article/CJFDTOTAL-DXQY200902018.htmCheng Q M, Zhang S Y, Zuo R G, et al. Progress of multifractal filtering techniques and their applications in geochemical information extraction[J]. Earth Science Frontiers, 2009, 16(2): 185-198(in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-DXQY200902018.htm [28] Zuo R G, Wang J, Chen G X, et al. Identification of weak anomalies: A multifractal perspective[J]. Journal of Geochemical Exploration, 2015, 148: 12-24. http://www.onacademic.com/detail/journal_1000036316229210_ddd1.html [29] Zuo R G, Xiong Y H, Wang J, et al. Deep learning and its application in geochemical mapping[J]. Earth-Science Reviews, 2019, 192: 1-14. http://www.onacademic.com/detail/journal_1000041584839699_fcea.html [30] Chen Y L, Lu L J, Li X B. Application of continuous restricted Boltzmann machine to identify multivariate geochemical anomaly[J]. Journal of Geochemical Exploration, 2014, 140: 56-63. http://www.sciencedirect.com/science?_ob=ShoppingCartURL&_method=add&_eid=1-s2.0-S0375674214000764&originContentFamily=serial&_origin=article&_ts=1484624996&md5=80f4d3a7f7c025c6af77c5175d9380a9 [31] Gong Q J, Li J Z, Xiang Y C, et al. Determination and classification of geochemical anomalies based on backgrounds and cutoff grades of trace elements: A case study in South Nanling Range, China[J]. Journal of Geochemical Exploration, 2018, 194: 44-51. [32] Wang J, Zuo R G. Identification of geochemical anomalies through combined sequential Gaussian simulation and grid-based local singularity analysis[J]. Computers & Geosciences, 2018, 118: 52-64. http://www.onacademic.com/detail/journal_1000040391359110_211b.html [33] Zhang D J, Cheng Q M, Agterberg F, et al. An improved solution of local window parameters setting for local singularity analysis based on Excel VBA batch processing technology[J]. Computers & Geosciences, 2016, 88: 54-66. doi: 10.1016/j.cageo.2015.12.012 [34] 贾琳, 石文杰, 魏俊浩, 等. 水平总梯度法在化探异常圈定中的应用: 以青海省某地区1∶5万水系沉积物地球化学测量为例[J]. 地质科技情报, 2019, 38(5): 71-80. https://www.cnki.com.cn/Article/CJFDTOTAL-DZKQ201905007.htmJia L, Shi W J, Wei J H, et al. Application of horizontal total gradient method in geochemical exploration anomaly setting: The geochemical survey of 1∶50 000 water sediments in area of Qinghai Province as an example[J]. Geological Science and Technology Information, 2019, 38(5): 71-80(in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-DZKQ201905007.htm [35] 黄啸坤, 魏俊浩, 石文杰, 等. 基于汇水盆地的化探异常识别与评价: 以东昆仑乌拉斯太地区1∶5万水系沉积物地球化学测量为例[J]. 地质科技通报, 2023, 42(1): 324-338. doi: 10.19509/j.cnki.dzkq.2021.0093Huang X K, Wei J H, Shi W J, et al. Identifying the geochemical anomalies using catchment basin analysis: The geochemical survey of 1∶50 000 stream sediments in Wulasitai region of East Kunlun Orogenic Belt as an example[J]. Bulletin of Geological Science and Technology, 2023, 42(1): 324-338(in Chinese with English abstract). doi: 10.19509/j.cnki.dzkq.2021.0093 [36] 廖时理, 陶春辉, 赵江南, 等. 基于便携式X射线荧光光谱(PXRF)分析的西南印度洋脊龙角区沉积物地球化学找矿研究[J]. 地质科技通报, 2022, 41(3): 264-272. doi: 10.19509/j.cnki.dzkq.2021.0068Liao S L, Tao C H, Zhao J N, et al. Application of PXRF in sediment analysis for geochemical prospecting in Dragon Horn area on the southwestern Indian Ridge[J]. Bulletin of Geological Science and Technology, 2022, 41(3): 264-272(in Chinese with English abstract). doi: 10.19509/j.cnki.dzkq.2021.0068 [37] 石文杰, 魏俊浩, 谭俊, 等. 基于滑动窗口对数标准离差法的地球化学异常识别: 以青海多彩地区1∶5万水系沉积物地球化学测量为例[J]. 地质科技情报, 2019, 38(5): 81-89. https://www.cnki.com.cn/Article/CJFDTOTAL-DZKQ201905008.htmShi W J, Wei J H, Tan J, et al. Identifying the geochemical anomalies using logarithmic standard deviation statistics method based on sliding window: The geochemical survey of 1∶50 000 water sediments in duocai region of Qinghai Province as an example[J]. Geological Science and Technology Information, 2019, 38(5): 81-89(in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-DZKQ201905008.htm [38] 张新铭, 魏俊浩, 石文杰, 等. 青海多彩当江地区水系沉积物元素地球化学结构特征及找矿方向[J]. 地质找矿论丛, 2019, 34(2): 302-314. https://www.cnki.com.cn/Article/CJFDTOTAL-DZZK201902019.htmZhang X M, Wei J H, Shi W J, et al. Geochemical characteristics of stream sediments and ore prospect orientation in Dangjiang area of Duocai Town, Qinghai Province[J]. Contributions to Geology and Mineral Resources Research, 2019, 34(2): 302-314(in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-DZZK201902019.htm [39] 王治华, 谭俊, 王凤林, 等. 多种区域化探数据处理方法及异常提取效果对比研究: 以青海小河坝地区水系沉积物测量为例[J]. 矿产勘查, 2019, 10(2): 321-332. https://www.cnki.com.cn/Article/CJFDTOTAL-YSJS201902024.htmWang Z H, Tan J, Wang F L, et al. A comparative study of several regional geochemical data processing methods and extraction effects of anomalies: A case study of stream system sediments in Xiaoheba area of Qinghai Province[J]. Mineral Exploration, 2019, 10(2): 321-332(in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-YSJS201902024.htm [40] Chen D J, Wei J H, Wang W H, et al. Comparison of methods for determining the thresholds of geochemical anomalies and the prospecting direction: A case of gold deposits in the Gouli exploration area, Qinghai Province[J]. Minerals, 2019, 9(6): 368. http://www.researchgate.net/publication/333874626_Comparison_of_Methods_for_Determining_the_Thresholds_of_Geochemical_Anomalies_and_the_Prospecting_Direction-A_Case_of_Gold_Deposits_in_the_Gouli_Exploration_Area_Qinghai_Province [41] Chen X, Zheng Y Y, Xu R K, et al. Application of classical statistics and multifractals to delineate Au mineralization-related geochemical anomalies from stream sediment data: A case study in Xinghai-Zeku, Qinghai, China[J]. Geochemistry: Exploration, Environment, Analysis, 2016, 16(3/4): 253-264. http://www.researchgate.net/publication/311267605_Application_of_classical_statistics_and_Multifractals_to_delineate_Au_Mineralization-Related_geochemical_anomalies_from_stream_sediment_data_A_case_study_in_Xinghai-Zeku_Qinghai_China [42] Zhang B Y, Li M Y, Li W X, et al. Machine learning strategies for lithostratigraphic classification based on geochemical sampling data: A case study in area of Chahanwusu River, Qinghai Province, China[J]. Journal of Central South University, 2021, 28(5): 1422-1447. doi: 10.1007/s11771-021-4707-9 [43] 马元林, 莫延强, 于小亮, 等. 青海祁连陇孔沟金矿1∶5万水系沉积物测量异常评价及找矿方向[J]. 矿产勘查, 2020, 11(9): 1993-1999. https://www.cnki.com.cn/Article/CJFDTOTAL-YSJS202009027.htmMa Y L, Mo Y Q, Yu X L, et al. Anomaly evaluation of 1∶50 000 stream sediment survey of the Longkonggou Gold Deposit in Qilian County, Qinghai Province and its prospecting direction[J]. Mineral Exploration, 2020, 11(9): 1993-1999(in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-YSJS202009027.htm [44] 田滔, 王斌, 邱瑜, 等. 青海东昆仑大格勒地区水系沉积物测量地球化学特征及找矿预测[J]. 中国锰业, 2019, 37(3): 63-67. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGMM201903018.htmTian T, Wang B, Qiu Y, et al. Geochemical characteristics and metallogenic prognosis of Dagele area in Qinghai Province based on stream sediment survey[J]. China's Manganese Industry, 2019, 37(3): 63-67(in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-ZGMM201903018.htm [45] 殷鸿福, 张克信. 东昆仑造山带的一些特点[J]. 地球科学: 中国地质大学学报, 1997, 22(4): 3-6. https://www.cnki.com.cn/Article/CJFDTOTAL-DQKX704.000.htmYin H F, Zhang K X. Characteristics of the Eastern Kunlun Orogenic Belt[J]. Earth Science: Journal of China University of Geosciences, 1997, 22(4): 3-6(in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-DQKX704.000.htm [46] 陈加杰. 东昆仑造山带东端沟里地区构造岩浆演化与金成矿[D]. 武汉: 中国地质大学(武汉), 2018.Chen J J. Paleozoic-Mesozoic tectono-magmatic evolution and gold mineralization in Gouli area, east end of East Kunlun Orogen[D]. Wuhan: China University of Geosciences(Wuhan), 2018(in Chinese with English abstract). [47] 杨宝荣, 张新铭, 李文君, 等. 青海沟里地区水系沉积物地球化学异常特征及找矿预测[J]. 地质科技情报, 2019, 38(4): 181-192. https://www.cnki.com.cn/Article/CJFDTOTAL-DZKQ201904019.htmYang B R, Zhang X M, Li W J, et al. Geochemical characteristics of stream sediments and ore prospecting orientation in Gouli area, Qinghai Province[J]. Geological Science and Technology Information, 2019, 38(4): 181-192(in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-DZKQ201904019.htm [48] 赵旭. 东昆仑造山带沟里地区构造岩浆转换与金成矿作用[D]. 武汉: 中国地质大学(武汉), 2020.Zhao X. Tectono-magmatic transformation and gold mineralization in the Gouli area, the East Kunlun Orogen[D]. Wuhan: China University of Geosciences(Wuhan), 2020(in Chinese with English abstract). [49] Xiong F H, Ma C Q, Zhang J Y, et al. The origin of mafic microgranular enclaves and their host granodiorites from East Kunlun, Northern Qinghai-Tibet Plateau: Implications for magma mixing during subduction of Paleo-Tethyan lithosphere[J]. Mineralogy & Petrology, 2012, 104(S3/4): 211-224. doi: 10.1007/s00710-011-0187-1 [50] Xu Z H, Xin W, Zhou X D, et al. Triassic granitoids in the East Kunlun Orogenic Belt, northwestern China: Magmatic source and implications for geodynamic evolution[J]. International Geology Review, 2020, 65(S1): 983-999. http://doc.paperpass.com/foreign/rgArti2020170330344.html [51] Xin W, Sun F Y, Zhang Y T, et al. Mafic-intermediate igneous rocks in the East Kunlun Orogenic Belt, northwestern China: Petrogenesis and implications for regional geodynamic evolution during the Triassic[J]. Lithos, 2019, 346/347: 105-159. [52] Dong Y P, He D F, Sun S S, et al. Subduction and accretionary tectonics of the East Kunlun Orogen, western segment of the Central China Orogenic System[J]. Earth-Science Reviews, 2018, 186: 231-261. http://d.wanfangdata.com.cn/periodical/2487fde443efcea3e9cd5496142d67c0 [53] 付乐兵, 魏俊浩, 谭俊, 等. 东昆仑沟里整装勘查区脉状金矿床多级构造控矿规律[J]. 矿物学报, 2015, 35(增刊1): 388-389. https://www.cnki.com.cn/Article/CJFDTOTAL-KWXB2015S1279.htmFu L B, Wei J H, Tan J, et al. Multistage structural ore control law of vein gold deposit in Gouli integrated exploration area, East Kunlun[J]. Acta Mineralogica Sinia, 2015, 35(S1): 388-389(in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-KWXB2015S1279.htm [54] Chen J, Wei J, Fu L, et al. Multiple sources of the Early Mesozoic Gouli batholith, Eastern Kunlun Orogenic Belt, northern Tibetan Plateau: Linking continental crustal growth with oceanic subduction[J]. Lithos, 2017, 292/293: 161-178. http://www.sciencedirect.com/science/article/pii/S0024493717303079 [55] 张昊, 李平. 归一化法在新疆巴勒尕依西地区化探数据处理中的应用[J]. 四川有色金属, 2015(1): 13-16. https://www.cnki.com.cn/Article/CJFDTOTAL-ACJS201501004.htmZhang H, Li P. The application of normalization of geochemical data in Balegayixi of Xinjiang Province[J]. Sichuan Nonferrous Metals, 2015(1): 13-16(in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-ACJS201501004.htm [56] 池顺都, 王淑华, 王学平. 化探数据系统分析的应用效果[J]. 地质科技情报, 1994, 13(3): 94-98. https://www.cnki.com.cn/Article/CJFDTOTAL-DZKQ403.019.htmChi S D, Wang S H, Wang X P. Radon measurements used in landslide investigations[J]. Geological Science and Technology Information, 1994, 13(3): 94-98(in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-DZKQ403.019.htm [57] 史长义, 赵永平, 刘莉. 矿产资源地球化学评价和预测的几个问题[J]. 地质与勘探, 2003, 39(6): 14-17. https://www.cnki.com.cn/Article/CJFDTOTAL-DZKT200306004.htmShi C Y, Zhao Y P, Liu L. On some problems about mineral resource geochemical assessment and prospecting prediction[J]. Geology and Prospecting, 2003, 39(6): 14-17(in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-DZKT200306004.htm [58] Cheng Q. Mapping singularities with stream sediment geochemical data for prediction of undiscovered mineral deposits in Gejiu, Yunnan Province, China[J]. Ore Geology Reviews, 2007, 32(1/2): 314-324. http://www.sciencedirect.com/science/article/pii/S0169136806001119 [59] 陈军林, 闫岩, 彭润民. 基于t-SNE降维算法的区域化探数据中地质体空间分布信息可视化: 以英格兰西南部为例[J]. 地质科技通报, 2021, 40(2): 186-196. doi: 10.19509/j.cnki.dzkq.2021.0217Chen J L, Yan Y, Peng R M. Visualization of geological spatial distributing information in regional geochemical explorartion data based on t-SNE algorithm: A case study of SW England[J]. Bulletin of Geological Science and Technology, 2021, 40(2): 186-196(in Chinese with English abstract). doi: 10.19509/j.cnki.dzkq.2021.0217 -
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