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新疆东天山彩霞山式铅锌矿多元地学信息找矿预测研究

Minerals Prediction Based on Caixiashan Lead-zinc Deposit by Integrating Geological Information in East Tianshan Area,Xinjiang Autonomous Region

【作者】 路璐

【导师】 朱立新; 肖克炎;

【作者基本信息】 中国地质科学院 , 地球探测与信息技术, 2012, 博士

【摘要】 东天山是中国有色金属、贵金属的重要成矿带,是全国固体矿产资源十六个重点成矿区带之一。该区地层分布齐全,沉积建造多样,地质构造复杂,岩浆活动频繁,变质变形作用明显,成矿历史悠久,成矿地质条件优越,目前的工作程度相对较低,近年来国土资源大调查在该区获得彩霞山大型铅锌矿的突破,说明该区找矿潜力巨大。本文以成矿系列理论为指导,以矿床模型综合地质信息预测技术为基本方法,以东天山区域小比例尺度范围内彩霞山式层控热液型铅锌矿预测研究为研究方向,围绕多元地学综合信息的筛选及预测模型的合理构建的理论与方法为核心,在充分收集消化研究区以往地质、矿产、化探、物探、遥感和钻孔等勘查资料以及厘清了彩霞山铅锌矿成矿机制和成矿规律的基础上,在MRAS矿产潜力评价平台上,从已知到未知,圈定了预测的远景靶区和资源量并进行了初步的评价,并对矿产资源勘查研究领域地学信息的部分问题开展了试验探索性研究。如何有效地识别和提取地球化学信息是本次论文地质定量化探研究的技术难点,针对这个问题一方面作者结合野外实测剖面和收集的区域化探扫面数据对矿体、矿区、区域三个维度的地球化学特征从不同层次不同角度进行研究,另一方面从数据处理角度对水系沉积物系统偏差校正问题在对比均值比值法、C型转换和移动衬值三种方法的基本原理以及在示范区As元素的应用效果择优选择适合本区的方法为移动衬值法,并使用非线性网络对重点的化探样品进行提取,然后将其取代传统方法中直接使用最高值样品点应用到化探预测因子的构建中。最后,如何将大比例尺原生晕发现的规律应用到小比例尺矿产资源量估算是本次论文的定量化研究的另外一个技术难点,针对这一问题作者以现代成矿成晕理论为指导,以实际矿床钻孔中高精度多元素的分析测试数据为支撑,建立深部成晕机制与地表地球化学示踪指标之间的内在联系,在资源量估算中引入剥蚀系数改进了传统的类比法。研究区共圈定出彩霞山式铅锌预测区39个,运用改进的类比法计算资源量为3288万吨。

【Abstract】 East Tianshan area is an important metallogenic belt of nonferrous metal and precious metal, and also one of the sixteen important metallogenic regions of non-fuel mineral resources in China. There has complete stratum, multiform sedimentary formations, complicated geologic structure, frequent magmatic activities, obvious metamorphosis, long metallogenic history and ascendant mineralization condition. But, it also has relatively lower working density. The exploration breakthroughs have been made in recent National Land and Resources Survey. Caixiashan lead-zinc deposit, for instance have been found, which foreshows great potential in this area.Using the theory of metallogenic series and the deposit model prediction technology of integrated geological information, this thesis made a research on the prediction of the Caixiashan type strata-bound hydrothermal lead-zinc deposits in the small scale range of eastern Tianshan region. Since the key of this method is the selection of the multivariate geological information and the construction of the prediction model, plenty of geological, mineral, geochemical, geophysical, remote sensing and drilling data were collected and analyzed, and the metallogenic regularity and mechanism of Caixiashan lead-zinc deposits were clarified. The perspective target area was delineated and preliminary evaluation was made based on the mineral potential evaluation platform of MRAS, and a pilot exploratory study of geological information in the field of mineral resources exploration was carried out.The technical difficulty of the quantitative geochemical exploration in this thesis is how to identify and extract geochemical information effectively. To solve this problem, on one hand, the author made a research on the geochemical characteristics in three dimensions of orebody, mining area and mining region based on the measured profiles and collected geochemical scanning data. On the other hand, compared with ratio method and C-transformation method, moving contrasting coefficient method was taken to deal with the system deviation of the stream sediment data since it has a better application effect for As in the representative area. Instead of the traditional method which used the sample with highest value, nonlinear network was used in the extraction of important geochemical samples for the first time, and it was applied to the construction of geochemical predictor. Finally, another problem of this research is how to do small-scale mineral resource estimation referring to the discovery pattern of large-scale primary halos. Following the modern metallogenic theory and primary halos theory, this thesis established the intrinsic link between the deep primary halos mechanism and the surface geochemical tracers. It improved the traditional areal productivity by introducing denudation coefficient into the resource estimation.At last,39optimal prospective areas were selected out and total resource of lead-zinc of this style is32.88Mt estimated by advanced analogy method.

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