3D Euler deconvolution of irregularly spaced magnetic data on an uneven topographic surface

Abstract

Euler deconvolution has been widely utilized to recover geometry of magnetic bodies in mineral exploration and interpretation of geological structure. However, most of Euler deconvolution techniques require rectangular grid of magnetic data given on a planar surface. We propose a new Euler deconvolution scheme of irregularly spaced magnetic data on an uneven topographic surface. The scheme first inverts the given irregular magnetic data to obtain the subsurface equivalent sources, from which horizontal and vertical derivatives are calculated directly on the given data points. Then, we minimize the so-called homogeneity scaling function to simultaneously estimate the structural index (SI) and the window radius. The depth and position of a magnetic body are calculated based on the estimated structural index and the window radius. We validated the proposed method via synthetic and field datasets. The method gives the correct structural index and location even under moderate Gaussian noise, which demonstrated its accuracy and noise resistance.