Extrapolated Tikhonov method and inversion of 3D density images of gravity data

重力数据3D密度成像中EXTR方法的各参数变化对反演结果的影响(英文)

Tikhonov regularization（TR） method has played a very important role in the gravity data and magnetic data process. In this paper, the Tikhonov regularization method with respect to the inversion of gravity data is discussed. and the extrapolated TR method（EXTR） is introduced to improve the fitting error. Furthermore, the effect of the parameters in the EXTR method on the fitting error, number of iterations, and inversion results are discussed in details. The computation results using a synthetic model with the same and different densities indicated that. compared with the TR method, the EXTR method not only achieves the a priori fitting error level set by the interpreter but also increases the fitting precision, although it increases the computation time and number of iterations. And the EXTR inversion results are more compact than the TR inversion results, which are more divergent. The range of the inversion data is closer to the default range of the model parameters, and the model features and default model density distribution agree well.

Tikhonov正则化(TR)方法在重磁数据处理中发挥了重要的作用,本文在研究如何利用Tikhonov正则化方法方法解决重力数据3D反演的同时,深入讨论了可进一步提高拟合误差的Extrapolation Tikhonov正则化方法(EXTR)的原理,并就其参数选择方法及各参数对拟合误差、迭代次数及反演结果的影响进行研究。常密度及变密度组合模型试算结果表明,与TR方法相比,EXTR方法不仅可以达到解释人员设定的先验拟合误差水平,在计算时间及迭代次数相应增加的前提下有更高的拟合精度;同时其反演结果也更加紧致,进一步改善了TR反演结果的发散性;并且其反演数据范围更贴近预设模型参数范围,模型特征与预设模型密度分布吻合较好。