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Thin interbed AVA inversion based on a fast algorithm for refectivity

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Języki publikacji
EN
Abstrakty
EN
Zoeppritz equations form the theoretical basis of most existing amplitude variation with incident angle (AVA) inversion methods. Assuming that only primary refections exist, that is, the multiples are fully suppressed and the transmission loss and geometric spreading are completely compensated for, Zoeppritz equations can be used to solve for the elastic parameters of strata efectively. However, for thin interbeds, conventional seismic data processing technologies cannot suppress the internal multiples efectively, nor can they compensate for the transmission loss accurately. Therefore, AVA inversion methods based on Zoeppritz equations or their approximations are not applicable to thin interbeds. In this study, we propose a prestack AVA inversion method based on a fast algorithm for refectivity. The fast refectivity method can compute the full-wave responses, including the refection, transmission, mode conversion, and internal multiples, which is benefcial to the seismic inversion of thin interbeds. A further advantage of the fast refectivity method is that the partial derivatives of the refection coefcient with respect to the elastic parameters can be expressed as analytical solutions. Based on the Gauss– Newton method, we construct the objective function and model-updating formula considering sparse constraint, where the Jacobian matrix takes the form of an analytical solution, which can signifcantly accelerate the inversion convergence. We validate our inversion method using numerical examples and feld seismic data. The inversion results demonstrate that the fast refectivity-based inversion method is more efective for thin interbed models in which the wave-propagation efects, such as interval multiples, are difcult to eliminate.
Czasopismo
Rocznik
Strony
1007--1020
Opis fizyczny
Bibliogr. 35 poz.
Twórcy
autor
  • Key Laboratory of Earth and Planetary Physics, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing 100029, China
  • University of Chinese Academy of Sciences, Beijing 100049, China
autor
  • School of Geophysics and Information Technology, China University of Geosciences, Beijing 100083, China
Bibliografia
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  • 3. Deng F, McMechan GA (2007) True-amplitude prestack depth migration. Geophysics 72(3):S155–S166. https://doi.org/10.1190/1.2714334
  • 4. Fatti JL, Smith GC, Vail PJ et al (1994) Detection of gas in sandstone reservoirs using AVO analysis: a 3-D seismic case history using the Geostack technique. Geophysics 59:1362–1376. https://doi.org/10.1190/1.1443695
  • 5. Fryer GJ (1980) A slowness approach to the reflectivity method of seismogram synthesis. Geophys J Int 63(3):747–758. https://doi.org/10.1111/j.1365-246X.1980.tb02649.x
  • 6. Fuchs K (1968) The reflection of spherical waves from transition zones with arbitrary depth-dependent elastic moduli and density. J Phys Earth 16:27–41. https://doi.org/10.4294/jpe1952.16.Special_27
  • 7. Fuchs K, Müller G (1971) Computation of synthetic seismograms with the reflectivity method and comparison with observations. Geophys J Int 23(4):417–433. https://doi.org/10.1111/j.1365-246X.1971.tb01834.x
  • 8. Jin S (1999) Characterizing reservoir by using jointly P- and S- wave AVO analyses. SEG Tech Program Expand Abstr. https://doi.org/10.1190/1.1821117
  • 9. Kennett BLN (1974) Reflections, rays, and reverberations. Bull Seismol Soc Am 64(6):1685–1696
  • 10. Kennett BLN (1983) Seismic wave propagation in stratified media. Cambridge University Press, Cambridge. https://doi.org/10.22459/SWPSM.05.2009
  • 11. Kennett BLN (2009) Seismic wave propagation in stratified media. ANU E Press, Canberra
  • 12. Larsen JA (1999) AVO inversion by simultaneous P–P and P–S Inversion. M.Sc. thesis, University of Calgary
  • 13. Levenberg K (1944) A method for the solution of certain non-linear problems in least squares. Quart Appl Math 2:164–168. https://doi.org/10.1090/qam/1944-02-02
  • 14. Liu HX, Li JY, Chen XH et al (2016) Amplitude variation with offset inversion using the reflectivity method. Geophysics 81(4):R185–R195. https://doi.org/10.1190/geo2015-0332.1
  • 15. Lu J, Yang Z, Wang Y et al (2015) Joint PP and PS AVA seismic inversion using exact Zoeppritz equations. Geophysics 80(5):R239–R250. https://doi.org/10.1190/geo2014-0490.1
  • 16. Lu J, Meng X, Wang Y et al (2016) Prediction of coal seam details and mining safety using multicomponent seismic data: a case history from China. Geophysics 81:B149–B165. https://doi.org/10.1190/geo2016-0009.1
  • 17. Lu J, Wang Y, Chen J et al (2017) Joint anisotropic AVO inversion of PP and PS seismic data. Geophysics 83(2):1–83. https://doi.org/10.1190/geo2016-0516.1
  • 18. Liu W, Wang Y-C, Li J-Y et al (2018) Prestack AVA joint inversion of PP and PS waves using the vectorized reflectivity method. Appl Geophys 15(3–4):448–465. https://doi.org/10.1007/s11770-018-0695-4
  • 19. Luo C, Li XY, Huang GT (2018) Hydrocarbon identification by application of improved sparse constrained inverse spectral decomposition to frequency-dependent AVO inversion. J Geophys Eng 15(5):1446–1459. https://doi.org/10.1088/1742-2140/aab1d6
  • 20. Mahmoudian F, Margrave GF (2004) Three parameter AVO inversion with PP and PS data using offset binning. SEG Tech Program Expand Abstr. https://doi.org/10.1190/1.1851239
  • 21. Mallick S, Frazer LN (1987) Practical aspects of reflectivity modeling. Geophysics 52(10):1355–1364. https://doi.org/10.1190/1.1442248
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  • 23. Paige CC, Saunders MA (1982) LSQR: an algorithm for sparse linear equations and sparse least squares. ACM Trans Math Softw (TOMS) 8(1):43–71. https://doi.org/10.1145/355984.355989
  • 24. Phinney RA, Odom RI, Fryer GJ (1987) Rapid generation of synthetic seismograms in layered media by vectorization of the algorithm. Bull Seismol Soc Am 77(6):2218–2226
  • 25. Sen MK, Roy IG (2003) Computation of differential seismograms and iteration adaptive regularization in prestack waveform inversion. Geophysics 68(6):2026–2039. https://doi.org/10.1190/1.1635056
  • 26. Sheen D-H, Tuncay K, Baag C-E et al (2006) Time domain Gauss–Newton seismic waveform inversion in elastic media. Geophys J Int 167(3):1373–1384. https://doi.org/10.1111/j.1365-246X.2006.03162.x
  • 27. Stewart RR (1990) Joint P and P–SV inversion. The CREWES Project research report 2.
  • 28. Tarantola A (1986) A strategy for nonlinear elastic inversion of seismic reflection data. Geophysics 51(10):1893–1903. https://doi.org/10.1190/1.1442046
  • 29. Tiğrek S, Slob EC, Dillen MWP et al (2005) Linking dynamic elastic parameters to static state of stress: toward an integrated approach to subsurface stress analysis. Tectonophysics 397(1–2):167–179. https://doi.org/10.1016/j.tecto.2004.10.008
  • 30. Wang Y-M, Wang X-P, Meng X-J et al (2011) Pre-stack inversion of wide incident angle seismic data. SEG Tech Program Expand Abstr. https://doi.org/10.1190/1.3627713
  • 31. Wang Y, Xu X, Zhang Y-G (2016) Ultrasonic elastic characteristics of six kinds of metamorphic coals in China under room temperature and pressure conditions Chinese. J Geophys Ch 59(7):2726–2738. https://doi.org/10.6038/cjg20160735
  • 32. Weglein AB, Hsu S-Y, Terenghi P et al (2011) Multiple attenuation: recent advances and the road ahead. Lead Edge 30(8):864–875. https://doi.org/10.1190/1.3626494
  • 33. Xu T, Zhang H, McMechan GA (1998) Amplitude compensation of seismic data: application to masking by shallow bright spots. J Seism Explor 7:173–198
  • 34. Yuan SY, Liu Y, Zhang Z, Luo CM (2019) Prestack stochastic frequency-dependent velocity inversion with rock-physics constraints and statistical associated hydrocarbon attributes. IEEE Geosci Remote Sens Lett 16(1):140–144
  • 35. Zhang Y, Zhang G, Bleistein N (2003) True amplitude wave equation migration arising from true amplitude one-way wave equations. Inverse Probl 19(5):1113–1138. https://doi.org/10.1088/0266-5611/19/5/307
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021)
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-5dfc42b9-d226-4b3d-a392-9612d52cbace
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