Depositional sequence characterization based on seismic variational mode decomposition
Depositional sequence characterization based on seismic variational mode decomposition
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DOI：
10.1190/int-2016-0069.1
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发表时间：
2017-04
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影响因子：
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通讯作者：
Fangyu Li;Bo Zhang;R. Zhai;Huai-lai Zhou;K. Marfurt
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文献类型：
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作者：
Fangyu Li;Bo Zhang;R. Zhai;Huai-lai Zhou;K. Marfurt
摘要在其他相似的地震数据中，主题变化可以在特定的频谱分量中突出显示。我们的目标是突出重复层序界面，以帮助确定沉积环境，这反过来又提供了一个解释框架。变分模式分解(VMD)是一种新的数据驱动的信号分解方法，与常用的时频分析方法相比，它具有许多有用的特征。VMD方法不是使用预定义的频段，而是自适应地将信号分解成频带受限的固有模式函数集合，每个函数都有自己的中心频率。因为它是数据自适应的，所以模式可以在相邻的轨迹之间快速变化。我们通过构造一个横向一致的VMD方法来解决以前工作的这个缺点，该方法保持了横向的连续性，便于提取细微的沉积模式。通过一个合成沉积旋回实例验证了该方法的准确性，并将其应用于识别沉积旋回。
AbstractSubtle variations in otherwise similar seismic data can be highlighted in specific spectral components. Our goal is to highlight repetitive sequence boundaries to help define the depositional environment, which in turn provides an interpretation framework. Variational mode decomposition (VMD) is a novel data-driven signal decomposition method that provides several useful features compared with the commonly used time-frequency analysis. Rather than using predefined spectral bands, the VMD method adaptively decomposes a signal into an ensemble of band-limited intrinsic mode functions, each with its own center frequency. Because it is data adaptive, modes can vary rapidly between neighboring traces. We address this shortcoming of previous work by constructing a laterally consistent VMD method that preserves lateral continuity, facilitating the extraction of subtle depositional patterns. We validate the accuracy of our method using a synthetic depositional cycle example, and then we apply it to identi...