A novel fusion Python application of data mining techniques to evaluate airborne magnetic datasets

Depths to the various subsurface anomalies have been the primary interest in all the applications of magnetic methods of geophysical prospection. Depths to the subsurface geologic features of interest are more valuable and superior to all other properties in any correct subsurface geologic structural interpretations. The varied nature of the subsurface geological terrains in the study area as obtained from the data, were delineated from the enhanced georeferenced airborne magnetic datasets with the primary objective of enhancing the signatures of the subsurface structural and lithologic boundaries associated with joints; major and minor faults, rock contacts and fractures underained the Omu-aran schist belt zone. About 343,982 enhanced georeferenced data points, made up of 100 m interspacing between the data points utilising the 3x3 window size were used to suitably map the region across the land area of about 30,568.7 km2. Six structural index values varied from between 0.5-3.0 were delineated with a maximum depth to the magnetic source rocks bodies at about 1.277 km.