【摘要】：地球化學(xué)數(shù)據(jù)處理是勘查地球化學(xué)找礦中很重要的一部分，它主要是對(duì)采集的化探數(shù)據(jù)進(jìn)行處理，包括數(shù)據(jù)加工、數(shù)據(jù)分析、數(shù)據(jù)可視化以及數(shù)據(jù)的解釋問(wèn)題。在地球化學(xué)數(shù)據(jù)處理工作中，需要完成的階段性目標(biāo)有：區(qū)分研究區(qū)域的背景和異常，根據(jù)確定的背景異常來(lái)確定與成礦有關(guān)聯(lián)的元素的組合規(guī)律以及各元素間的空間變化規(guī)律等。 小波變換是近些年化探數(shù)據(jù)處理的一個(gè)新的分支，它能夠有效的從化探數(shù)據(jù)中提取有用的信息,通過(guò)伸縮和平移等對(duì)化探數(shù)據(jù)進(jìn)行多尺度細(xì)化分析，這就為地球化學(xué)數(shù)據(jù)的非線性分析提供了理論依據(jù)。 論文將小波變換工具應(yīng)用于地球化學(xué)數(shù)據(jù)處理。首先對(duì)于研究區(qū)域中采集到的化探元素?cái)?shù)據(jù)做地球化學(xué)降噪處理，在保持原有數(shù)據(jù)有效性的同時(shí)，減少了地球化學(xué)數(shù)據(jù)中某些誤差產(chǎn)生的影響。所用的方法是小波閾值去噪法。針對(duì)閾值去噪過(guò)程中，最主要的幾個(gè)參數(shù)：最優(yōu)小波基，閾值，閾值函數(shù)，分解層數(shù)做了探討分析，得出適合于本次試驗(yàn)的閾值去噪?yún)?shù)，并表明小波變換工具在處理地球化學(xué)數(shù)據(jù)時(shí)能夠通過(guò)時(shí)頻分析，將小波分解后的細(xì)節(jié)信息更加突出，小波閾值降噪能夠很好的去除化探數(shù)據(jù)中的噪聲。通過(guò)對(duì)閾值函數(shù)的選擇對(duì)比發(fā)現(xiàn)，改進(jìn)閾值函數(shù)在處理地球化學(xué)數(shù)據(jù)時(shí)有一定的局限性，并不總是優(yōu)越于傳統(tǒng)的閾值函數(shù)，在處理地球化學(xué)數(shù)據(jù)時(shí)，有必要根據(jù)實(shí)際情況選擇合適的閾值函數(shù)。其次對(duì)去除噪聲后的地球化學(xué)數(shù)據(jù)做地球化學(xué)場(chǎng)數(shù)據(jù)分析，采用不同的背景來(lái)區(qū)分異常，得出不同背景下各個(gè)元素的異常等值線圖并作分析，表明不同背景值下元素的異常區(qū)域不同，選擇不同背景值有利于弱異常分布情況的客觀反映與提取，，同時(shí)使強(qiáng)異常區(qū)域更為突出。最后利用不同背景下的元素異常信息，確定與成礦有關(guān)的共生組合元素，利用與成礦有關(guān)的元素異常疊加圖形成的交集區(qū)域，結(jié)合地質(zhì)資料信息，初步推測(cè)異常區(qū)域可能存在的礦產(chǎn)資源。 總之,本文選取小波分析的方法來(lái)對(duì)地球化學(xué)數(shù)據(jù)進(jìn)行分析處理以及基于不同背景下的數(shù)據(jù)場(chǎng)分析，旨在為地球化學(xué)數(shù)據(jù)處理與異常分析以及礦產(chǎn)資源預(yù)測(cè)提供一種新的技術(shù)方法。
[Abstract]:Geochemical data processing is an important part of exploration geochemical prospecting. It mainly deals with collected geochemical data, including data processing, data analysis, data visualization and data interpretation. In the process of geochemical data processing, the objectives to be accomplished are to distinguish the background and anomaly of the study area. According to the determined background anomaly, the combination law of the elements associated with the mineralization and the law of spatial variation among the elements are determined. Wavelet transform is a new branch of geochemical data processing in recent years. It can effectively extract useful information from geochemical data and analyze geochemical data by scaling and translation. This provides a theoretical basis for nonlinear analysis of geochemical data. In this paper, wavelet transform tool is applied to geochemical data processing. Firstly, geochemical noise reduction is done for geochemical exploration element data collected in the study area, which not only maintains the validity of the original data, but also reduces the influence of some errors in the geochemical data. The wavelet threshold denoising method is used. In the process of threshold denoising, the most important parameters, such as the optimal wavelet basis, the threshold function, the number of decomposition layers, are discussed and analyzed, and the threshold denoising parameters suitable for this experiment are obtained. It is shown that wavelet transform tool can deal with geochemical data through time-frequency analysis, and the detail information after wavelet decomposition is more prominent. Wavelet threshold de-noising can remove the noise in geochemical data very well. By comparing the selection of threshold function, it is found that the improved threshold function has some limitations in dealing with geochemical data and is not always superior to the traditional threshold function. It is necessary to select an appropriate threshold function according to the actual situation. Secondly, the geochemical data after noise removal are analyzed by geochemical field data. Different backgrounds are used to distinguish anomalies, and the anomalous isoline maps of each element in different backgrounds are obtained and analyzed. The results show that the anomaly regions of elements are different under different background values. The selection of different background values is beneficial to the objective reflection and extraction of the distribution of weak anomalies and makes the strong anomaly regions more prominent. Finally, by using the element anomaly information under different background, the symbiotic assemblage elements related to metallogenesis are determined, and the intersection area formed by the superposition map of the elements related to mineralization is used to combine the geological data information. The possible mineral resources in anomalous regions are preliminarily speculated. In a word, wavelet analysis method is selected to analyze and process geochemical data and data field analysis based on different background. This paper aims to provide a new technical method for geochemical data processing, anomaly analysis and mineral resource prediction.
【學(xué)位授予單位】：內(nèi)蒙古科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類(lèi)號(hào)】：P632

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