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首页> 外文期刊>International Journal of Geophysics >3D DC Resistivity Inversion with Topography Based on Regularized Conjugate Gradient Method
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3D DC Resistivity Inversion with Topography Based on Regularized Conjugate Gradient Method

机译:基于正则共轭梯度法的带地形的3D DC电阻率反演

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During the past decades, we observed a strong interest in 3D DC resistivity inversion and imaging with complex topography. In this paper, we implemented 3D DC resistivity inversion based on regularized conjugate gradient method with FEM. The Fréchet derivative is assembled with the electric potential in order to speed up the inversion process based on the reciprocity theorem. In this study, we also analyzed the sensitivity of the electric potential on the earth’s surface to the conductivity in each cell underground and introduced an optimized weighting function to produce new sensitivity matrix. The synthetic model study shows that this optimized weighting function is helpful to improve the resolution of deep anomaly. By incorporating topography into inversion, the artificial anomaly which is actually caused by topography can be eliminated. As a result, this algorithm potentially can be applied to process the DC resistivity data collected in mountain area. Our synthetic model study also shows that the convergence and computation speed are very stable and fast.
机译:在过去的几十年中,我们观察到了对3D DC电阻率反演和复杂地形成像的浓厚兴趣。在本文中,我们基于有限元的正则共轭梯度法实现了3D DC电阻率反演。 Fréchet导数与电势组装在一起,以基于互易定理加快反演过程。在这项研究中,我们还分析了地球表面电位对地下每个电池中电导率的敏感性,并引入了优化的加权函数以产生新的敏感性矩阵。综合模型研究表明,这种优化的加权函数有助于提高深度异常的分辨率。通过将地形纳入反演,可以消除实际上由地形引起的人为异常。结果,该算法可能可以应用于处理在山区收集的直流电阻率数据。我们的综合模型研究还表明,收敛性和计算速度非常稳定且快速。

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