Enhancement of the total horizontal gradient of potential field data using the Modified Gudermannian Function (MGTHG): application to aeromagnetic data from Georgia, USA

One of the primary goals in interpreting potential field data is to delineate the horizontal boundaries of subsurface geological structures. Edge detection in this context involves using various filters designed to identify edges through the directional gradients of the potential field. However, traditional filters often face challenges such as low resolution, false edge generation, and dependence on depth information. This study introduces an innovative filter that combines the total horizontal gradient with the modified Gudermannian function to enhance the accuracy and clarity in horizontal boundary detection. The effectiveness of this new filter is validated through the analysis of both synthetic data sets and a real case study from Georgia, USA. To reduce noise in both synthetic and real models, vertical gradients are calculated using the stable and effective α-vertical gradient ratio technique. The results indicate that the proposed filter successfully generates high-resolution pseudo-boundary maps and produces superior outcomes.