Capability of improved Logistics filter in determining lateral boundaries and edges of gravity and magnetic anomalies Tuzgolu Area Turkey

The most critical problem of using edge detection filters is determining the horizontal boundaries of gravity and magnetic anomalies with different depths and integrating the effect of adjacent anomalies, which are diffused in geophysical maps. In recent years, edge enhancement filters having different performances have been provided to solve this problem. Edge detection filters are usually a combination of horizontal and vertical gradients with different orders to determine the boundaries and edges of gravity and magnetic anomalies data with different quality and accuracy. In this study, the efficiency of filters to determine the edge of potential field anomalies, including total horizontal derivative (THD), analytical signal (AS), tilt angle (TA), theta map (TM), the hyperbolic tangent of tilt angle (HTA), normalized total horizontal derivative (TDX), sun shading (SS), generalized derivative operator (GDO), and the improved logistics function (IL) are tested on potential field data. The efficacy of edge detection filters was evaluated using two synthetic gravity and magnetic models with and without Gaussian noise. The results reveal that the improved logistic filter outperforms existing edge detection filters in terms of accuracy and quality in determining the edges and boundaries of synthetic anomalies. This filter also prevents drawing erroneous or spurious boundaries, which complicates interpretation. Subsequently, applying an improved logistic filter on the real data of the Tuzgolu (Salt Lake) region of Turkey shows that this filter can detect the boundaries and edges of anomalies, even deep anomalies within the study area. In general, the data acquired using edge determination filters and a much improved logistic filter can be employed in qualitative interpretation for 3D modeling of subsurface structures and detecting faults and fractures.