Balanced edge detection based on eigenvalues of full magnetic gradient tensor
ZHENG Qiang1, GUO Hua2, ZHANG Guibin1, HAN Song2, WANG Ming2, LIU Haojun2
1. School of Geophysics and Information Technology, China University of Geosciences(Beijing), Beijing 100083, China; 2. Airborne Geophysical Prospecting and Remote Sensing Center, Ministry of Natural Resources, Beijing 100083, China
Abstract：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.
郑强, 郭华, 张贵宾, 韩松, 王明, 刘浩军. 基于磁力梯度全张量特征值的均衡边界识别方法[J]. 石油地球物理勘探, 2020, 55(2): 454-464.
ZHENG Qiang, GUO Hua, ZHANG Guibin, HAN Song, WANG Ming, LIU Haojun. Balanced edge detection based on eigenvalues of full magnetic gradient tensor. Oil Geophysical Prospecting, 2020, 55(2): 454-464.
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