Subtle 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 identify seismic sequence stratigraphy boundaries for a survey acquired in the Dutch sector, North Sea.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.