本文選題：海洋重力異常場劃分　切入點：頻率域　出處：《中國海洋大學(xué)》2014年碩士論文　論文類型：學(xué)位論文

【摘要】：研究區(qū)域地質(zhì)構(gòu)造需要大量的地球物理信息，在眾多地球物理勘探方法中，重力勘探以其易實現(xiàn)、快捷、適用性強(qiáng)的特點得到廣泛應(yīng)用，重力資料也是地球物理資料中范圍最廣，信息最全的資料，故重力資料在研究中往往起著基礎(chǔ)性的作用，在大尺度、大深度的地質(zhì)構(gòu)造研究中，重力資料更是作為主要研究資料，重力場數(shù)據(jù)反演能提供其他物探資料所不能提供的信息。 重力異常反映的是地下剩余質(zhì)量的分布情況，主要是由地質(zhì)構(gòu)造或礦藏分布等引起的地下物質(zhì)密度不均勻分布造成的，將重力異常數(shù)據(jù)反演就能得到地下地質(zhì)構(gòu)造信息，但是重力異常是地下剩余質(zhì)量的綜合反映，想要得到更加具體和詳盡的構(gòu)造信息，在反演前首先要將重力異常進(jìn)行劃分，將不同地質(zhì)構(gòu)造引起的異常分開，分開后的重力異常反演就能得到更具體的構(gòu)造信息。傳統(tǒng)的二分法是將重力異常劃分為大尺度構(gòu)造引起的區(qū)域異常和小尺度構(gòu)造或地質(zhì)體引起的局部異常，傳統(tǒng)的劃分方法有高次求導(dǎo)、解析延拓、趨勢分析等，這些方法都是在空間域?qū)崿F(xiàn)重力異常的劃分，實際上區(qū)域異常與局部異常在頻率上一般存在較明顯的差異，我們可以在頻率域上根據(jù)異常的頻率差異實現(xiàn)異常的劃分，小波變換是一種較完美空間域與頻率域轉(zhuǎn)換工具，具有多尺度分析的優(yōu)點。并且通過Mallat算法與濾波器組的結(jié)合可以快速實現(xiàn)，小波的多尺度分解也更符合反演問題多解性的需求。小波分析的上述優(yōu)點使得它理論上能夠有效的實現(xiàn)重力異常的劃分。 本文主要是對小波多尺度分析實現(xiàn)重力異常劃分的技術(shù)研究，并通過實際海洋重力資料的處理驗證小波多尺度分析法的實際應(yīng)用效果，結(jié)合其他物探資料對劃分結(jié)果給出相應(yīng)的構(gòu)造分析。 論文的主要研究內(nèi)容和路線為：首先研究了重力位場和重力異常的基本特征與原理，研究了解析延拓法和高次求導(dǎo)實現(xiàn)異常劃分的數(shù)學(xué)原理并編程實現(xiàn)，之后研究了解了小波變換多尺度分析原理并結(jié)合Matlab編程實現(xiàn)，研究掌握了小波母函數(shù)選取原則，隨后建立重力異常數(shù)據(jù)模型，，分別使用解析延拓、高次求導(dǎo)和小波多尺度分析實現(xiàn)異常劃分，比較三種方法的優(yōu)缺點，在小波分析時嘗試不同的母小波和不同的分解階次，驗證了小波母函數(shù)的選取原則，選取了最符合實際情況的分解階次，最后將南海和東海某區(qū)域的海洋重力異常衛(wèi)星資料進(jìn)行了小波多尺度分析，結(jié)合相關(guān)性分析及地形數(shù)據(jù)對小波分解結(jié)果進(jìn)行了構(gòu)造分析。 研究表明小波分析能夠快速、高效、準(zhǔn)確的實現(xiàn)重力異常的劃分，和解析延拓法及高次求導(dǎo)法相比有明顯優(yōu)勢，實際海洋重力異常資料處理結(jié)果表明，小波分解的四階逼近值主要是由莫霍面起伏引起的，而四階細(xì)節(jié)則主要反映了沉積基底面的起伏。
[Abstract]:The study of regional geological structure requires a lot of geophysical information. Among many geophysical exploration methods, gravity exploration is widely used because of its easy realization, fast and strong applicability. Gravity data is also the most extensive and complete geophysical data, so gravity data often play a fundamental role in the study, in the large-scale, deep geological structure research, Gravity data as the main research data, gravity field data inversion can provide other geophysical data can not provide information. Gravity anomaly reflects the distribution of underground residual mass, which is mainly caused by the uneven distribution of underground material density caused by geological structure or mineral deposit distribution. The information of underground geological structure can be obtained by inversion of gravity anomaly data. But gravity anomaly is a comprehensive reflection of underground residual mass. In order to obtain more specific and detailed structural information, the gravity anomaly must be divided before inversion, and the anomalies caused by different geological structures should be separated. The conventional dichotomy is to divide gravity anomalies into regional anomalies caused by large scale structures and local anomalies caused by small scale structures or geological bodies. The traditional partitioning methods include high-order derivation, analytic continuation, trend analysis, etc. These methods all realize the division of gravity anomalies in spatial domain. In fact, there are obvious differences in frequency between regional anomalies and local anomalies. We can divide the anomaly in frequency domain according to the frequency difference of anomaly. Wavelet transform is a perfect conversion tool between spatial domain and frequency domain. It has the advantage of multi-scale analysis, and can be realized quickly by the combination of Mallat algorithm and filter bank. The multi-scale decomposition of wavelet is also more in line with the need of multi-solution of inverse problem. The advantages of wavelet analysis make it effective to partition gravity anomalies theoretically. In this paper, the technique of realizing gravity anomaly division by wavelet multi-scale analysis is studied, and the practical application effect of wavelet multi-scale analysis is verified by processing the actual marine gravity data. Combined with other geophysical data, the corresponding structural analysis of the division results is given. The main contents and routes of this paper are as follows: firstly, the basic characteristics and principles of gravity potential field and gravity anomaly are studied, and the mathematical principle of dividing anomaly by analytic continuation method and high order derivation is studied and realized by programming. Then, the principle of wavelet transform multi-scale analysis is studied and realized with Matlab programming, and the principle of selecting wavelet mother function is studied. Then, the gravity anomaly data model is established, and the analytic continuation is used respectively. High order derivation and wavelet multiscale analysis are used to realize abnormal partition, and the advantages and disadvantages of the three methods are compared. In wavelet analysis, different mother wavelets and different decomposition orders are tried, which verifies the selection principle of wavelet generating function. Finally, the wavelet multiscale analysis of the satellite data of marine gravity anomaly in the South China Sea and the East China Sea is carried out, and the wavelet decomposition results are constructed by combining the correlation analysis and topographic data. The research shows that wavelet analysis can realize the division of gravity anomaly quickly, efficiently and accurately, and has obvious advantages compared with analytic continuation method and high-order derivation method. The processing results of actual marine gravity anomaly data show that, The fourth order approximation value of wavelet decomposition is mainly caused by Moho surface fluctuation, while the fourth order detail mainly reflects the fluctuation of sedimentary basement surface.
【學(xué)位授予單位】：中國海洋大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：P631.1;P738.2

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