Random and coherent noise attenuation by empirical mode decomposition
Random and coherent noise attenuation by empirical mode decomposition
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DOI：
10.1190/1.3063881
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发表时间：
2009-08
期刊：
影响因子：
--
通讯作者：
M. Bekara;M. Baan
中科院分区：
文献类型：
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作者：
M. Bekara;M. Baan
我们设计了一种新的滤波技术，用于衰减地震数据中的随机噪声和相干噪声，在频偏f-x域中应用了恒频域上的模式分解EM，并去除了第一固有模式函数，其动机是克服f-x反褶积在处理高度复杂的地质剖面、使用不规则道间距采集的数据和/或受陡倾相干噪声污染的数据时用于信噪比增强的潜在性能。由此产生的f-x EMD方法等效于具有频率依赖的高波数截止滤波特性的自适应f-k滤波器。在叠前或叠加/偏移剖面中去除随机和陡倾相干噪声是有效的，并且与其他降噪方法，如f-x反褶积，中值滤波和局部奇异值合成相比也很好。
We have devised a newfiltering technique for random and coherentnoiseattenuationinseismicdatabyapplyingempiricalmodedecompositionEMDonconstant-frequencyslicesinthefrequency-offsetf-xdomainandremovingthefirst intrinsicmodefunction.Themotivationbehindthisdevelopmentistoovercomethepotentiallowperformanceof f-x deconvolution for signal-to-noise enhancement when processinghighlycomplexgeologicsections,dataacquiredusingirregular trace spacing, and/or data contaminated with steeply dipping coherent noise. The resulting f-x EMD method is equivalent to an autoadaptive f-k filter with a frequency-dependent, high-wavenumber cut filtering property. Removing both random and steeply dipping coherent noise in either prestackorstacked/migratedsectionsisusefulandcompares well with other noise-reduction methods, such as f-x deconvolution,medianfiltering,andlocalsingularvaluedecomposition.Initssimplestimplementation, f-xEMDisparameterfree and can be applied to entire data sets without user interaction.