A new method of balanced edge detection based on curvature for gravity data

Abstract The edge detection method can be used to delineate the position of the structural boundary of the geological body, and it occupies an important position in the processing of gravity data. The shortcomings of traditional edge detection methods are that the output boundary is divergent, the S...
Ausführliche Beschreibung

Abstract The edge detection method can be used to delineate the position of the structural boundary of the geological body, and it occupies an important position in the processing of gravity data. The shortcomings of traditional edge detection methods are that the output boundary is divergent, the Strength and weak anomalies cannot be balanced, or false boundaries appear in the recognition results. There is a close connection between gravity anomaly and its curvatures and subsurface geological formations. Thus they can be used to describe the geometry of subsurface formations. In this paper, a new method of balanced edge detection based on curvature is proposed by combining the fusion formula of average curvature, vertical curvature, and the degree of curvature. Model tests show that the method proposed in this paper has obvious advantages compared with the recognition effects of several traditional curvature and equalization filtering methods. The edge detection results of the proposed method have good convergence. When both positive and negative anomalies exist, this method is less affected and has anti-noise capabilities. Applying the method to real field data, the results show that the identified geological body structural boundaries are clearer and more accurate, and can be applied to more complex geological environments. Ausführliche Beschreibung