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Seismic residual static correction using BEADS
ZAHRA SADEGHI,
ALIREZA GOUDARZI,
PARVANEH PAKMANESH,
SADEGH MOGHADDAM
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Department of Geophysics, Graduate University of Advanced Technology, Kerman, Iran,
JSE 2022, 31(1), 65–80;
Submitted: 9 June 2025 | Revised: 9 June 2025 | Accepted: 9 June 2025 | Published: 9 June 2025
© 2025 by the Authors. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution -Noncommercial 4.0 International License (CC-by the license) ( https://creativecommons.org/licenses/by-nc/4.0/ )
Abstract
Sadeghi, Z., Goudarzi, A., Pakmanesh, P. and Moghaddam, S., 2022. Seismic residual static correction using BEADS. Journal of Seismic Exploration, 31: 65-80. When seismic waves propagate through layers close to the surface, topography and velocity variations, as well as the thickness of this layer, change the shape of the travel-time hyperbolas. These deviations are known as static and cause misalignment and loss events in the CMP gathers, so estimating residual statics in complex areas is one of the greatest challenges in seismic data processing, and the results derived from them will affect the quality of the final reconstructed image and the results of the interpretation. In this research, at least in the category of seismic data processing, sparsity for the residual static correction is implemented for the first time. Baseline estimation and denoising using sparsity (BEADS) is based on modeling the series of seismogram peaks, as sparse with sparse derivatives, and additionally on modeling the datum as a low-pass signal. This method estimates the seismogram datum and residual static correction with sparsity and it's far assessed through evaluating with Gaussian smoothing that is a traditional method, using both synthetic and real seismic data.
Keywords
residual static correction
sparsity
datum correction
sparse derivative
penalty function
low-pass filtering
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