Gravity and Magnetic Anomaly Separation Based on Bidimensional Empirical Mode Decomposition
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摘要: 由于地质过程的复杂性及成矿过程的多期次叠加性,原始重磁异常往往是多种地质因素的混合信息,既包含区域背景异常信息,也包含与矿床(体)、矿化蚀变带以及隐伏岩体等与找矿密切相关的地质要素所引起的局部重磁异常.如何从复杂的叠加重磁异常中分离出具有找矿意义的局部异常,是当前矿产勘查和资源潜力评价工作中面临的难题之一.采用经验模态分解(EMD)方法来分解重磁异常,为提高分解的稳健性提出了用双调和样条插值(BSI)进行包罗面插值的新方法,并以云南个旧地区重磁数据为例,对其进行非线性多尺度分解,实现对区域异常与局部重磁异常的分离,揭示了深层次找矿信息并拓宽了经验模态分解方法的应用领域.Abstract: Geological process often experienced a number of causal or complex genetic stages, which often resulted in original gravity and magnetic anomaly composed of various geological elements including background anomaly, and local anomaly which may be caused by deposits, alternation and concealed rocks, etc., which are associated with mineral exploration and prospecting. It is one of the most difficult issues in mineral prospecting and potential resource assessment as how to separate gravity and magnetic anomaly, which is significant for mineral exploration from original composite anomaly. Empirical mode decomposition (EMD) is considered to be an effective method in superimposed information separation. In this paper, a new bidimensional empirical mode decomposition (BEMD) method is proposed, that is, biharmonic spline interpolation (BSI) instead of general spline interpolation for improving stability. As a case study, gravity and magnetic data in Gejiu, Yunnan, China, have been used to extract local anomaly which could reveal potential information in mineral exploration by multiscale and nonlinear decomposition with BEMD method. It extends the application of empirical mode decomposition.
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表 1 各模态函数的相关系数
Table 1. Correlation coefficients of IMFs
IMF1 IMF2 IMF3 IMF4 IMF5 Residue IMF1 1.000 -0.299 -0.131 -0.106 0.044 -0.044 IMF2 -0.299 1.000 -0.090 -0.136 0.057 -0.049 IMF3 -0.131 -0.090 1.000 -0.147 -0.099 0.077 IMF4 -0.106 -0.136 -0.147 1.000 0.003 -0.027 IMF5 0.044 0.057 -0.099 0.003 1.000 -0.993 Residue -0.044 -0.049 0.077 -0.027 -0.993 1.000 -
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