4.7 Article

High-Order Directional Total Variation for Seismic Noise Attenuation

Journal

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TGRS.2021.3073737

Keywords

Noise reduction; HDTV; Attenuation; Noise measurement; Image reconstruction; Geology; Linear programming; High-order directional total variation; noise attenuation; seismic data; structural direction; total variation (TV)

Funding

  1. National Natural Science Foundation of China [41674135, 41774129, 41874123, 41904116]
  2. Natural Science Basic Research Program of Shaanxi Province [2021JQ-561]

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A high-order directional total variation (HDTV) method for seismic denoising is developed, considering the local structural direction and higher order derivatives to avoid the staircasing effect. Comparative tests with synthetic models and field seismic data sets demonstrate better denoising performance of the proposed method compared to first-order DTV and conventional high-order TV methods.
High-amplitude noise could interfere with useful seismic signals, affecting our ability in processing and interpreting seismic data. Thus, attenuating seismic noise is an important task in seismic processing. Total variation (TV) has played an important role in many steps of seismic data processing but always neglected the seismic structural information. Directional TV (DTV), however, considers the structural direction of seismic events but tends to cause the staircasing effect on seismic records based on the first-order formulation. Here, we develop a high-order DTV (HDTV) method for seismic denoising. It considers the local structural direction of the seismic data and calculates the higher order derivatives of seismic images to avoid the staircasing effect. We design several synthetic models that are contaminated by various types of random noise to test the denoising ability. The denoising performance of our new method is compared with the first-order DTV, conventional high-order TV, and TV regularization methods from two aspects, i.e., the signal-to-noise ratio and the effective signal leakage degree. Then, the advantages of the proposed method are further validated via several field seismic data sets.

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