论文标题

从海洋CSEM数据计算出的2D反转模型的空间变化迭代恢复

Space-Varying Iterative Restoration of 2-D Inversion Models Computed from Marine CSEM Data

论文作者

Li, Feng-Ping, Thorkildsen, Vemund Stenbekk, Gelius, Leiv-J, Yue, Jian-Hua

论文摘要

海洋控制的电磁源(CSEM)均用于大规模的地球物理应用以及碳氢化合物和气体水合物的探索中。由于EM场的扩散特征,仅使用了非常低的频率,从而导致分辨率相当低的反转结果。在本文中,我们计算与反转相关的分辨率矩阵,并得出相应的点扩散函数(PSFS)。 PSF提供了有关实际反转的数量模糊的信息,因此,使用空间变化的卷积可以进一步改善反转结果。实际的去缩合是通过使用非负柔性共轭梯度算法来进行最小二乘问题(NN-FCGL)进行的,这是一种快速的迭代恢复技术。为了完整性,我们还介绍了通过使用未知PSF的最大似然估计(MLE)的最大似然估计(MLE)来获得的结果。使用复杂的合成数据以及在Barents Sea的Wisting Oil Field获得的现场数据也证明了所提出的方法的潜力。在这两种情况下,最终反转结果的分辨率都得到了改善,并且与已知的目标区域显示出更好的一致性。

Marine Controlled Source Electromagnetic (CSEM) is employed both in large-scale geophysical applications as well as within exploration of hydrocarbons and gas hydrates. Due to the diffusive character of the EM field only very low frequencies are used leading to inversion results with rather low resolution. In this paper, we calculate the resolution matrix associated with the inversion and derive the corresponding point spread functions (PSFs). The PSFs give information about how much the actual inversion has been blurred, and use of space-varying deconvolution can therefore further improve the inversion result. The actual deblurring is carried out by use of the nonnegative flexible conjugate gradient algorithm for least squares problem (NN-FCGLS), which is a fast iterative restoration technique. For completeness, we also introduce results obtained by use of a blind deconvolution algorithm based on maximum likelihood estimation (MLE) with unknown PSFs. The potential of the proposed approaches have been demonstrated using both complex synthetic data as well as field data acquired at the Wisting oil field in the Barents Sea. In both cases, the resolution of the final inversion result has improved and shows better agreement with the known target area.

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