Gold Anomaly Identification and Its Uncertainty Analysis in the West Junggar Belt, Xinjiang
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摘要: 西准噶尔成矿带地处中亚成矿域核心区，伴随着古生代强烈的构造岩浆活动，发生了广泛的金成矿作用，形成了一系列金矿床、矿点及矿化点，如萨尔托海、哈图、包古图等金矿床，已成为我国重要的黄金开发基地之一.基于该成矿带水系沉积物地球化学数据，采用集成序贯指示模拟技术和多重分形局部奇异性分析方法，开展金异常信息识别及其不确定性定量模拟，有效突出局部异常和弱缓异常，实现金元素富集异常在空间上的概率分布与量化表达.研究结果显示，金奇异性指数小于2的条件下，金元素富集异常的高概率区与已知金矿产地在空间分布上非常吻合，该研究可为西准噶尔成矿带金矿勘查及其不确定性风险评估提供决策依据.Abstract: West Junggar belt, located in the core area of the Central Asian metallogenic domain, is one of the most important gold development bases in China. Accompanying intense tectonic and magmatic activities, extensive gold mineralization occurred during Paleozoic and a series of gold deposits/occurrences and mineralized points have been discovered in the West Junggar belt such as Sartohay, Hatu and Baogutu gold deposits. In the present study, the methods of local singularity analysis and sequential indicator simulation were employed to identify gold anomaly and model its uncertainty based on stream sediment geochemical data sampled from West Junggar belt, which allows for enhancing local and weak anomalies effectively. The results of simulation can be used to express probability distribution pattern of gold anomalies characterized by singularity indices less than 2. The results indicate that high probability zones of gold anomalies are closely associated with known gold deposits/occurrences, which provides an important decision-making for risk evaluation of gold resource exploration in the West Junggar belt.
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图 1 西准噶尔成矿带大地构造简图(a)，西准噶尔成矿带地质简图(b)
Fig. 1. Tectonic framework for the West Junggar belt (a), geological sketch of the West Junggar belt (b)
图 3 9个类型变量的经验变异图和拟合的指数模型
Fig. 3. Experimental variograms and the fitted exponent models of nine categorical variables
图 4 随机选取的4个金元素含量的模拟实现
a.模拟实现#35；b.模拟实现#77；c.模拟实现#123；d.模拟实现#234
Fig. 4. Random selected four simulation realizations of Au concentrations
图 5 4个金含量模拟实现对应的4个金奇异性指数模拟实现
a.#35；b.#77；c.#123；d.#234
Fig. 5. Four simulation realizations of Au concentration corresponding to four Au simulation singularity index realizations
图 6 均值型金奇异性指数α估计(a)；奇异性指数α=2作为阈值分割点(b)
Fig. 6. E-type Au simulation singularity index realization (a), singularity index with α=2 as threshold value (b)
图 7 金奇异性指数α＜2条件下：连续型金异常概率值分布模式(a)，金异常概率值大于0.5的空间分布特征(b)，金异常概率值大于0.7的空间分布特征(c)
Fig. 7. Under the condition of α < 2: probability distribution of Au anomaly with continuous values (a), probability distribution of Au anomaly with probability values larger than 0.5 (b), probability distribution of Au anomaly with probability values larger than 0.7 (c)
表 1 9个类型变量的半变异模型参数
Table 1. Semi-variation model parameters of nine categorical variables
截值(%) 块金值 基台值 变异系数(%) 相关系数 残差平方和 变程(m) 10 0.061 0.033 64.89 0.844 9.80×10-5 28 000 20 0.107 0.061 63.69 0.874 7.01×10-4 35 000 30 0.122 0.099 55.20 0.933 4.19×10-4 39 900 40 0.142 0.110 56.35 0.955 4.89×10-4 53 000 50 0.117 0.138 45.88 0.826 2.38×10-3 48 000 60 0.108 0.127 45.96 0.831 2.13×10-3 48 800 70 0.095 0.106 47.26 0.829 1.99×10-3 45 000 80 0.072 0.082 46.75 0.852 6.15×10-4 39 000 90 0.052 0.035 59.77 0.692 2.02×10-4 29 000 
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