本文選題：水系沉積物　切入點：低弱地球化學(xué)異常　出處：《吉林大學(xué)》2017年博士論文

【摘要】：我國于上世紀(jì)70年代開展的1:20萬水系沉積物地球化學(xué)測量工作已基本覆蓋山區(qū)和半山區(qū)。1:20萬水系沉積物地球化學(xué)測量是低成本、高效率的礦產(chǎn)勘查方法,在圈定成礦遠(yuǎn)景區(qū)(帶)、尋找礦田和大、中型礦床,特別是有色、貴金屬礦床的勘查中發(fā)揮了極其關(guān)鍵的作用。隨著我國礦產(chǎn)勘查工作的不斷深入,地表礦、淺部礦以及易識別礦逐漸減少,找礦的重點逐步轉(zhuǎn)向?qū)ふ译[伏礦、半隱伏礦和難識別礦。目前我國積累的海量高質(zhì)量的1:20萬水系沉積物地球化學(xué)數(shù)據(jù)仍將在未來的地質(zhì)找礦中發(fā)揮重要作用。經(jīng)過多年的工作,雖然1:20萬水系沉積物的“高、大、全”地球化學(xué)異常幾乎被評價殆盡,但其中仍蘊含的大量有找礦價值的低、弱地球化學(xué)異常信息值得進(jìn)一步挖掘。研究表明,大礦不一定有大異常,大異常不一定有大礦,礦致異常的規(guī)模與強度受諸多因素制約。近些年我國在低弱異常區(qū)陸續(xù)發(fā)現(xiàn)一系列礦床的事實充分證明了低弱地球化學(xué)異常的找礦價值。目前,尚無完善的水系沉積物低弱地球化學(xué)異常識別的有效方法,因此研究探索低弱地球化學(xué)異常識別理論與方法具有實際意義。本文以湖南省1:20萬水系沉積物為主要研究對象,同時選擇了其他景觀區(qū)的水系沉積物進(jìn)行了相關(guān)研究。論文重點研究了湖南省水系沉積物的地球化學(xué)特征,剖析了水系沉積物元素地球化學(xué)背景的影響因素,研究了地球化學(xué)背景影響因素的消除方法,在此基礎(chǔ)上,提出了基于正態(tài)分布的異常提取方法和基于多元非正態(tài)總體的異常提取方法。湖南省水系沉積物地球化學(xué)成分具有明顯的空間差異,通過K均值聚類方法將湖南省分為六個地球化學(xué)區(qū),不同地球化學(xué)區(qū)的元素背景值具有一定的差異。研究表明,水系沉積物元素地球化學(xué)背景受研究尺度、巖性背景、樣品粒度、景觀條件等多種因素的影響,其中基巖巖性的影響尤為顯著。在巖性復(fù)雜區(qū),由于水系沉積物來源于多個“母體”,元素含量概率分布通常呈現(xiàn)出多“母體”的混合分布,元素含量概率分布圖上往往表現(xiàn)出“多峰”的特點。地質(zhì)背景(特別是巖性背景)對元素背景的影響,其結(jié)果可能導(dǎo)致有價值的低弱地球化學(xué)異常被掩蓋,同時可能誤將元素背景含量高的地質(zhì)體圈定成“異�！�。為了消除巖性背景的影響,本文提出了以K均值聚類和穩(wěn)健回歸分析為核心的地球化學(xué)背景影響因素消除方法。該方法以水系沉積物中可以表征巖性特征的造巖元素以及親石元素含量為基礎(chǔ),通過K均值聚類算法將樣品分為多個子類,檢查每個子類中元素與主要氧化物(如Si O2、Fe2O3)的相關(guān)性。對于與主要氧化物無明顯相關(guān)關(guān)系的元素,首先對該元素數(shù)據(jù)進(jìn)行正態(tài)變換,剔除異點后計算均值和標(biāo)準(zhǔn)差,用均值和標(biāo)準(zhǔn)差對數(shù)據(jù)進(jìn)行標(biāo)準(zhǔn)化。對于與主要氧化物呈顯著相關(guān)關(guān)系的元素,建立該元素與主要氧化物的回歸方程,采用穩(wěn)健回歸方法求解待定系數(shù),計算回歸值和標(biāo)準(zhǔn)殘差,然后用回歸值和標(biāo)準(zhǔn)殘差對數(shù)據(jù)進(jìn)行標(biāo)準(zhǔn)化。最后形成標(biāo)準(zhǔn)化的正態(tài)分布的基礎(chǔ)數(shù)據(jù)。以湖南省桂陽地區(qū)和瀏陽地區(qū)1:20萬水系沉積物數(shù)據(jù)為例進(jìn)行了分析,發(fā)現(xiàn)原始數(shù)據(jù)多為偏態(tài)或多峰分布,而經(jīng)過處理的數(shù)據(jù)均接近均值為0、標(biāo)準(zhǔn)差為1的標(biāo)準(zhǔn)正態(tài)分布,在很大程度上消除了地質(zhì)背景的影響。消除背景影響的標(biāo)準(zhǔn)化數(shù)據(jù)突出了一些低弱地球化學(xué)異常,壓制了高背景,使得異常與已知礦床的吻合更好。對于樣品粒級、系統(tǒng)誤差以及景觀條件的影響,本文采用了分幅標(biāo)準(zhǔn)化方法進(jìn)行消除。本文分析了常規(guī)等值線異常圖的弱點,提出了基于正態(tài)分布的標(biāo)準(zhǔn)化數(shù)據(jù)元素組合異常色塊編圖法,采用主成礦元素與成礦伴生元素相結(jié)合的方式,將采樣點位以一個色塊表示,每個色塊分為9個小方格,每個方格代表一種元素,然后采用相應(yīng)倍數(shù)的標(biāo)準(zhǔn)偏差表示異常強度。研究表明,該方法可以傳達(dá)更豐富的關(guān)于異常強度以及礦床剝蝕程度的信息,可以提高異常圈定的準(zhǔn)確度。該方法充分考慮了熱液礦床元素垂直分帶規(guī)律和研究區(qū)不同礦種異常元素組合特點。與傳統(tǒng)等值線法相比具有信息量大、異常位置準(zhǔn)確、易使用等特點。以消除背景影響的標(biāo)準(zhǔn)化正態(tài)數(shù)據(jù)為基礎(chǔ),對傳統(tǒng)的馬氏距離背景與異常劃分方法進(jìn)行了改進(jìn),提出了基于多元正態(tài)總體的異常提取方法和馬氏距離異常圖編制方法。本文提出的馬氏距離異常圖具有簡單、直觀的特點,可以展示出每個點位的異常元素組合信息。通過實例研究,發(fā)現(xiàn)馬氏距離方法圈定的異常位置與已知礦床吻合較好,突出了弱小異常。利用多維數(shù)據(jù)信息,從多元角度刻畫元素異常,有利于進(jìn)行低弱異常識別,提高異常的預(yù)測精度。研究表明,水系沉積物中一些元素的含量,即使消除了巖性背景的影響,其標(biāo)準(zhǔn)化數(shù)據(jù)也難以符合正態(tài)分布,甚至近似正態(tài)分布。在這種情況下,采用基于正態(tài)分布理論的水系沉積物地球化學(xué)異常提取方法是不合適的。為此,本文提出了適合非正態(tài)分布高維數(shù)據(jù)的基于實碼加速遺傳算法的投影尋蹤模型,將高維數(shù)據(jù)投影到一維子空間,依據(jù)投影值的大小來提取地球化學(xué)異常。該方法不僅可以解決上述方法的數(shù)據(jù)正態(tài)分布限制,也可以充分利用礦化過程中虧損元素的信息,充分利用數(shù)據(jù)中的有效信息并避免其他信息的干擾。實例研究表明,采用消除背景的標(biāo)準(zhǔn)化數(shù)據(jù)的投影尋蹤方法可以發(fā)現(xiàn)傳統(tǒng)方法無法發(fā)現(xiàn)的低弱異常信息。水系沉積物低弱地球化學(xué)異常提取是地球化學(xué)數(shù)據(jù)處理過程中的關(guān)鍵問題,本文提出的一系列方法對于背景消除理論方法方面有了一定的創(chuàng)新和補充。基于消除背景的標(biāo)準(zhǔn)化數(shù)據(jù)的多元地球化學(xué)異常提取方法能夠有效地識別低弱異常,壓制高背景,將多元數(shù)據(jù)融合的化探異常評判也符合多元信息集成的發(fā)展趨勢。本文提出的方法對于低弱地球化學(xué)異常識別與提取方面具有一定的理論以及實際意義。
[Abstract]:1:20 000 stream sediment geochemical survey in China in the last century in 70s has basically covered.1:20 of mountainous and semi mountainous 000 stream sediment geochemical survey is of low cost, high efficiency method in mineral exploration, delineated metallogeneticprospective provinces (zones), looking for ore field and large, medium-sized deposits, especially nonferrous, plays the key role of the exploration of precious metal deposits in mineral exploration in China. With the deepening of the work, surface mine, shallow mine and easy to identify ore prospecting focus gradually reduced, and gradually turn to search for concealed deposits, half concealed ore deposits and ore difficult to identify. Play an important role in massive accumulation of China's high quality at 1:20 000 stream sediment geochemical data will remain in the future geological prospecting. After years of work, although the 1:20 000 stream sediment "high, big, the whole" geochemical anomaly evaluation was almost exhausted, but the Still contains a large number of a prospecting value low, weak geochemical anomaly information mining. Further research shows that large deposits do not necessarily have unusual large abnormalities does not necessarily have large deposits, ore size and strength of the anomaly is restricted by many factors. In recent years our country in the low anomaly areas have found a series of ore deposits the fact proves that the weak geochemical anomaly prospecting value. At present, there is no perfect effective method to identify the low sediment geochemical anomaly, so exploring weak geochemical anomaly identification theory and method has practical significance. This paper takes Hunan province 1:20 000 stream sediment is the main research object, and choose the other sediments the landscape was studied. The paper focuses on the geochemical characteristics of stream sediment in Hunan Province, analyzes the elements of stream sediment geochemical background The influence factors on the method of eliminating the effect of geochemical background factors, on this basis, put forward the anomaly extraction method based on normal distribution and based on the multiple abnormal extraction method. The overall Hunan province stream sediment geochemical composition has obvious differences in space, through the K means clustering method divides Hunan province six geochemical regions, with some differences in background values in different geochemical zones. The study shows that the elements in stream sediment geochemical background of scale, lithological background, sample size, a variety of factors which affect the landscape conditions, bedrock lithology is particularly significant. In areas with complex lithology, due to sediment source in the "matrix", mixed distribution elements in the probability distribution are usually more "parent", elements of probability distribution often show multi peaks" The characteristics of geological background (especially lithologic background) influence on the element background, could result in lacking of valuable geochemical anomalies to be covered, and may mistakenly delineate geological body element background with high content of "abnormal". In order to eliminate the influence of lithology background, using K means clustering and robust the regression analysis method to eliminate the influence factors of geochemical background as the core. The method to build rock sediments can characterize lithologic characteristics of elements and lithophile element content as the basis, the sample is divided into several sub classes by K means clustering algorithm, the elements of each sub class were examined with major oxides (such as Si O2, Fe2O3) for the correlation. And there was no obvious correlation between the main oxide elements, first normal transformations of the data elements, get rid of abnormal after the calculation of the mean and standard deviation of data using the mean and standard deviation Standard. For there was a significant correlation with the main oxide elements, establish regression equation of the main elements and oxides, using robust regression for the undetermined coefficient method, regression calculation value and standard error, and then use the return value and standard error of standard data. Finally the formation of basic data distribution of normal standard by 1:20. 000 stream sediment data in Hunan area and Liuyang area of Guiyang Province as an example to analyze, and find that the original data is more skewed or multi peak distribution, and the processed data are close to the mean value is 0, the standard deviation is 1 of the standard normal distribution to a great extent to eliminate the effect of geological background. Standard data. Eliminate the background effect highlights some of the weak geochemical anomalies, suppress the high background, the anomaly and agree better known deposits. For sample size, system error and landscape The effects of the condition in the picture of the standard method eliminated. This paper analyses the conventional contour map of abnormal weakness, put forward the normal distribution of the standard data element mapping method based on the combination of abnormal color, the main ore-forming elements associated with mineralization elements combination, the sampling points to a color, each color is divided into 9 small squares, each square represents an element, then the standard deviation of the corresponding multiples of said anomaly intensity. The results show that the method can convey more about abnormal strength and deposit erosion degree information, can improve the accuracy of the anomaly. This method takes full account of the hydrothermal deposit elements of vertical zoning and research area of different mineral anomaly elements. Compared with the traditional contour method with a large amount of information, the abnormal position is accurate, easy to use features to eliminate. Standard background of normal data based on Mahalanobis distance background and anomaly classification method to improve traditional proposed anomaly map compilation method of anomaly extraction method and Mahalanobis distance in multivariate normal population. Based on Mahalanobis distance anomaly map is proposed in this paper has a simple, intuitive, can show the abnormal elements combining the information of each point. Through case study, found that the delineation of Mahalanobis distance method and abnormal position of known deposits in good agreement, highlighting the weak anomalies. Using multidimensional data, from the multi angle description element abnormal, to identify the weak anomalies, improve the prediction accuracy of the anomaly. The study shows that the content of some elements in stream sediments the even eliminates the influence of lithology background, the standard data to conform to normal distribution, and the approximate normal distribution. In this case, using the base Yu Zheng normal distribution theory of stream sediment geochemical anomaly extraction method is not appropriate. Therefore, this paper put forward a non projection pursuit model of real coded accelerating genetic algorithm based on the normal distribution of high dimensional data, high-dimensional data is projected to one dimensional subspace, based on the projection values to extract the geochemical anomalies. The method can not only solve the above method data of normal distribution, also can make full use of the loss element mineralization in the process of information, make full use of effective information interference in the data and avoid other information. The case study shows that the elimination of projection pursuit method standard data background can be found in the weak abnormal information can not be found by traditional methods low. Stream sediment geochemical anomaly extraction is the key problem in geochemical data processing, a series of methods proposed for back On the view of innovation and elimination theory method is supplemented. Multiple Geochemical Standard data to eliminate background anomaly extraction method can effectively identify the weak anomaly based on the suppression of high background, the development trend of the multivariate data fusion geochemical anomaly evaluation with multi information integration. This method has a certain the theoretical and practical significance for the identification of weak geochemical anomalies and extraction.

【學(xué)位授予單位】：吉林大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2017
【分類號】：P632

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