中南大学学报（自然科学版）2013，Vol.44Issue(2)：619-625,7.
重力梯度张量的预条件共轭梯度法反演
Inversion of gravity gradient tensor based on preconditioned conjugate gradient
摘要
Abstract
The 3d inversion based on preconditioned conjugate gradient was proposed for Tensor Gradient gravity data. Roughness matrix was added in the objective function to avoid the unstable defect of inversion problem caused by the number of inverse parameter far than observational point's. Depth weighting function was integrated into the objective function to compensate kernel function avoid diminishing rapidly with depth. The inverse tests with every single component and joint five independent measured components of Tensor Gradient gravity data of the synthesized simple model and Y-type dyke show that the joint inversion is better than the others. The inversion result of the last test with joint five independent measured components of Tensor Gradient gravity data of the synthesized Y-type dyke coincides well with the real model. The results demonstrate the effect of the new algorithm.关键词
重力梯度张量/深度加权函数/预条件共轭梯度法/反演Key words
gravity gradient tensor/ depth weighting function/ preconditioned conjugate gradient/ inversion分类
天文与地球科学引用本文复制引用
陈少华,朱自强,鲁光银,曹书锦..重力梯度张量的预条件共轭梯度法反演[J].中南大学学报（自然科学版）,2013,44(2):619-625,7.基金项目
国家自然科学基金资助项目(41174061) （41174061）
中南大学自由探索计划项目(2011QNZT011) （2011QNZT011）
