Curvelet-based migration amplitude recovery
Curvelet-based migration amplitude recovery
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DOI：
10.14288/1.0052987
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发表时间：
2010
期刊：
影响因子：
--
通讯作者：
P. Moghaddam
中科院分区：
文献类型：
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作者：
P. Moghaddam
偏移能够准确地定位地球中的反射层，但在大多数情况下无法正确解析其振幅。这可能会导致对反射层性质的错误解读。在本论文中，我介绍了一种精确恢复地震反射层振幅的方法。这种方法依赖于一种基于新变换的恢复方法，该方法利用了最近发展的曲波变换对地震图像的表达式。这种变换的元素，称为曲波，是多维、多尺度和多方向的。它们在成像算子下也大致保持不变。我利用曲波的这些特性，引入了一种称为曲波匹配滤波（CMF）的方法，用于在偏移图像和数据都存在噪声的情况下恢复地震振幅。我详细介绍了该方法，并在合成数据集上说明了其性能。我还将CMF公式扩展到其他地球物理应用中，并展示了在多次波去除方面的结果。除此之外，我还研究了偏移的预处理，这使得使用偏移的迭代方法具有快速收敛速度。
Migration can accurately locate reflectors in the earth but in most cases fails to correctly resolve their amplitude. This might lead to mis-interpretation of the nature of reflector. In this thesis, I introduced a method to accurately recover the amplitude of the seismic reflector. This method relies on a new transform-based recovery that exploits the expression of seismic images by the recently developed curvelet transform. The elements of this transform, called curvelets, are multi-dimensional, multi-scale, and multi-directional. They also remain approximately invariant under the imaging operator. I exploit these properties of the curvelets to introduce a method called Curvelet Match Filtering (CMF) for recovering the seismic amplitude in presence of noise in both migrated image and data. I detail the method and illustrate its performance on synthetic dataset. I also extend CMF formulation to other geophysical applications and present results on multiple removal. In addition of that, I investigate preconditioning of the migration which results to rapid convergence rate of the iterative method using migration.