Wavelet-based 3-D inversion for frequency-domain airborne EM data

Wavelet-based 3-D inversion for frequency-domain airborne EM data
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基于小波的频域机载电磁数据 3D 反演

DOI:
10.1093/gji/ggx545
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发表时间:
2018-04
影响因子:
2.8
通讯作者:
Vikas C. Branwal
Vikas C. Branwal
中科院分区:
地球科学2区
文献类型:
--
作者:
Yunhe Liu;Colin G. Farquharson;Changchun Yin;Vikas C. Branwal

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在本文中,我们提出了一种新的基于小波的频域机载电磁(FDAEM)数据3D反演方法。这种新方法不是使用平滑约束在空间域中反转模型,而是基于稀疏约束在小波域中恢复模型。在小波域中,模型由两类系数表示,这两种系数同时包含模型的大尺度和细尺度信息,这意味着小波域反演具有固有的多分辨率。为了实现稀疏性约束,我们最小化小波域中的 L1 范数测量,该测量主要给出稀疏解。最终的反演系统通过迭代重新加权最小二乘法求解。我们研究不同阶的 Daubechies 小波来完成我们的反演算法,并在合成频域 AEM 数据集上对其进行测试。结果表明,具有较大消失矩和规律性的高阶小波可以提供更稳定的反演过程并提供更好的局部分辨率,而低阶小波更简单且不太平滑,因此如果模型简单,则能够恢复尖锐的不连续性。最后,我们在挪威 Byneset 采集的频域直升机电磁场 (HEM) 现场数据集上测试了这种新的反演算法。将基于小波的 HEM 数据 3 维反演与基于 L2 范数的 3 维反演结果进行比较,以进一步研究新方法的特点。
In this paper, we propose a new wavelet-based 3-D inversion method for frequency-domain airborne electromagnetic (FDAEM) data. Instead of inverting the model in the space domain using a smoothing constraint, this new method recovers the model in the wavelet domain based on a sparsity constraint. In the wavelet domain, the model is represented by two types of coefficients, which contain both large- and fine-scale informations of the model, meaning the wavelet-domain inversion has inherent multiresolution. In order to accomplish a sparsity constraint, we minimize an L1-norm measure in the wavelet domain that mostly gives a sparse solution. The final inversion system is solved by an iteratively reweighted least-squares method. We investigate different orders of Daubechies wavelets to accomplish our inversion algorithm, and test them on synthetic frequency-domain AEM data set. The results show that higher order wavelets having larger vanishing moments and regularity can deliver a more stable inversion process and give better local resolution, while the lower order wavelets are simpler and less smooth, and thus capable of recovering sharp discontinuities if the model is simple. At last, we test this new inversion algorithm on a frequency-domain helicopter EM (HEM) field data set acquired in Byneset, Norway. Wavelet-based 3-D inversion of HEM data is compared to L2-norm-based 3-D inversion's result to further investigate the features of the new method.
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