Czasopismo
2023
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Vol. 71, no. 5
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2125--2135
Tytuł artykułu
Autorzy
Wybrane pełne teksty z tego czasopisma
Warianty tytułu
Języki publikacji
Abstrakty
Stacking is one crucial seismic data processing technique that gives a composite record made by combining traces from different shot records. The quality of stacking dramatical affects the performance of many seismic data processing tasks. The conventional equal-weight stacking method is the average of all traces in the pre-stack CMP gather, improving the signal-to-noise ratio (SNR) but reducing resolution. Most weighted stacking algorithms aim to enhance image quality by the increased SNR; however, these algorithms do not consider the resolution. Therefore, we proposed a weighted stacking algorithm with resolution enhancement, which is regarded as having maximum bandwidth and dominant frequency. Based on the genetic algorithm (GA), we calculated the stacking weights in common midpoint (CMP), or common-reflection-point (CRP) gathers. Then, we presented a weighted stacking approach to obtain the resolution-enhancement stacked data. The proposed method can obtain the resolution-enhancement stacked data by the single-trace spectrum constraint without wavelet estimation. Applications to synthetic and field seismic datasets demonstrate that compared with the traditional stacking method, the proposed method can improve the stacking resolution better, which is beneficial for subsequent interpretation.
Czasopismo
Rocznik
Tom
Strony
2125--2135
Opis fizyczny
Bibliogr. 37 poz., rys.
Twórcy
autor
- College of Geophysics, China University of Petroleum- Beijing, Beijing, China
autor
- College of Geophysics, China University of Petroleum- Beijing, Beijing, China, 344491362@qq.com
autor
- College of Geophysics, China University of Petroleum- Beijing, Beijing, China
Bibliografia
- 1. Baykulov M, Gajewski D (2009) Pre-stack seismic data enhancement with partial common-reflection-surface (CRS) stack. Geophysics 74(3):V49–V58
- 2. Boyd S, Parikh N, Chu E (2011) Distributed optimization and statistical learning via the alternating direction method of multipliers. Found Trends Machine Learn 3(1):1–122
- 3. Buzlukov V, Landa E (2013) Imaging improvement by pre-stack signal enhancement. Geophys Prospect 61(6-Challenges of Seismic Imaging and Inversion Devoted to Goldin):1150–1158
- 4. Chai X, Wang S, Yuan S (2014) Sparse reflectivity inversion for non-stationary seismic data. Geophysics 79(3):V93–V105
- 5. Cheng Q, Chen R, Li TH (1996) Simultaneous wavelet estimation and deconvolution of reflection seismic signals. IEEE Trans Geosci Remote Sens 34(2):377–384
- 6. Chui CK (1992) An introduction to wavelets. Academic Press, Cambridge, Massachusetts
- 7. Donoho DL (2006) Compressed sensing. IEEE Trans Inf Theory 52(4):1289–1306
- 8. Elumalai K, Yadav DK, Manpura AK, Patney RK (2020) Stacking seismic data based on ramanujan sums. IEEE Geosci Remote Sens Lett 17(9):1633–1636
- 9. Finnila AB, Gomez MA, Sebenik C, Stenson C, Doll JD (1994) Quantum annealing: a new method for minimizing multidimensional functions. Chem Phys Lett 219(5–6):343–348
- 10. Fomel S (2002) Applications of plane-wave destruction filters. Geophysics 67(6):1946–1960
- 11. Geyer CJ (1992) Practical markov chain monte carlo. Statistical Science, 473–483
- 12. Harik GR, Lobo FG, Goldberg DE (1999) The compact genetic algorithm. IEEE Trans Evol Comput 3(4):287–297
- 13. Houck CR, Joines JA, Kay MG (1995) A genetic algorithm for function optimization: a Matlab implementation. NCSUIE-TR 95(09):1–10
- 14. Howard LT, Stephen CB, John FM (1979) Deconvolution with the L1 norm. Geophysics 44(1):39–52
- 15. Lee MW (1986) Spectral whitening in the frequency domain. Department of the Interior, US Geological Survey, Reston, Virginia
- 16. Li Q, Gao J (2014) Application of seismic data stacking in time-frequency domain. IEEE Geosci Remote Sens Lett 11(9):1484–1488
- 17. Liu G, Fomel S, Jin L, Chen X (2009) Stacking seismic data using local correlation. Geophysics 74(3):V43–V48
- 18. Loo GV, Saelens X, Gurp MV, Macfarlane M, Martin SJ, Vandenabeele P (2002) The role of mitochondrial factors in apoptosis: a russian roulette with more than one bullet. Cell Death Differ 9(10):1031
- 19. Margrave GF, Lamoureux MP, Henley DC (2011) Gabor deconvolution: estimating reflectivity by nonstationary deconvolution of seismic data. Geophysics 76(3):W15–W30
- 20. Maurya SP, Singh KH, Singh NP (2018) Reservoir characterization using post-stack seismic inversion techniques based on real coded genetic algorithm. J Geophys 39(2)
- 21. Nawab S, Quatieri T, Lim J (1983) Signal reconstruction from short-time fourier transform magnitude. IEEE Trans Acoust Speech Signal Process 31(4):986–998
- 22. Neelamani R, Dickens TA, Deffenbaugh M (1949) Stack-and-denoise: a new method to stack seismic datasets. SEG Tech Program Expand Abs 25(1).
- 23. Padhi A, Mallick S (2013) Accurate estimation of density from the inversion of multicomponent pre-stack seismic waveform data using a nondominated sorting genetic algorithm. Lead Edge 32(1):94–98
- 24. Peacock KL, Treitel S (1969) Predictive deconvolution: theory and practice. Geophysics 34(2):155–169
- 25. Rashed MA (2008) Smart stacking: a new CMP stacking technique for seismic data. Leading Edge 27(4):462–467
- 26. Robinson EA, Treitel S (1967) Principles of digital wiener filtering. Geophys Prospect 15(3):311–332
- 27. Sanchis C, Hanssen A (2011) Enhanced local correlation stacking method. Geophysics 76(3):V33–V45
- 28. Sattari H (2017) High-resolution seismic complex trace analysis by adaptive fast sparse S-transform. Geophysics 82(1):V51–V67
- 29. Schimmel M, Paulssen H (1997) Noise reduction and detection of weak, coherent signals through phase-weighted stacks. Geophys J Int 130(2):497–505
- 30. Schoenberger M (1996) Optimum weighted stack for multiple suppression. Geophysics 61(3):891–901
- 31. Stephen B, Lin X, Almir M (2003) Subgradient methods
- 32. Trickett S (2007) Maximum-likelihood-estimation stacking. In: SEG technical program expanded abstracts. pp 2640–2643
- 33. Van Laarhoven PJ, Aarts EH (1987) Simulated annealing: theory and applications. Springer, Netherlands
- 34. Vose MD (1999) The simple genetic algorithm: foundations and theory. MIT press, Cambridge, Mass
- 35. Wu J, Bai M (2017) Fast principal component analysis for stacking seismic data. J Geophys Eng 15(2):295
- 36. Xie J, Chen W, Zhang D, Zu S, Chen Y (2017) Application of principal component analysis in weighted stacking of seismic data. IEEE Geosci Remote Sens Lett 14(8):1213–1217
- 37. Yilmaz Ö (2001) Seismic data analysis: processing, inversion, and interpretation of seismic data. Society of Exploration Geophysicists
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.baztech-fa8612a3-a9a1-4f39-afe7-10a94d598152