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Acta Geodaetica et Geophysica

, Volume 53, Issue 4, pp 679–690 | Cite as

Modeling acoustic attenuation of discrete stochastic fractured media

  • Guiwu Chen
  • Lei SongEmail author
  • Ray Ruichong Zhang
Original Study
  • 106 Downloads

Abstract

The acoustic response has many important roles in seismic exploration and nondestructive testing. It enables the development of fracture classification and sizing. In this paper, we combined Hudson’s effective medium scheme and finite-difference time-domain modeling method to simulate acoustic wave propagation in fractured media. Fractures are represented by discrete fracture networks, allowing for a state-of-the-art representation of natural fracture networks by a negative Exponential Law length distribution. The propagation of acoustic waves that are emitted by a point source and reflected from a fractured area in a 2D digital rock model are examined numerically with the purpose of developing an acoustic inference of fracture properties. In these fractured models, we vary the number and mean length of fractures to explore the relation between internal structure of rock and acoustic wave field characters. The modeling results indicate that acoustic wave field is more sensitive to the fracture number than to the mean of the fracture length. Moreover, a fracture-dependent attenuation analysis of the reflection records of discrete stochastic fractured models is obtained. The frequency- and time- dependent attenuation profiles feature two parts in frequency, (1) fracture-to-background at lower frequencies and (2) fracture-to-fracture at higher frequencies. Our results indicate that accounting for attenuation effects may not only allow for improving estimation of fracture number, but also provide information about geometrical characteristics of length distribution. Such an approach can be used to estimate nature fracture network properties with given acoustic records.

Keywords

Acoustic wave modeling Attenuation estimation Stochastic fracture networks 

Notes

Acknowledgements

We would like to thank Doc. Younes Fadakar Alghalandis for providing ADFNE software for discrete fracture modeling. This research is supported by the National Science Foundation of China (NSFC Grant Nos. 41474122 and 51323004).

References

  1. Bakulin A, Grechka V, Tsvankin I (2000) Estimation of fracture parameters from reflection seismic data—Part III: fractured models with monoclinic symmetry. Geophysics 65:1818–1830.  https://doi.org/10.1190/1.1444865 CrossRefGoogle Scholar
  2. Barbosa ND, Rubino JG, Caspari E, Holliger K (2017) Sensitivity of seismic attenuation and phase velocity to intrinsic background anisotropy in fractured porous rocks: a numerical study. J Geophys Res Solid Earth 122:8181–8199.  https://doi.org/10.1002/2017jb014558 CrossRefGoogle Scholar
  3. Bohlen T (2002) Parallel 3-D viscoelastic finite difference seismic modelling. Comput Geosci 28:887–899.  https://doi.org/10.1016/S0098-3004(02)00006-7 CrossRefGoogle Scholar
  4. Dasgupta R, Clark RA (1998) Estimation of Q from surface seismic reflection data. Geophysics 63:2120–2128.  https://doi.org/10.1190/1.1444505 CrossRefGoogle Scholar
  5. Ehsan MI, Ahmed N, Din ZU, Khalid P, Wei LX (2016) An application of AVO derived attributes to analyze seismic anomalies of gas hydrate bearing sediments in Makran offshore, Pakistan. Acta Geod Geophys 51:671–683.  https://doi.org/10.1007/s40328-015-0146-0 CrossRefGoogle Scholar
  6. Fadakar Alghalandis Y (2017) ADFNE: open source software for discrete fracture network engineering, two and three dimensional applications. Comput Geosci 102:1–11.  https://doi.org/10.1016/j.cageo.2017.02.002 CrossRefGoogle Scholar
  7. Hentati H, Kriaa Y, Haugou G, Chaari F, Wali M, Zouari B, Dammak F (2017) Influence of elastic wave on crack nucleation—experimental and computational investigation of brittle fracture. Appl Acoust 128:45–54.  https://doi.org/10.1016/j.apacoust.2017.04.019 CrossRefGoogle Scholar
  8. Hunziker J, Favino M, Caspari E, Quintal B, Rubino JG, Krause R, Holliger K (2018) Seismic attenuation and stiffness modulus dispersion in porous rocks containing stochastic fracture networks. J Geophys Res Solid Earth 123:125–143.  https://doi.org/10.1002/2017jb014566 CrossRefGoogle Scholar
  9. Kruger OS, Saenger EH, Oates SJ, Shapiro SA (2007) A numerical study on reflection coefficients of fractured media. Geophysics 72:D61–D67.  https://doi.org/10.1190/1.2732690 CrossRefGoogle Scholar
  10. Liu TH (2012) High precision numerical modeling and dynamic characteristic analysis of seismic scattering wave. Chin J Geophys Chin 55:1318–1324.  https://doi.org/10.6038/j.issn.0001-5733.2012.04.027 CrossRefGoogle Scholar
  11. Liu ER, Hudson JA, Pointer T (2000) Equivalent medium representation of fractured rock. J Geophys Res Sol Ea 105:2981–3000.  https://doi.org/10.1029/1999JB900306 CrossRefGoogle Scholar
  12. Muller TM, Gurevich B, Lebedev M (2010) Seismic wave attenuation and dispersion resulting from wave-induced flow in porous rocks—a review. Geophysics 75:A147–A164.  https://doi.org/10.1190/1.3463417 CrossRefGoogle Scholar
  13. Saenger EH, Kruger OS, Shapiro SA (2006) Effective elastic properties of fractured rocks: dynamic vs. static considerations. Int J Fracture 139:569–576.  https://doi.org/10.1007/s10704-006-0105-4 CrossRefGoogle Scholar
  14. Schubnel A, Gueguen Y (2003) Dispersion and anisotropy of elastic waves in cracked rocks. J Geophys Res Sol Ea.  https://doi.org/10.1029/2002jb001824 CrossRefGoogle Scholar
  15. Szokoli K, Szarka L, Metwaly M, Kalmar J, Pracser E, Szalai S (2018) Characterisation of a landslide by its fracture system using electric resistivity tomography and pressure probe methods. Acta Geod Geophys 53:15–30.  https://doi.org/10.1007/s40328-017-0199-3 CrossRefGoogle Scholar
  16. Wang B, Liu SD, Zhou FB, Lu T, Huang LY, Gao YJ (2016) Polarization migration of three-component reflected waves under small migration aperture condition. Acta Geodyn Geomater 13:47–58.  https://doi.org/10.13168/AGG.2015.0049 CrossRefGoogle Scholar
  17. Wang XJ, Zhang B, Zhao T, Hang JB, Wu H, Yong ZQ (2017) Facies analysis by integrating 3D seismic attributes and well logs for prospect identification and evaluation—a case study from Northwest China. Interpretation J Sub 5:Se61-Se74.  https://doi.org/10.1190/INT-2016-0149.1 CrossRefGoogle Scholar
  18. Wu H, Dong S, Li D, Huang Y, Qi X (2015) Experimental study on dynamic elastic parameters of coal samples. Int J Min Sci Technol 25:447–452.  https://doi.org/10.1016/j.ijmst.2015.03.019 CrossRefGoogle Scholar
  19. Yang H, Shan R, Zhang J, Wu F, Guo Z (2018) Mechanical properties of frozen rock mass with two diagonal intersected fractures. Int J Min Sci Technol 28:631–638.  https://doi.org/10.1016/j.ijmst.2018.02.005 CrossRefGoogle Scholar
  20. Yue C, Yue X (2017) Simulation of acoustic wave propagation in a borehole surrounded by cracked media using a finite difference method based on Hudson’s approach. J Geophys Eng 14:633–640.  https://doi.org/10.1088/1742-2140/aa5af8 CrossRefGoogle Scholar
  21. Zhou H, Fu LY (2018) Scattering and intrinsic components of attenuation through the spectral ratio method in ultrasonic laboratory experiment. Chin J Geophys Chin 61:1083–1094.  https://doi.org/10.6038/cjg2018L0359 CrossRefGoogle Scholar
  22. Zhou P, Zhang Y, Za Huang, Gao Y, Wang H, Luo Q (2017) Coal and gas outburst prevention using new high water content cement slurry for injection into the coal seam. Int J Min Sci Technol 27:669–673.  https://doi.org/10.1016/j.ijmst.2017.05.003 CrossRefGoogle Scholar

Copyright information

© Akadémiai Kiadó 2018

Authors and Affiliations

  1. 1.State Key Laboratory of Geomechanics and Deep Underground EngineeringChina University of Mining and TechnologyXuzhouChina
  2. 2.Department of Civil and Environmental EngineeringColorado School of MinesGoldenUSA

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