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Seismic image enhancement by double-weighted stacking
PAN DENG1,2 ,
QIUMING CIENG3 ,
XIUFA CIEN4 ,
JIANPING CIEN5 ,
FANGYU LI6 ,
LEI GUAN7
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1
International Mining Research Center, China Geological Survey, Beijing 100037, P.R. China. dpan@mail.cgs.gov.cn,
2
China Mining News, China Geological Survey, Beijing 100037, P.R. China.,
3
China University of Geosciences (Beijing), Beijing 100083, P.R. China.,
4
Development Research Center, China Geological Survey, Beijing 100037, P.R. China.,
5
Wuhan University, Wuhan 430079, P.R. China.,
6
Kennesaw State University, Marietta, GA 30060, U.S.A.,
7
CNODC, China National Petroleum Corporation (CNPC), Beijing 100034, P.R. China.,
JSE 2021, 30(1), 1–20;
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
Deng, P., Cheng, Q., Chen, X., Chen, J.P., Zhang, Y., Li, F.-Y. and Guan, L., 2021. Seismic image enhancement by double-weighted stacking. Journal of Seismic Exploration, 30: 1-20. Normal-moveout velocity analysis using semblance spectrum and common-midpoint stacking after normal-moveout correction are two indispensable procedures in seismic reflection data processing, especially for random noise attenuation, velocity model estimation, and imaging quality enhancement. During this process, weighting functions have been frequently used to improve the resolution of semblance and the performance of stacking. In this paper, the interactive relationship between semblance and _ stacking allows a new method of double-weighted stacking to be created. This method applies the same local-similarity-weighting function to the calculation of both semblance and stacking, aiming to enhance the final stacked image sections. The synthetic and field data numerical experiments have demonstrated that our new approach enhances the signal-to-noise ratio and the reflection-event continuity compared with conventional processing flows.
Keywords
semblance spectrum
normal-moveout correction
double-weighted stacking
local similarity
random noise attenuation
image quality enhancement.
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