基于重加权反演评价重力梯度异常各分量（英文）

Evaluating gravity gradient components based on a reweighted inversion method

重力梯度反演中,了解重力梯度各分量在反演中发挥的作用,从而选择合适的分量组合非常重要。基于前人对重力梯度各分量的信息特征的研究,本文提出了一种重加权反演方法来评价单一重力梯度分量对反演结果分辨率的影响。这种方法仅用到了正则化方程中的拟合函数,并引入深度加权函数克服重力梯度反演中的"趋肤效应"。本文对比了不同的反演结果,验证了深度加权函数对反演结果的影响。基于避免引入先验信息这一前提,文中选择灵敏度矩阵构建的深度加权函数。基于单一长方体模型和复杂模型试验的反演结果表明不同分量对反演结果分辨率的影响在不同方向存在差异。此外,在两种模型数据中加入不同水平的随机噪声,得出结果与无噪声模型反演结果基本一致。最后,本文方法在美国路易斯安娜州文顿盐丘的实际数据得到了应用。

In gravity gradient inversion,to choose an appropriate component combination is very important,that needs to understand the function of each component of gravity gradient in the inversion.In this paper,based on the previous research on the characteristics of gravity gradient components,we propose a reweighted inversion method to evaluate the influence of single gravity gradient component on the inversion resolution The proposed method only adopts the misfit function of the regularized equation and introduce a depth weighting function to overcome skin effect produced in gravity gradient inversion.A comparison between different inversion results was undertaken to verify the influence of the depth weighting function on the inversion result resolution.To avoid the premise of introducing prior information,we select the depth weighting function based on the sensitivity matrix.The inversion results using the single-prism model and the complex model show that the influence of different components on the resolution of inversion results is different in different directions,however,the inversion results based on two kind of models with adding different levels of random noise are basically consistent with the results of inversion without noises.Finally,the method was applied to real data from the Vinton salt dome,Louisiana,USA.