小波分析在矿井高密度电法数据处理中的应用

矿井高密度电阻率法数据由于受地电干扰、地形、接地电阻等因素的影响,通常会遇到具有一定水平尺度和垂向幅度的类似尖脉冲假异常。在数据处理过程中,对于高幅度和宽尺度的噪声,特别是与有用信息的幅度及尺度相近时,即使应用广泛的Donoho软阈值函数和硬阈值函数去噪,也存在着难以克服的问题。为此提出了一种基于线性软阈值的去噪方法：根据噪声尺度确定分解层数,而每一层的阈值则采用线性函数确定。通过实测资料分析可知,这种方法能有效地消除高频随机噪声和特定尺度的噪声,尤其是在处理类似尖脉冲的噪声信号时有较好的效果,同时又能较好地保持原有地质信息。

Application of Wavelet Analysis in Coalmine High-Density Electric Prospecting Data Processing

Since the impacts from factors of earth current disturbance, landform, earth resistance etc, the mine high density resistivity data will incur quasi-spike pulse false anomaly with certain horizontal scale and vertical amplitude. In data processing, in regard to high amplitude and wide scale noises, especially when amplitude and scale close to that of useful information, even though to use the vastly used Donoho＇s soft and hard threshold de-noise, will also confront with issues hard to be overcome. Thus a method based on linear soft threshold de-noise put forward： according to noise scale determining decomposition levels, while threshold of every level is determined by a linear function. Through the analysis of measured data, we can find that the method can eliminate high frequency random and target scale noises, especially better effect in quasi-spike pulse noise signal processing, and maintaining original geological information better.