吉林省和龙市南坪地区钼矿综合信息成矿预测研究
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摘要
南坪地区在吉林省延边朝鲜族自治州和龙市境内,大地构造上位于中朝准地台北缘东段之和龙地块,属古亚洲和濒西太平洋构造成矿域的结合部位。是中国地质调查局确定的16个重点成矿区带之一,地处辽东~吉南成矿带东部,在夹皮沟~和龙金铜镍成矿远景区与抚顺~和龙太古代铜金绿岩建造分布区的交叉部位,因而区域成矿条件良好。
     目前众多学者对成矿预测做了大量研究且各有特色,但我国目前成矿规律和成矿预测研究工作仍处于经验性的总结阶段,没有形成一套统一的理论体系,随着各种新理论、新方法的出现,成矿预测理论体系需要不断完善。针对这一现状本文选定和龙市南坪地区作为研究区域,以综合信息预测理论为指导思想,全面利用物探、化探所显示的地质找矿信息,通过对与区域成矿有关的基础地质问题的研究,实现了研究区钼资源定量预测评价,证明和龙东部南坪地区依然拥有巨大的找矿潜力可以发掘,为后续的找矿靶区优选及其资源评价提供了科学依据。
     本研究以综合成矿预测理论为指导,对南坪地区进行综合成矿预测,对研究区的成矿规律认识和找矿指导有所创新,对指导区域找矿勘查具有一定的实际意义。
     作者主要做了以下的研究工作:
     1、总结了南坪地区的成矿规律,初步查明研究区地层、岩浆岩、构造等基础地质特征及与成矿有关的主要地质因素。对南坪地区的典型矿床~石马洞矿床含矿岩体的规模、形态、产状及蚀变矿化特征进行了系统的分析和提炼。
     2、通过改进谢别德法对二维经验模态分解的包络方式,提高了其运算速度,并利用其对区域地球物理、地球化学数据进行了分析,提出新的基于经验模态分解的物、化探异常提取方法。能够提取比常规方法更丰富的与成矿有关的地球物理、地球化学信息,可从多个层面认识地球物理场、地球化学场的特征,对成矿远景区的圈定有重要作用。
     3、利用解析延拓等方法对研究区1:5万高精度磁测数据等资料进行了处理。对比向上延拓与二维经验模态分解后的结果可知,二维经验模态分解获得的IMF分量能更精确、客观地揭示和龙市南坪地区的地球物理(地质)结构特征。二维经验模态分解可以达到场分解的效果,不会出现信息混淆的情况。对IMF分量进行水平方向导数、垂向导数处理,通过研究区不同地质单元磁场空间形态的描述,对磁异常进行推断解释,重建研究区的构造框架,并在此基础上编制了磁性体分布图和构造解释图。
     4、利用南坪地区1:5万水系沉积物地球化学数据,合理确定Au、Ag、Mo、Cu、W等元素的异常下限,通过因子分析、相关分析、聚类分析等多元统计方法研究区域内各元素的分布富集特征及共生组合规律,确定地球化学异常找矿标志。并结合地球化学数据特点编制了单元素地球化学异常图、组合元素地球化学异常图、多元素累加地球化学异常图。
     5、研究工作基于GIS平台,结合石马洞典型矿床、成矿规律、地层、岩浆岩、构造等地质特征,以及物化探异常信息的研究,对地质统计单元进行了划分。提取了与矿床形成关系密切的各种能够直接或间接指示地下矿床存在的找矿标志作为预测变量,进一步通过地质—数学模型转换成为预测变量,对预测变量进行优化处理,建立了基于石马洞典型矿床的地、物、化综合找矿模型。
     6、以成矿预测理论为指导思想,运用模糊神经网络方法,结合找矿模型编制了综合信息成矿预测图,确定和优选了找矿靶区。根据不同的成矿条件,将找矿预测单元划分为三级:A级(找矿有利度>0.7)、B级(0.7>找矿有利度>0.6)、C级(0.6>找矿有利度>0.5)。其中A级预测单元对于找矿最为有利,最有希望发现钼矿床(体);B级预测单元找矿标志较为明显,有可能发现钼矿床(体);C级预测单元具有一定的找矿标志,有发现钼矿床的可能性。
     7、利用基于蒙特卡洛法的定量预测方法对矿产资源加以定量评价。经过模拟预测估算,吉林省和龙市南坪地区钼矿资源量在概率60%处大约为120000吨;80%处大约为65000吨。该区域已经探明的储量为48956吨,因此确定仍然有着大量的未知潜力矿体可供开发。
The Nanping area is located in the Yanbian Korean Autonomous Prefecture andHelong city.It is on the Helong block which is on the northern margin of Sino-Koreanparaplatform and plots, is the ancient Asian metallogenic domain. The Nanping area isone of the16Metallogenic belts which are identified by the China Geologicalsurvey.This area is in the eastern part of the Liaodong-Southern Jilin ore belt, andeast-and Jin Tongnie, the mineralization and Fushun-and too ancient bronzegreenstone formation distribution area of cross section, regional metallogeniccondition is good.
     At present, many scholars have done a lot of research and have their owncharacteristics. But the metallogenic regularities and metallogenic prediction researchin our country are still limited to empirical summary stage, did not formed a unifiedtheory system. With the emergence of a variety of new theories,new methods still need to constantly improve. This paper selected the Nanping areain Helong city and with integrated information prediction theory as the guide,strengthen and mineralization related to basic geological research, strengthen theregional metallogenic regularity, full use of geophysical, geochemical shows thegeological prospecting information; the forecasting technology, qualitative predictionin delineation basis, realization study on prediction of resource potential evaluation ofdistrict molybdenum, as follow-up to the optimization of prospecting targets in andprovide scientific basis for resource evaluation. This paper mainly focuses on thefollowing research work:
     1. At first, I summarize the Nanping regional metallogenic regularity.Preliminary I identify the basic geological characteristics of the stratigraphic,magmatic, tectonic and metallogenic geological’s factors. Papers on the Nanpingregion characteristic of ore deposits-ShiMa hole ore potentiality of rock mass scale,shape, form in altered mineralization and characteristics of the system are analyzedand refining.
     2. The2d empirical mode decomposition is a kind of decomposition method ofnonlinear data. This article uses the improved Xie Biede method, envelope methodand operation speed improvement. Through the two-dimensional empirical modedecomposition to obtain rich geochemical information for from multiple aspects of geophysical, geochemical field characteristics, extraction and mineralization related tocontent, metallogenic prospective area of objective prediction has important role.
     3. I collected1:50000geophysical (magnetic) data in the Nanping area, and usedjust like analytic continuation methods deal with the study area1:50000high precisionmagnetic survey data. I compared the upward continuation results with the empiricalmode decomposition, application of empirical mode decomposition for IMFcomponent more accurately, objectively reveals and city Nanping area geophysical(Geological) structural characteristics. And the application of empirical modedecomposition can reach field decomposition effect, there is no information confusedsituation, this article on the basis of research on the IMF components of the horizontaldirection, vertical direction derivative derivative processing, based on the differentgeological unit magnetic field space form of description, inference and interpretationof magnetic anomaly, reconstruction of study area tectonic framework, and on thebasis of the preparation of the magnetic body distribution and structure interpretationmap.
     4. Collected the Nanping1:50000stream sediment geochemical data, anddetermined the lower limited of the elements such as Au, Ag, Mo, Cu, W. This articleuse the factor analysis,correlation analysis, cluster analysis, multivariate statisticalmethods the distribution and enrichment of various elements in the studyarea characteristics and paragenesis, and identify the geochemical anomalyprospecting criteria. Combined with the geochemical data on the characteristics of thepreparation of a single-element geochemical anomaly maps, anomaly maps of thecomposite element geochemical anomaly map, multi-element geochemicalaccumulation.
     5. The reasearch work is based on the GIS platform,combined withthe Shima hole typical deposit, and metallogenic regularity of the known in the studyarea and stratigraphic, magmatic,tectonicand other geological features,and geologicalfeatures, and geophysical and geochemical anomalies, geostatistical unit has beendivided, extract and deposit close gelogicalsigns,be able to the geophysicalsign,geochemical,and other direct or indirectinstructions underground existenceof the deposit prospecting indicator as a predictor variable, and further convertedinto geological–mathematical model of the predictor variables to optimizethe predictor variable established based on the Shima hole typical deposits in theground,things of comprehensive prospecting model.
     6. Metallogenic prediction theory, the use of fuzzy neural network, combinedwith prospecting model based on the preparation of comprehensive informationmineralization forecast map to determine the mineralization prospect area, andpreferably prospecting targets. Depending on the ore-forming conditions,prospectingprediction unit is divided into three levels: level A(prospecting favorable>0.7),GradeB(0.7> prospecting beneficial degree>0.6), C-level (0.6> favorable prospecting> 0.5).Class A prediction unit is most favorable for prospecting, most have foundthat themolybdenum deposit (body); more obvious prediction unit B prospectingcriteria, may find that the molybdenum deposit (body); prediction unit C has acertain prospectingsigns, there is the possibility to find molybdenum deposit.
     7. Use of quantitative forecasting methods based on the Monte Carlo method tobequantitative evaluation of mineral resources, resource prediction, and then on theNanping area molybdenum reserves. Monte Carlo simulation and predictionestimates, Jilin Province and the Dragon Nanping molybdenum ore resources about120,000tons in the probability of60%;80%at about65,000tons, the region hasproven reserves of48,956tons, soto determine the study area is still a large number ofunknown potential ore body can be developed.
     In summary, the Nanping area in the east of the Helong city still has a hugeprospecting potential to explore, this study metallogenic prediction comprehensiveexploration of the study area has played a guidingrole to provide practical theoreticalbasis for further detailed investigation of evaluation.
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