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Low porosity and low permeability reservoirs characterization using low frequency seismic attribute

Wybrane pełne teksty z tego czasopisma
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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The low-frequency seismic refection is important for the characterization of hydrocarbon reservoirs. Previous research has proved that the frequency-dependent component of the low-frequency refection coefcient is approximately proportional to the reservoir fuid mobility. A low-frequency seismic attribute is defned to extract an approximate measurement of reservoir fuid mobility from seismic refection data. Based on the high-resolution time–frequency decomposition technology, we apply this seismic attribute to detect hydrocarbons in shale and igneous reservoirs with low porosity and low permeability. The application results illustrate that the low-frequency seismic attribute can not only indicate the spatial distribution of oil and gas, which can help design the optimal landing point and trajectory of directional drilling, but also be approximately proportional to the production of oil and gas, which can be used for resource evaluation during the early exploration stage. We also give a brief discussion on the working mechanism of the low-frequency seismic attribute. The present work may provide some references for the subsequent exploration and research of reservoirs with low porosity and low permeability.
Czasopismo
Rocznik
Strony
1345--1360
Opis fizyczny
Bibliogr. 42 poz.
Twórcy
autor
  • State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum-Beijing, Beijing 102249, People’s Republic of China
  • College of Geophysics, China University of Petroleum-Beijing, Beijing 102249, People’s Republic of China
  • State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum-Beijing, Beijing 102249, People’s Republic of China
  • College of Geophysics, China University of Petroleum-Beijing, Beijing 102249, People’s Republic of China
autor
  • State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum-Beijing, Beijing 102249, People’s Republic of China
  • College of Geophysics, China University of Petroleum-Beijing, Beijing 102249, People’s Republic of China
autor
  • Fourth Oil Production Plant of Huabei Oilfeld, CNPC, Renqiu 062550, People’s Republic of China
Bibliografia
  • 1. Batzle M, Han D, Hofmann R (2006) Fluid mobility and frequency-dependent seismic velocity—direct measurements. Geophysics 71(1):1–9
  • 2. Bhatti B, Brown R (2016) Low-frequency seismic analysis and direct hydrocarbon indicators. SEG Tech Program Expand Abstr 2051−2056
  • 3. Biot MA (1956a) Theory of propagation of elastic waves in a fluid-saturated porous solid. I. Low-frequency range. J Acoust Soc Am 28(2):168–178
  • 4. Biot MA (1956b) Theory of propagation of elastic waves in a fluid-saturated porous solid II Higher frequency range. J Acoust Soc Am 28(2):179–191
  • 5. Buland A, Omre H (2003) Bayesian linearized AVO inversion. Geophysics 68(1):185–198
  • 6. Castagna JP, Sun S, Siegfried RW (2003) Instantaneous spectral analysis: detection of low-frequency shadows associated with hydrocarbons. Lead Edge 22(2):120–127
  • 7. Caudle BH, Dyes AB (1958) Improving miscible displacement by gas-water injection. Soc Petrol Eng 213(11):281–284
  • 8. Chabyshova E, Goloshubin G (2014) Seismic modeling of low-frequency “shadows” beneath gas reservoirs. Geophysics 79(6):417–423
  • 9. 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
  • 10. Dasgupta R, Clark RA (1998) Estimation of Q from surface seismic reflection data. Geophysics 63(6):2120–2128
  • 11. Dasios A, Astin TR, McCann C (2001) Compressional-wave Q estimation from full-waveform sonic data. Geophys Prospect 49(3):353–373
  • 12. Ebrom D (2004) The low-frequency gas shadow on seismic sections. Lead Edge 23:772–772
  • 13. Goloshubin GM, Van Schuyver C, Korneev V et al (2006) Reservoir imaging using low frequencies of seismic reflections. Lead Edge 25(5):527–531
  • 14. Goloshubin GM (2000) Seismic low-frequency effects from fluid-saturated reservoir. SEG Tech Program Expand Abstr 1671−1674
  • 15. Goloshubin, GM, Korneev, V, Vingalov, VM (2002) Seismic low-frequency effects from oil-saturated reservoir zones. SEG Tech Program Expand Abstr 1813–1816
  • 16. Gurevich B, Zyrianov VB, Lopatnikov SL (1997) Seismic attenuation in finely layered porous rocks: effects of fluid flow and scattering. Geophysics 62(1):319–324
  • 17. Han C, Jiang Z, Han M et al (2016) The lithofacies and reservoir characteristics of the Upper Ordovician and Lower Silurian black shale in the Southern Sichuan Basin and its periphery, China. Mar Pet Geol 75:181–191
  • 18. He Z, Xiong X, Bian L (2008) Numerical simulation of seismic low-frequency shadows and its application. Appl Geophys 5(4):301–306
  • 19. Hilterman F (2007) Advanced reservoir imaging using frequency-dependent seismic attributes. Dissertation, University of Houston
  • 20. Huang HD, Zhang RW, Shen GQ et al (2011) Study of prestack elastic parameter consistency inversion methods. Appl Geophys 8(4):311–318
  • 21. Huang HD, Wang YC, Guo F et al (2015) Zoeppritz equation-based prestack inversion and its application in fluid identification. Appl Geophys 12(2):199–211
  • 22. Ji YZ, Yuan SY, Wang SX, Deng L (2016) Frequency-domain sparse Bayesian learning inversion of AVA data for elastic parameters reflectivities. J Appl Geophys 133:1–8
  • 23. Korneev VA, Goloshubin GM, Daley TM, Silin DB (2004) Seismic low-frequency effects in monitoring fluid-saturated reservoirs. Geophysics 69(2):522–532
  • 24. Lichman E, Goloshubin G (2003) Unified approach to gas and fluid detection on instantaneous seismic wavelets. SEG Tech Progr Expand Abstr 1699−1702
  • 25. Liu L, Cao S, Wang L (2011) Poroelastic analysis of frequency-dependent amplitude-versus-offset variations. Geophysics 76(3):C31–C40
  • 26. Rapoport MB, Rapoport LI, Ryjkov VI (2004) Direct detection of oil and gas fields based on seismic inelasticity effect. Lead Edge 23(3):276–278
  • 27. Ren H, Goloshubin G, Hilterman FJ (2009) Poroelastic analysis of amplitude-versus-frequency variations. Geophysics 74(6):41–48
  • 28. Shapiro SA, Müller TM (1999) Seismic signatures of permeability in heterogeneous porous media. Geophysics 64(1):99–103
  • 29. Silin D, Goloshubin G (2010) An asymptotic model of seismic reflection from a permeable layer. Transp Porous Media 83(1):233–256
  • 30. Silin DB, Korneev VA, Goloshubin GM, Patzek TW (2004) A hydrologic view on Biot's theory of poroelasticity. Lawrence Berkeley National Laboratory Report, Berkeley, California, USA
  • 31. Taner MT, Koehler F, Sheriff RE (1979) Complex seismic trace analysis. Geophysics 44(6):1041–1063
  • 32. Toksöz MN, Johnston DH, Timur A (1979) Attenuation of seismic waves in dry and saturated rocks: I. Lab Meas Geophys 44(4):681–690
  • 33. Tonn R (1991) The determination of the seismic quality factor Q from VSP data: a comparison of different computational methods. Geophys Prospect 39(1):1–27
  • 34. Wang Y (2007) Seismic time-frequency spectral decomposition by matching pursuit. Geophysics 72(1):V13–V20
  • 35. Wang Y, Huang HD, Yuan S, Zhang S, Li BW (2016) Gas prediction using low-frequency components of variable-depth streamer seismic data applied to the deep water area of the South China Sea. J Nat Gas Sci Eng 34:1310–1320
  • 36. White JE (1975) Computed seismic speeds and attenuation in rocks with partial gas saturation. Geophysics 40(2):224–232
  • 37. White RS (1977) Seismic bright spots in the Gulf of Oman. Earth Planet Sci Lett 37(1):29–37
  • 38. Xi Z, Tang S, Wang J (2018) The reservoir characterization and shale gas potential of the Niutitang formation: case study of the SY well in northwest Hunan Province, South China. J Petrol Sci Eng 171:687–703
  • 39. Yuan SY, Wang SX, Ma M et al (2017) Sparse Bayesian learning-based time-variant deconvolution. IEEE Trans Geosci Remote Sens 55(11):6182–6194
  • 40. Yuan SY, Liu Y, Zhang Z et al (2018) Prestack stochastic frequency-dependent velocity inversion with rock-physics constraints and statistical associated hydrocarbon attributes. IEEE Geosci Remote Sens Lett 16(1):140–144
  • 41. Zhang H, Zhang R, Yang H et al (2014) Characterization and evaluation of ultra-deep fracture-pore tight sandstone reservoirs: a case study of Cretaceous Bashijiqike Formation in Kelasu tectonic zone in Kuqa foreland basin, Tarim, NW China. Petrol Explor Dev 41(2):175–184
  • 42. Zeng J, Huang HD, Li HJ et al (2017) A fast complex domain-matching pursuit algorithm and its application to deep-water gas reservoir detection. J Geophys Eng 14(6):1335–1348
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-f6eb4c3d-e8d6-4ed6-b75c-d8adc6800133
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