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Improving the resolution of seismic data based on S transform and modified variational mode decomposition, an application to Songliao Basin, Northeast China

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The sandstone of the lithologic reservoir in Songliao Basin is characterized by thin vertical thickness and rapid lateral pinch outs, which make it difficult to identify and describe the sandstone due to insufficient resolution of existing seismic data. To solve this problem, a method based on S-transform and modified variational mode decomposition is proposed to improve the resolution in the time–frequency domain by cepstrum deconvolution. Firstly, the time–frequency spectrum of seismic records is obtained by generalized S-transform; then it is transformed into cepstrum; and the wavelet amplitude spectrum is extracted by modified variational mode decomposition with permutation entropy, to realize the time–frequency domain deconvolution of cepstrum. After improving the resolution of seismic data in the study area, the frequency band of the data is broadened by more than 20%. After frequency expansion, the seismic refection structure reflects the sedimentary characteristics of the actual sandstone in the area. The seismic refection has a good correspondence with the well point sandstone, and the thin sandstone is clearly depicted. It is fully verified that this method can effectively improve the resolution of seismic data and has the characteristics of relative amplitude preservation.
Słowa kluczowe
Czasopismo
Rocznik
Strony
1103--1113
Opis fizyczny
Bibliogr. 25 poz.
Twórcy
autor
  • Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring, Ministry of Education, Changsha, People’s Republic of China
  • School of Geosciences and Info-Physics, Central South University, Changsha, People’s Republic of China
  • School of Geosciences and Info-Physics, Central South University, Changsha, People’s Republic of China
autor
  • College of Earth Sciences, Guilin University of Technology, Guilin, Guangxi, People’s Republic of China
autor
  • College of Earth Sciences, Guilin University of Technology, Guilin, Guangxi, People’s Republic of China
autor
  • Sichuan Earthquake Administration, Chengdu, Sichuan, People’s Republic of China
autor
  • Exploitation and Development Research Institute, PetroChina Daqing Oilfeld Company, Daqing, Heilongjiang, People’s Republic of China
Bibliografia
  • 1. An P, Yu ZL, Liu Z, Ma YH, Li L, Liu FX (2020) Application of sensitive frequency seismic attributes in thin sand body prediction: a case study of Zhaoyuan area. Songliao Basin Geophys Geochem Explor 44(02):321–328
  • 2. Bandt C, Pompe B (2002) Permutation entropy: a natural complexity measure for time series. Phys Rev Lett 88(17):174102
  • 3. Clarke KG (1968) Time-varying deconvolution filters. Geophysics 33(6):936–944
  • 4. Dragomiretskiy K, Zosso D (2014) Variational mode decomposition. IEEE Trans Signal Process 62(3):531–544
  • 5. Hale D (1949) Q-adaptive deconvolution. Seg Tech Program Expand Abstr 1(1):520
  • 6. Li ZB, Liu HL, Ma ZJ, Li YF, Xiao XB (2016) Slope matching waveform extension method suppressing the EMD end effect. J Northwest Univ (natural Science Edition) 46(5):7
  • 7. Li ZC, A-Li FJ, Wang DY, Wang J (2015) Time-varing deconvolution method based on tine-frequency domain. Prog Geophys 30(06):2698–2705
  • 8. Liu ZW, Cong N, Long Dan Wu, Nanke, (2018) Cepstral time-frequency domain deconvolution based on improved generalized S-transform. J China Univ Pet 42(05):57–64
  • 9. Mao WF, Zou ZL, Min CW (2019) Research and application of MVMD-ARMA residual correction ionospheric prediction model. Sci Surv Mapp 44(4):33–40
  • 10. Margrave GF (1998) Theory of nonstationary linear filtering in the fourier domain. Geophysics 63(1):244–259
  • 11. Margrave G, Lamoureux M (2001) Gabor deconvolution. CREWES Res Rep 13:241–276
  • 12. Margrave GF, Lamoureux MP, Henley DC (2011) Gabor deconvolution: Estimating reflectivity by nonstationary deconvolution of seismic data. Geophysics 76(3):W15–W30
  • 13. Pang X, Chen Z, Lerche I (1997) Uncertainty analysis and the relative contributions of geological factors for the Qingshankou source rocks in the North Songliao Basin. Northeast China Nonrenew Resour 6(4):263–271
  • 14. Pinnegar CR, Mansinha L (2003) The S-transform with windows of arbitrary and varying shape. Geophysics 68(1):381
  • 15. Rosa A, Ulrych TJ (1991) Processing via spectral modeling. Geophysics 56(8):1244–1251
  • 16. Stockwell RG, Mansinha L, Lowe RP (1996) Localization of the complex spectrum: the S transform. IEEE Trans Signal Process 44(4):998–1001
  • 17. Tang BW, Zhao B, Wu YH, Li HQ (2010) A new method to realize spectral simulation deconvolution. Pet Geophys Explor 45(A01):66–70
  • 18. Wang QZ, Jiang XD, Weng B, Liu ZP, Yin HY, Chen JJ (2015) Research and application of high-resolution technique based on Gabor transform with variable time window. China Offshore Oil Gas 27(006):19–26
  • 19. Yeh JR, Shieh JS, Huang NE (2010) Complementary ensemble empirical mode decomposition: a novel noise enhanced data analysis method. Adv Adapt Data Anal 2(2):135–156
  • 20. Yilmaz O (1987) Seismic data processing. Society of exploration geophysicists. Investig Geophys 2:1–526
  • 21. Zhang P, Dai YS, Tan YC, Zhang HQ, Wang CX (2019a) A time-varing wavelet extraction method using EMD and the relationship between wavelet amplitude and phase spectra. Chin J Geophys 62(2):680–696
  • 22. Zhang P, Dai Y, Zhang H, Wang C, Zhang Y (2019b) Combining CEEMD and recursive least square for the extraction of time-varying seismic wavelets. J Appl Geophys 170:103854
  • 23. Zheng JD, Cheng JS, Yang Y (2013) Modified EEMD algorithm and its applications. J Vib Shock 32(21):21–46
  • 24. Zhou HL, Wang CC, Marfurt KJ, Jiang YW, Bi JX (2016) Enhancing the resolution of non-stationary seismic data using improved time–frequency spectral modeling. Geophys J Int 205(1):203–219
  • 25. Ziolkowski A (1991) Why don’t we measure seismic signatures? Geophysics 56(2):190–201
Uwagi
PL
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-aa759197-c61d-4ee0-bf10-45e23bd29bd3
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