利用水平导数与垂向导数标准偏差的相关系数法识别磁源边界

基于导数换算的边界检测技术在位场数据处理与解释中具有重要应用,但是高阶导数算法极易受到干扰噪声的影响,稳定性较差。鉴于此,本文提出利用水平导数与垂向导数标准偏差的相关系数进行边界检测,该方法是基于水平导数与垂向导数的标准偏差在地质体边界位置处呈现负相关性实现的。理论模型试验表明:该方法不仅可以识别出不同深度的异常体的边界位置,而且受噪声影响较小,计算稳定性更强。将本文方法应用于海拉尔盆地实测航磁数据,检测结果与实际资料有着较好的对应关系。

Identification of magnetic source boundaries using correlation coefficients of standard deviation of horizontal and vertical derivatives

Edge detection methods based on derivation calculation of the potential field have significant applications in data processing and interpretation. However, high-order derivative algorithms are susceptible to noise disturbance, leading to instability of results. To solve this problem, we propose a new boundary detection method using the correlation coefficients of standard deviation of horizontal and vertical derivatives. It is feasible because the standard deviation of horizontal and vertical derivatives has a negative correlation relationship at the boundary position. Tests on theoretical models show that this method can identify the locations of the sources with different depths, and is less susceptible to noise with better stability calculation. The proposed method is applied to aeromagnetic data of the Hailaer Basin, and test results show a good correspondence to the real data.