二维重力数据径向反演及应用

2Dgravity data radial inversion

相对于直角坐标系下的反演方法,径向反演方法具有模型参数减少一半且反演参数具有同一量纲的特点,而Tikhonov正则化方法能方便地应用多种约束条件和引入场源先验信息。该方法对于近圆形、梨形或在某方向呈瘦长形的独立场源的反演效果较好。本文将正则化因子自适应选取引入径向反演方法中,提高了反演效率和数据拟合程度。自适应正则化径向反演方法在模型数据试算和实际重力数据处理中均取得了较好的效果。

Comparing with the inversion method in the Cartesian coordinate system,the radial inversion method uses half of model parameters,and inversion parameters have the same dimension.The Tikhonov regularization method can easily apply a variety of constraints and prior information.This method obtains stable solutions of independent field inversion for near-circular shaped,pear-shaped,elongated in one or more directions.In this paper,the regularization factor adaptive selection is introduced into the radial inversion,which improves the inversion efficiency and the data fitting.The adaptive regularized radial inversion method has achieved good results in both model and real gravity data processing.