A new technique based on the eigenvalue of the curvature tensor for enhancing gravity data

Abstract

Enhancement of the boundaries of geologic structures is one of the main goals in interpretation of gravity anomalies. A range of different algorithms based on field derivatives has been introduced to solve this problem. Among these algorithms, the curvature gravity gradient tensor and its modifications are widely used in enhancing gravity data. These algorithms, however, have some main limitations such as the estimated edges are not compatible with the actual edges or bringing false information. In this study, I introduce a new technique based on the eigenvalue of the curvature tensor. The robustness of the presented technique is exemplified using model studies and a real-world dataset of the Vredefort dome (South Africa). The model studies show that the proposed filter can provide more accurate results and avoid artifacts in the output map. The real application result shows a good correlation between the edges highlighted by the presented algorithm and ring structures in the dome.