| 基于随机模拟技术和局部奇异性理论的地球化学异常不确定性分析 |
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| 引用本文： | 刘岳.基于随机模拟技术和局部奇异性理论的地球化学异常不确定性分析[J].地质与勘探,2019,55(6):1416-1425. |
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| 作者姓名： | 刘岳 |
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| 作者单位： | 中国科学院新疆生态与地理研究所新疆矿产资源研究中心,新疆乌鲁木齐 830011;新疆矿产资源与数字地质重点实验室,新疆乌鲁木齐 830011 |
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| 基金项目： | 本文由新疆自然科学基金面上项目（编号：2017D01A81）资助。 |
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| 摘 要： | 地球化学异常通常是直接按某个阈值将整个研究区划分为高异常区或低异常区,这可能导致一些重要异常信息的丢失或决策判断失误。从统计学角度分析,推断未采样点处可能取得结果的概率,或者刻画估计值大于或小于某一地球化学异常阈值的概率分布,更符合勘查地球化学找矿活动的实际需要。针对确定性地球化学场建模方法的局限性,本研究通过集成地统计随机模拟和局部奇异性理论实现地球化学异常识别及其不确定性度量。通过奇异性指数-分位数分析,刻画奇异性指数在频率域中的分布模式,实现地球化学异常阈值分割。采用局部不确定性和空间不确定性算法模拟地球化学异常不确定性传播过程,并以新疆西天山地区为研究区,开展铜异常识别及其不确定性评价应用研究。
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| 关 键 词： | 地统计随机模拟 局部奇异性理论 不确定性分析 异常识别 西天山地区 新疆 |
| 收稿时间： | 2018/3/22 0:00:00 |
| 修稿时间： | 2019/7/25 0:00:00 |
Uncertainty analysis of geochemical anomalies based on stochastic simulation and local singularity theory |
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| Liu Yue.Uncertainty analysis of geochemical anomalies based on stochastic simulation and local singularity theory[J].Geology and Prospecting,2019,55(6):1416-1425. |
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| Authors: | Liu Yue |
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| Institution: | Xinjiang Research Centre for Mineral Resources, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, Xinjiang; Xinjiang Key Laboratory of Mineral Resources and Digital Geology, Urumqi, Xinjiang |
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| Abstract: | It is a common way that geochemical anomalies are directly separated into high or low anomalous zones in the study area based on a geochemical threshold, which may miss some important information or lead to wrong decision-making. From a statistical perspective, inferring the possible probability of un-sampled points or describing the probability distribution that the estimated values are greater or less than a certain geochemical anomaly threshold is more reasonable for actual needs in the geochemistry prospecting. To solve the limitations of deterministic geochemical modeling, this work combines geostatistical stochastic simulation and multifractal local singularity theory to identify geochemical anomalies and measure its uncertainty. In order to determine geochemical anomaly thresholds, the singularity index analysis is performed to characterize the distribution patterns of geochemical anomalies in the frequency domain by integrating singularity analysis and quantile-quantile plots. A geochemical anomaly uncertainty evaluation model is established by means of local uncertainty and spatial uncertainty algorithms that are employed to simulate uncertainty propagation processes of geochemical anomalies. This paper presents the method aforementioned in detail using an example of indentifying Cu anomalies and evaluating their uncertainty in the West Tianshan area, China. |
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| Keywords: | geostatistical stochastic simulation local singularity analysis geochemical anomaly identification uncertainty assessment West Tianshan |
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