Edge detection of geological structures based on a logistic function: a case study for gravity data of the Western Carpathians

Abstract

Magnetic and gravity anomalies have spatially overlapping fingerprints from many buried sources that differ in shape, depth, density contrast, magnetization intensity, and direction. Geophysicists have developed a suite of image enhancement filter algorithms that accurately represent the geometry and detail of subsurface features. Edge enhancement filters are high-pass filters that emphasize potential field anomalies, horizontal lateral edges, and the horizontal location of buried sources, i.e., specific combinations of directional derivatives of gravity and magnetic fields. Lateral edge enhancement filters (e.g., THG, AS, TA, TM, LTHG, IL, and ILTHG) were investigated using Gaussian noise on synthetic magnetic and gravity field data. The results show that LTHG and IL perform better than the other procedures. The ILTHG filter defined with the logistic function does not have the required accuracy and capability to determine the lateral boundaries. In addition, the filters were examined using real gravity field data from the Western Carpathians area in Slovakia. The primary and secondary faults in the western and southern Tribeč Mountains and the secondary faults and geological formations in the Pohronský Inovec Mountains are recognizable in the LTHG and IL images. The results of the LTHG and IL maps will allow us to improve the qualitative interpretation of gravity anomalies in studying the structural and tectonic geology of the Slovak Tribeč and Pohronský Inovec Mountains.

Keywords

• edge enhancement filter
• gravity data
• logistic function
• slovakia territory