Global Optimization for Delineation of Self-potential Anomaly of a 2D Inclined Plate

Abstract

A fast and efficient technique for explanation of self-potential anomalies is of immense importance for exploration, engineering, and environmental problems. Estimation of model parameters of ore bodies in the subsurface is the primary concern in mineral exploration. In most cases, self-potential data are delineated considering various simple or idealized structures for the interpretation of lateral and vertical variations of subsurface ore bodies. In this context, we developed an inversion algorithm to determine the different parameters associated with a 2D inclined plate-type structure, which does not require any a priori information. The developed algorithm can interpret appropriately every parameter with minimum uncertainty. The position of causative source body (x0), its half-width (w) and its depth (z) were the parameters interpreted using the developed algorithm. It was found that these parameters were well resolved within the estimated uncertainty, although solutions for w showed wide variability. The technique was verified with synthetic data without noise and with different degrees of Gaussian noise. The technique was also confirmed with three field datasets for mineral exploration, and the interpreted parameters were in fair agreement with those reported in earlier works.