An edge recognition technique enhanced with interface inversion for potential field data

One of the pivotal tasks in energy and resources exploration is identifying geological boundaries such as petroliferous structure, ore-controlling faults, and rock mass boundaries. The edge recognition of gravity and magnetic potential data has unique advantages in the detection of geological boundaries, and has become an indispensable and important means in energy and resources exploration. We have combined interface inversion and normalized vertical derivative of the total horizontal derivative (NVDR_THDR) for potential field data to improve the effect of the potential field edge recognition method for deep small-scale geological bodies. Firstly, we invert the gravity anomaly using density interface inversion method to make the anomaly more prominent of the small-scale geological structures, then the NVDR_THDR technique is used as an edge extraction and enhancement method to deal with the density interface inversion result. The results conducted with rifted basin model and the isolated bodies model show that the proposed method has obvious advantages of edge enhancement and can balance the deep and shallow anomalies to some extent. The real gravity data test of the northern Ordos Basin also show that our method can detect the small-scale faults in the basement of the basin, which indicates that this method can be successfully used in real data processing.