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Fracture identification with acoustic logging
Locating fractures, recognizing fracture morphology, and identifying fluid-flow properties in the fracture system are important criteria in characterizing reservoirs that produce predominantly from fracture systems. Acoustic techniques can provide insight.
What can be learned from acoustic logging
Fracture identification and evaluation using conventional resistivity and compressional-wave acoustic logs is difficult, in part because fracture recognition is very dependent on the dip angle of fractures with respect to the borehole.
Fractures are physical discontinuities that generate acoustic reflection, refraction, and mode conversion—all of which contribute to a loss of transmitted acoustic energy. In particular, compressional- and shear-wave amplitude and attenuation and Stoneley-wave attenuation are significantly affected by the presence of fractures. Compressional waves are primarily affected by oblique fractures—those with dip angles between 15° and 85°—while shear waves are primarily affected by horizontal or near-horizontal fractures.[1] On conventional-velocity logs, fracture-induced attenuation may be evidenced as[2][3]:
- Cycle skipping
- Variations in the Vp/Vs ratio and on VDL presentations
- Chevron (crisscross) patterns caused by mode-conversion interference
Borehole-televiewer-type imaging devices provide a higher degree of success in identifying fractures and determining whether or not they are open (producible) or closed. The development of reliable full-waveform shear- and borehole-imaging devices enabled enhanced fracture identification and evaluation.[4][5] Aguilera[6] summarizes the use of conventional acoustic-log methods for fracture identification.
Recently developed anisotropy-analysis methods use the following methods—individually or in combination—to provide reliable identification and evaluation of in-situ and induced fractures:
- Crossed-dipole shear
- Stoneley-wave
- Acoustic-imaging data
(see the Anisotropy analysis article for more information on crossed-dipole anisotropy analysis)
Stoneley-wave analysis
The pressure-driven, fluid-borne nature of Stoneley waves makes them sensitive to fluid movement, and thus, to open fractures. The effects of open fractures on Stoneley waves are[7][8][9]:
- Amplitude reduction
- An increase in Stoneley slowness
- The occurrence of mode conversion
- The occurrence of Stoneley reflections
The Stoneley wave responds to fracture permeability while NMR does not, thus, the Stoneley-wave permeability is greater in the presence of fractures than NMR permeability. The combined use of Stoneley- and NMR-derived permeability provides a fracture indicator in both sandstones (Fig. 1) and carbonates (Fig. 2).[10]
Fig. 1 – Stonely-wave and NMR permeability profiles in the presence of borehole fractures. Stoneley-wave results are dominated by the fracture-system contribution, while the NMR results are dominated by the matrix-based permeability. The fractured sandstone interval, indicated by separation of the two permeability curves (Tracks 2 and 6), is confirmed by Stoneley-wave reflection data (Track 3) and the acoustic image log (Track 5) (courtesy of Baker Atlas).
Fig. 2 – Correlation between azimuthal anisotropy and Stoneley reflections. A fracture zone in a U.S. mid-continent well causes both shear-wave splitting and Stoneley-wave reflections – in the anisotropy map (left), brighter colors represent higher anisotropy. The azimuth of the fast shear arrival is east/west (center). The fractures intersecting the borehole cause significant up- and down-going Stoneley-wave reflections seen in Stoneley-waveform amplitudes (right) (courtesy of Baker Atlas).
References
- ↑ Morris, R.L., Grine, D.R., and Arkfeld, T.E. 1964. Using Compressional and Shear Acoustic Amplitudes for The Location of Fractures. J Pet Technol 16 (6): 623-632. SPE-723-PA. http://dx.doi.org/10.2118/723-PA
- ↑ Minne, J.-C. and Gartne, J. 1979. Fracture Detection in the Middle East. Presented at the Middle East Technical Conference and Exhibition, Bahrain, 25-28 February 1979. SPE-7773-MS. http://dx.doi.org/10.2118/7773-MS
- ↑ Cheung, P.S.V. 1984. Fracture Detection Using the Sonic Tool, paper 42. Trans., 1984 Intl. Formation Evaluation Symposium, SPWLA, Paris Chapter (SAID) 1–8.
- ↑ Prensky, S. 1999. Advances in Borehole Imaging Technology and Applications. In Borehole Imaging—Applications and Case Histories, M.A. Lovell, G. Williamson, and P.K. Harvey eds., 1-44. London: Geological Soc., Special Publication No. 159.
- ↑ Paillet, F.L. 1991. Qualitative and Quantitative Interpretations of Fracture Permeability by Means of Acoustic Full-Waveform Logs. The Log Analyst 32 (3): 256–270.
- ↑ Aguilera, R. 1995. Formation Evaluation by Well Log Analysis. In Naturally Fractured Reservoirs, second edition, Ch. 3, 181-315. Tulsa, Oklahoma: PennWell Publishing Co.
- ↑ Paillet, F.L. 1991. Qualitative and Quantitative Interpretations of Fracture Permeability by Means of Acoustic Full-Waveform Logs. The Log Analyst 32 (3): 256–270.
- ↑ Hornby, B.E. et al. 1989. Fracture Evaluation Using Reflected Stoneley-Wave Arrivals. Geophysics 54 (10): 1,274–1,288. http://dx.doi.org/10.1190/1.1442587
- ↑ Medlin, W.L. and Schmitt, D.P. 1994. Fracture Diagnostics With Tube-Wave Reflection Logs. J Pet Technol 46 (3): 239-248. SPE-22872-PA. http://dx.doi.org/10.2118/22872-PA
- ↑ Tang, X.M., Altunbay, M., and Shorey, D. 1998. Joint Interpretation of Formation Permeability from Wireline Acoustic NMR, and Image Log Data, paper KK. Trans., 1998 Annual Logging Symposium, SPWLA, 1–13.
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