Edge detection is one of the most commonly used interpretation techniques applied to potential data for detecting subsurface susceptibility/density discontinuities. Several edge detection techniques utilize the first, second, or even third-order gradients of the magnetic field to delineate the susceptibility contrasting zones. A new filter called Balanced Horizontal Gradient (BHG) filter is designed for enhancing the edges of the subsurface bodies that overcomes the limitations of the conventional filters. The BHG filter is based on the arctangent function of derivatives of horizontal gradients. The main advantage of the proposed filter is that it seems to detect all the source edges with no false edges generated around the true edges and effectively balances the edges arising from the shallow and deep-seated sources. We applied the filter on the aeromagnetic data from central India and identified the extensions of the Godavari rift and central Indian shear underneath the Deccan volcanic province.

Edge detection techniques identify the horizontal extents of the underground geological bodies and work well in association with magnetic as well as seismic data. Even though the detected edges might not be a lithological contact, they offer first-hand information regarding various rocks that ultimately offers an extra argument for existing tectonics. Most of the edge enhancement techniques depend either on the horizontal gradient or total gradient of the potential fields. As of now, no single edge detection filter performance is best in all conditions. The study proposes a novel edge detection filter called “ETG-Enhanced Total Gradient” that combines the derivatives of the analytic signal (AS) (in the third dimension). The maximum amplitude of the AS is less dependent of the direction of magnetization and is critical in mapping the borders of the buried magnetic sources beneath the Earth. As the ETG filter is based on the total gradient of the field, there is no need to apply reduction to the pole process on the magnetic data. One limitation of the method is that the filter is unable to perform better at the corners where the other conventional methods miserably failed. The filter’s behavior is examined and validated using 2D and 3D synthetic magnetic data. The reliability of the ETG filter is examined by applying it to the magnetic data of the Seattle uplift region, USA. A new structural map of the region is generated by using the proposed ETG filter. The observed peak response of the ETG filter is well correlated with major tectonic features such as the Seattle Fault Zone (SFZ), Hood Canal Fault (HCF), and Dewatto Fault (DF).