2015
DOI: 10.1016/j.jappgeo.2015.03.026
|View full text |Cite
|
Sign up to set email alerts
|

Improving depth imaging of legacy seismic data using curvelet-based gather conditioning: A case study from Central Poland

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
8
0

Year Published

2016
2016
2023
2023

Publication Types

Select...
5
1
1

Relationship

0
7

Authors

Journals

citations
Cited by 9 publications
(8 citation statements)
references
References 12 publications
0
8
0
Order By: Relevance
“…This processing step was performed with a MATLAB toolbox developed by Górszczyk et al . 48 for the purpose of legacy seismic data processing and employing Discrete Curvelet Transform implementation of Candes et al . 49 Finally, a finite-difference migration algorithm, which is based on an implicit 45° migration in the time domain developed by Claerbout 50 , was used for post-stack time migration using GLOBE Claritas TM .…”
Section: Methodsmentioning
confidence: 99%
“…This processing step was performed with a MATLAB toolbox developed by Górszczyk et al . 48 for the purpose of legacy seismic data processing and employing Discrete Curvelet Transform implementation of Candes et al . 49 Finally, a finite-difference migration algorithm, which is based on an implicit 45° migration in the time domain developed by Claerbout 50 , was used for post-stack time migration using GLOBE Claritas TM .…”
Section: Methodsmentioning
confidence: 99%
“…Before interpretation, we filter out (using curvelet transform; Górszczyk et al, 2015) some of the strong migration smiles apparent in the final PSDM sections, which after analysis in the pre-stack domain have been addressed as residual multiples or out-of-plane arrivals. To foster the joint interpretation of the PSDM results and FWI velocity models, we overlay the migrated section on the (i) FWI model, (ii) velocity gradient image, i.e., the average of the horizontal and vertical derivative of the FWI velocity model (Fig.…”
Section: Geological Consistencymentioning
confidence: 99%
“…The stacked section is obtained by CMP stacking, and steps (5) to ( 7) are conducted iteratively to obtain a stack section with high quality; 8. Finally, the F-X domain filtering and curvelet denoising (Górszczyk et al, 2015) are applied to the stacked profile to enhance the SNR.…”
Section: 1029/2022jb025748mentioning
confidence: 99%
“…After extensively performing experimental tests with various processing parameters, our optimum processing workflow is summarized as follows: The geometry correction is first applied to compensate for the wavefield spreading; The bandpass filtering is then performed to suppress noise at lower and higher frequencies, where the corner frequencies are set accordingly as follow: 8‐12‐40‐45 Hz in 0–2 s, 6‐10‐30‐35 Hz in 2–4 s, and 4‐6‐20‐25 Hz in 4–30 s, respectively; The F‐K domain filtering is conducted to eliminate the surface waves and airwaves; The elevation and refraction static corrections are then applied to correct for influences from the minor surface topography as well as the near surface low‐velocity zones (LVZ); The NMO correction is subsequently performed based on the velocity analysis; The residual static correction is also performed to improve the continuity of the reflection events; The stacked section is obtained by CMP stacking, and steps (5) to (7) are conducted iteratively to obtain a stack section with high quality; Finally, the F‐X domain filtering and curvelet denoising (Górszczyk et al., 2015) are applied to the stacked profile to enhance the SNR. …”
Section: Deep Seismic Profilingmentioning
confidence: 99%