This study applies a Tikhonov regularization framework to aeromagnetic data from parts of northeastern Nigeria to enhance the resolution of magnetic anomalies and suppress geological and cultural noise. The dataset, covering twelve geological map sheets acquired by Fugro Airborne Surveys (2004–2009), was processed using a range of derivative-based edge-detection filters, including the Horizontal Gradient (HG), Analytic Signal (AS) amplitude, Tilt, Horizontal Gradient of Tilt (HGTilt), Theta, Normalized HG (TDX), TDXAS, Tilt Angle of the Total Horizontal Gradient (TAHG), Enhanced Tilt (ETilt), Enhanced Total Horizontal Derivative of the Tilt Angle (ETHDR), and Modified Horizontal Gradient Amplitude (MHGA). The MHGA method was further optimized by varying a constant offset (often a fraction or multiplication of π in its computation to evaluate its sensitivity and performance. Results show that regularized derivatives effectively minimize noise amplification while preserving structural integrity, with a revisited algorithm (published by Karcol and Pašteka in year 2025) providing the most stable differentiation. The ETHDR and MHGA (−π/3) filters delineated low-magnetic anomaly zones associated with the Bima, Yolde, Pindiga, Gombe, and Kerri-Kerri Formations, indicating promising geothermal potential. High-gradient zones correspond to granitic intrusions and fault intersections that may act as heat sources and hydrothermal conduits. These results demonstrate that integrating regularized derivatives with advanced edge-detection filters significantly enhances geothermal prospectivity mapping in complex crustal settings.
Usman et al. (2025) studied this question.