位场异常分离的递减半径迭代法

Decreasing radius iterative method for regional-residual separation of potential field data

本文提出了位场区域-剩余异常分离的空间域递减半径迭代法.由给定半径的圆周上八点位场值的算术平均导出一个新的八点圆周平均公式,它是一个由重磁数据计算区域异常的滤波器.该滤波器的传递函数有一主瓣和多个旁瓣,且半径越大,旁瓣越多,滤波器特性越差.由从大到小不同半径对应的传递函数的连乘积构造了递减半径迭代传递函数,它以大半径为参变量.递减半径迭代传递函数类似低通滤波器,其截止波数与大半径成反比.由递减半径迭代传递函数,给出空间域分离区域异常的递减半径线性迭代法,由重磁数据减去区域异常求得剩余异常.进一步,通过构造非线性修正系数,把空间域递减半径线性迭代法中线性迭代公式变成非线性迭代公式,得到空间域递减半径非线性迭代法.重磁理论模型及安徽泥河铁矿重磁资料的试验表明,空间域递减半径非线性迭代法可有效地压制假异常和高频干扰以及减少异常畸变,并能有效地分离出区域异常和剩余异常.

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 cutoff wavenumber 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 on 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.