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3-D Data Interpolation and Denoising by an Adaptive Weighting Rank-Reduction Method Using Multichannel Singular

Farzaneh Bayati1, Daniel Trad1

  • 1Department of Earth Science, University of Calgary, 2500 University Drive NW, Calgary, AB T2N 1N4, Canada.

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Summary

This study introduces an adaptive weighted rank reduction (AWRR) method to improve seismic data processing. AWRR automatically selects optimal ranks, enhancing denoising and interpolation for complex seismic events.

Keywords:
MSSASVDinterpolationrank reductionseismic data

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Area of Science:

  • Geophysics
  • Seismic Data Processing
  • Signal Processing

Background:

  • Insufficient and irregular sampling pose significant challenges in seismic processing and imaging.
  • Rank reduction methods, utilizing truncated singular value decomposition (TSVD), are employed for simultaneous denoising and interpolation.
  • Traditional rank reduction can fail with complex data due to fixed rank estimation.

Purpose of the Study:

  • To propose an adaptive weighted rank reduction (AWRR) method for automated optimal rank selection in seismic data processing.
  • To address limitations of existing methods in handling complex seismic events and residual errors.
  • To enhance the accuracy of seismic denoising and interpolation.

Main Methods:

  • Developed an adaptive weighted rank reduction (AWRR) technique.
  • Implemented automatic optimum rank selection within processing windows based on singular value energy ratios.
  • Introduced a weighting operator to mitigate residual errors by minimizing noise projection effects.

Main Results:

  • The AWRR method demonstrated effectiveness in selecting optimal ranks for seismic trajectory matrices.
  • Successfully reduced residual errors associated with processing highly curved complex events.
  • Showcased improved performance on both synthetic and real seismic datasets.

Conclusions:

  • The proposed AWRR method offers an automated and robust solution for seismic data denoising and interpolation.
  • AWRR effectively handles complex seismic events, overcoming limitations of conventional rank reduction techniques.
  • The method shows significant potential for improving seismic imaging and interpretation accuracy.