自适应网格直流电阻率三维反演

3D DC resistivity inversion based on inversion-oriented adaptive meshes

采用基于模型灵敏度信息的非结构化自适应网格算法生成面向反演需求的高质量网格,并进一步开展直流电阻率三维反演研究。模型灵敏度作为地下模型改变量对观测数据集总体响应的度量,以其为依据进行网格优化,可生成高质量网格,以降低反演对模型正则化约束的依赖性,提高反演效果。反演采用四面体单元构造基于最小结构的正则化反演目标函数,通过高斯-牛顿法优化求解,采用稳定双共轭梯度法求解高斯-牛顿方程,实现了三维直流电阻率法的稳定反演。最后,理论与实测数据反演证明了本文方法的有效性。

We use the unstructured adaptive grid algorithm based on model sensitivity information to generate high-quality inversion-oriented meshes,and adopt them to 3 D DC resistivity inversion.The model sensitivity is a measure of the overall response of underground model change to real datasets.So,the optimized mesh generated based on the model sensitivity information has higher quality than the ordinary mesh.This new mesh can reduce the dependence of inversion on model regularization constraints and improve the quality of inversion results.We use the minimum-structure inversion object function based on a tetrahedral element mesh.The Gauss-Newton method optimizes the inversion object function.The GaussNewton equation is solved by the stable double conjugate gradient method in order to increase the stability of 3 D DC resistivity inversion.The calculating results of both synthetic and field data prove the validity of the proposed approach.