Seismic denoising using thresholded adaptive signal decomposition

Abstract

Noise reduction is critical for structural, stratigraphic, lithological and quantitative interpretation. In the absence of physical insight into its cause and behavior, separating the noise from the underlying signal can be difficult. We construct a noise suppression workflow based on a data-adaptive signal decomposition method (variational mode decomposition). Key to our workflow is to determine which of the generated intrinsic mode functions represent signal and which represent noise. We address this issue by a scaling exponent based on detrended fluctuation analysis. The proposed method shows excellent performance on synthetic and field data, especially when encountering data exhibiting a low signal-to-noise ratio. Laterally continuous events are preserved and steeply dipping coherent events due to aliasing as well as random noise are rejected. Presentation Date: Wednesday, September 27, 2017 Start Time: 3:05 PM Location: Exhibit Hall C/D Presentation Type: POSTER