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Fluid identification based on P-wave anisotropy dispersion gradient inversion for fractured reservoirs

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Fluid identification in fractured reservoirs is a challenging issue and has drawn increasing attentions. As aligned fractures in subsurface formations can induce anisotropy, we must choose parameters independent with azimuths to characterize fractures and fluid effects such as anisotropy parameters for fractured reservoirs. Anisotropy is often frequency dependent due to wave-induced fluid flow between pores and fractures. This property is conducive for identifying fluid type using azimuthal seismic data in fractured reservoirs. Through the numerical simulation based on Chapman model, we choose the P-wave anisotropy parameter dispersion gradient (PADG) as the new fluid factor. PADG is dependent both on average fracture radius and fluid type but independent on azimuths. When the aligned fractures in the reservoir are meter-scaled, gas-bearing layer could be accurately identified using PADG attribute. The reflection coefficient formula for horizontal transverse isotropy media by Rüger is reformulated and simplified according to frequency and the target function for inverting PADG based on frequency-dependent amplitude versus azimuth is derived. A spectral decomposition method combining Orthogonal Matching Pursuit and Wigner–Ville distribution is used to prepare the frequency-division data. Through application to synthetic data and real seismic data, the results suggest that the method is useful for gas identification in reservoirs with meter-scaled fractures using high-qualified seismic data.
Czasopismo
Rocznik
Strony
1081--1093
Opis fizyczny
Bibliogr. 35 poz.
Twórcy
autor
  • Unconventional Natural Gas Research Institute, State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum, Beijing, China
  • State Key Laboratory of Petroleum Resources and Prospecting, CNPC Key Lab of Geophysical Exploration, China University of Petroleum, Beijing, China
autor
  • State Key Laboratory of Petroleum Resources and Prospecting, CNPC Key Lab of Geophysical Exploration, China University of Petroleum, Beijing, China
  • Unconventional Natural Gas Research Institute, State Key Laboratory of Petroleum Resources and Prospecting, Chin
autor
  • Unconventional Natural Gas Research Institute, State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum, Beijing, China
  • State Key Laboratory of Petroleum Resources and Prospecting, CNPC Key Lab of Geophysical Exploration, China University of Petroleum, Beijing, China
autor
  • Xinjiang Oilfield Branch Company, PetroChina Company Limited, Karamay, China
Bibliografia
  • 1. Al-Harrasi OH, Kendall JM, Chapman M (2011) Fracture characterization using frequency-dependent shear wave anisotropy analysis of microseismic data [J]. Geophys J Int 185(2):1059–1070
  • 2. Banik NC (1987) An effective anisotropy parameter in transversely isotropic media [J]. Geophysics 52(12):1654–1664
  • 3. Castagna JP, Sun S, Siegfried RW (2003) Instantaneous spectral analysis: detection of low-frequency shadows associated with hydrocarbons. Lead Edge 22(2):120–127
  • 4. Chapman M (2001) Modelling the wide-band laborator y response of rock samples to fluid pressure changes. Ph.D. thesis, University of Edinburgh
  • 5. Chapman M (2003) Frequency-dependent anisotropy due to meso-scale fractures in the presence of equant porosity. Geophys Prospect 51(5):369–379
  • 6. Chapman M, Zatsepin S, Crampin S (2002) Derivation o f a microstructural poroelastic model [J]. Geophys J Int 151(2):427–451
  • 7. Chapman M, Maultzsch S, Liu E et al (2003) The effect of fluid saturation in an anisotropic multi-scale equant porosity model [J]. J Appl Geophys 54(3–4):191–202
  • 8. Chapman M, Liu E, Li XY (2006) The influence of fluid-sensitive dispersion and attenuation on AVO analysis. Geophys J Int 167(1):89–105
  • 9. Chen W (1995) AVO in azimuthally anisotropic media: fracture detection using P-wave data and a seismic study of naturally fractured tight gas reservoirs. Ph.D. dissertation, Stanford University
  • 10. Chen H, Zhang G, Ji Y et al (2017) Azimuthal seismic amplitude difference inversion for fracture weakness [J]. Pure Appl Geophys 174:279
  • 11. Cheng BJ, Xu TJ (2012) Research and application of frequency dependent AVO analysis for gas recognition [J]. Chin J Geophys Chin Edn 55(2):608–613
  • 12. Daley PF, Hron F (1977) Reflection and transmission coefficients for transversely isotropic media [J]. Bull Seismol Soc Am 67(3):661–675
  • 13. Fatti JL (1994) Detection of gas in sandstone reservoirs using AVO analysis: a 3-D seismic case history using the Geostack technique [J]. Geophysics 59(59):1362–1376
  • 14. Goodway W, Chen T, Downton J (1997) Improved AVO fluid detection and lithology discrimination using Lamé petrophysical parameters; “λρ”, “μρ”, &“λ/μ fluid stack”, from P and S inversions [J]. In: SEG technical program expanded abstracts, pp 183–186
  • 15. Gray FD (2002) Elastic inversion for lamé parameters [J]. In: SEG technical program expanded abstracts, pp 697–700
  • 16. Huang HD, Wang JB, Guo F (2012) Application of sensitive parameters analysis in fluid recognition based on pre-stack inversion [J]. Geophys Geochem Explor 36(6):941–946
  • 17. Macbeth C, Lynn HB (2000) Applied seismic anisotropy: theory background and field studies [C]. Society of Exploration Geophysicists, Tulsa, pp 682–685
  • 18. Mallat S, Zhang Z (1993) Matching pursuit with time–frequency dictionaries [J]. IEEE Trans Signal Process 41(12):3397–3415
  • 19. Marfurt KJ, Kirlin RL (2001) Narrow-band spectral analysis and thin-bed tuning [J]. Geophysics 66(4):1274–1283
  • 20. Mavko G, Jizba D (1991) Estimating grain-scale fluid effects on velocity dispersion in rocks [J]. Geophysics 56(12):1940–1949
  • 21. Partyka GJ, Gridley J, Lopez J (1999) Interpretational applications of spectral decomposition in reservoir characterization. Lead Edge 18(3):173–184
  • 22. Rüger A (1997) P-wave reflection coefficients for transversely isotropic models with vertical and horizontal axis of symmetry [J]. Geophysics 62(3):713–722
  • 23. Rüger A (1998) Variation of P-wave reflectivity with offset and azimuth in anisotropic media [J]. Geophysics 63:935–947
  • 24. Russell BH, Gray D, Hampson DP (2011) Linearized AVO and poroelasticity [J]. Geophysics 76(3):C19–C29
  • 25. Schoenberg M, Protazio J (1992) “Zoeppritz” rationalized, and generalized to anisotropic media [J]. J Seism Explor 1(2):125–144
  • 26. Smith GC, Gidlow PM (1987) Weighted stacking for rock property estimation and detection of gas [J]. Geophys Prospect 35(9):993–1014
  • 27. Thomsen L (1993) Weak anisotropic reflections. In: Castagna J, Backus M (eds) Offset-dependent reflectivity—theory and practice of AVO analysis. Society of Exploration Geophysicists, Tulsa, pp 103–114
  • 28. Thomsen L (1995) Elastic anisotropy due to aligned cracks in porous rocks. Geophys Prospect 43(6):805–829
  • 29. Tsvankin I (1997) Reflection moveout and parameter estimation for horizontal transverse isotropy [J]. Geophysics 62(2):614–629
  • 30. Václav V, Ivan P (1998) PP-wave reflection coefficients in weakly anisotropic elastic media [J]. Geophysics 63(6):2129–2141
  • 31. Wilson A (2010) Theory and methods of frequency-dependent AVO Inversion. University of Edinburgh, Edinburgh
  • 32. Wu X, Chapman M, Li XY (2012) Frequency-dependent AVO attribute: theory and example [J]. First Break 30:67–72
  • 33. Wu X, Chapman M, Li XY et al (2014) Quantitative gas saturation estimation by frequency-dependent amplitude-versus-offset analysis [J]. Geophys Prospect 62(6):1224–1237
  • 34. Zhang SX, Yin XY, Zhang GZ (2011) Dispersion-dependent attribute and application in hydrocarbon detection [J]. J Geophys Eng 8(4):498–507
  • 35. Zhang Z, Yin XY, Hao QY (2014) Frequency dependent fluid identification method based on AVO inversion. Chin J Geophys Chin Edn 57(12):4171–4184
Uwagi
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018)
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-60eb881d-e828-42c2-826e-2e70bd71d156
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