基于磁力梯度全张量特征值的均衡边界识别方法

Balanced edge detection based on eigenvalues of full magnetic gradient tensor

目前广泛采用的重磁梯度全张量数据具有高精度、高分辨率、多参量的优点,成为近年来位场数据处理与解释的研究热点。基于磁力梯度全张量的最大特征值,提出一种新的均衡边界识别方法,可有效提高边界识别的精度和稳定性。模型试验验证了新方法不仅能够同时识别深、浅模型体的边界,而且具有较高的识别精度、一定的抗倾斜磁化能力以及较强的稳定性。最后,将其应用于中国北部某地区由实测航磁三分量数据转换的梯度全张量数据,获得了较清晰的边界信息,验证了方法的实用性。

Full gravimetric-magnetic gradient tensor data,which feature high precision,high resolution,and multi-parameter,is a focus in potential field data processing and interpretation.For accurate and robust edge detection,we present a balanced edge detection method based on the maximum eigenvalue of full magnetic gradient tensor.Model tests show that the boundaries of the deep and shallow models could be identified simultaneously with high precision and robustness;It also has some resistance to oblique magnetization.To test its feasibility,we apply this method to field data acquired in a prospect in north China and obtain the clear image of structure boundaries.