Decreasing Radius Iterative Method for Regional‐residual Separation of Potential Field Data

Abstract

A decreasing radius iterative method in spatial domain is presented for regional-residual separation of potential field data. A new eight-point circumference average formula is derived by arithmetical average of potential field values at eight points along the circumference of a circle of given radius, which can be seen as a filter for calculating regional anomaly from gravity or magnetic data. The transfer function of the filter has a main lobe and multiple side lobes. When the radius becomes large, the number of the side lobes increases, and the filter characteristics become bad. The product of the transfer functions for various values of the radius from large to small is constructed, which is defined as decreasing radius iterative transfer function herein, with the largest radius as its parameter. The decreasing radius iterative transfer function is similar to the low-pass filter, and the cut-off wave number is inversely proportional to the largest radius. Based on the decreasing radius iterative transfer function, the decreasing radius linear iterative method in spatial domain is presented for separating regional anomaly, and the residual anomaly is obtained by subtracting the regional anomaly from the gravity or magnetic data. Furthermore, by constructing the nonlinear correction coefficient, the linear iterative formula of the decreasing radius linear iterative method is transformed into the nonlinear iterative formula, and the decreasing radius nonlinear iterative method in spatial domain is proposed. The decreasing radius nonlinear iterative method is tested with synthetic data from model and a field data set from the Nihe iron deposit in Anhui Province. The results show that the proposed method effectively suppresses false anomaly and high frequency interference, reduces anomaly distortion, and separates regional anomaly and residual anomaly from the gravity and magnetic data.