Successful Discoveries Using Novel DHI Technology Based on Seismic Resonance and Dispersion
- Kristofer Skantze (Rex Technology Management Ltd)
- Document ID
- Society of Petroleum Engineers
- Abu Dhabi International Petroleum Exhibition & Conference, 11-14 November, Abu Dhabi, UAE
- Publication Date
- Document Type
- Conference Paper
- 2019. Society of Petroleum Engineers
- Resonance, Delineation, Dispersion, Seismic, Exploration
- 4 in the last 30 days
- 71 since 2007
- Show more detail
- View rights & permissions
|SPE Member Price:||USD 5.00|
|SPE Non-Member Price:||USD 28.00|
A new technology that analyses dispersion events in seismic data is presented. The technology aims at identifying both reservoirs and also the likelihood of any presence of liquid hydrocarbons within them. This paper details the science on which the technology is based and empirical results from usage of the technology.
Presence of strong wave dispersion in seismic data has analytically and in tests been seen to correlate with high porosity and permeability formations. A lack of dispersion has conversely been seen to correlate with low porosity systems. Furthermore, a high viscosity fluid in a poro-elastic system has been seen to cause higher dispersion effects compared to brine. This permits derisking of reservoirs to identify locations with high chance of liquid hydrocarbon.
Resonance wave systems are abundant in sedimentary rock. The measurement of resonance waves permits the study of otherwise weak frequency shifts in seismic data, which can then be used to search for reservoir rock and liquid hydrocarbon.
Velocity dispersion and resonance wave analysis of seismic data requires carefully selected wavelet based spectral decomposition methods. Results from a commercially available technology presented in this paper have shown a need to prioritize high accuracy spectral decomposition methods that are able to identify minute dispersion events. These methods are often very computationally demanding. Therefore, those methods need to be selected that ensure highest accuracy while optimizing for speed.
A dispersive event occurs when an incoming P-wave propagates through a heterogeneous porous media due to mesoscopic flow. Dispersivity contributions may also stem from localized effects such as Krauklis waves. The level of dispersivity has in models and field tests been identified as a function of the reservoir porosity, permeability and fluid viscosity. Empirical results from the technology presented here, suggest the ability to identify reservoirs and frequently also their fluid content using dispersion analysis of seismic data.
Case study results using the commercial technology are presented over both discovery and dry wells in Norway and Oman. The results show how new insights into poro-elastic lithology can be provided and also the technology's potential to contribute to an improved overall prospect derisking and field delineation with respect to fluid content.
The technology demonstrates the ability to extract additional information from seismic data sets and thereby further the geological and geophysical subsurface interpretation and modelling.
|File Size||1 MB||Number of Pages||12|
Batzle, M., Han D -h. and Castagna, J. 1996. Attenuation and velocity dispersion at seismic frequencies. SEG-1996-1687. https://doi.org/10.1190/1.1826453
Biot, M. A. 1956. Theory of propagation of elastic waves in fluid-saturated porous solid: I. Low-frequency range J. Acoust. Soc. Am. 28: 168–178. https://doi.org/10.1121/1.1908239
Biot, M. A. 1956. Theory of propagation of elastic waves in a fluid saturated porous solid, II, Higher frequency range: J. Acoust. Soc. Am. 28: 179–l91. https://10.1121/1.1908241
Boitnott, G. N., Broadhead, M. K. and Keho, T. H. 2011. Laboratory measurements of modulus dispersion in sandstone at seismic frequencies. SEG-2011-2236. https://doi.org/10.1190/1.3627653
Brennan, B. J. and Stacey, F. D. 1977. Frequency dependence of elasticity of rock – test of seismic velocity dispersion. Nature, 268: 220–222. https://doi.org/10.1038/268220a0
Cao, J., Yue, Y., Zhang K. 2015. Subsurface Channel Detection Using Color Blending of Seismic Attribute Volumes. Int. J. of Signal Proc., Image Proc. and Pattern Recognition. 8 (12): 157–170. http://dx.doi.org/10.14257/ijsip.2015.8.12.16
Carcione, J. M. and Picotti, S. 2006. P-wave seismic attenuation by slow wave diffusion: effects of inhomogeneous rock properties. Geophysics, 71: O1–O8. https://doi.org/10.1190/1.2194512
Castagna, J. P., Sun, S. and Wu, S. R. 2003. Instantaneous spectral analysis: Detection of low-frequency shadows associated with hydrocarbons. The Leading Edge. 22: 120–127. https://10.1190/1.1559038
Dashti, H. H. and Riazi, M. R. 2014. Acoustic velocities in petroleum fluids: Measurement and prediction. Journal of Petroleum Science and Engineering. 124: 94–104. https://10.1016/j.petrol.2014.10.013
Ferrazzini, V. and Aki, K. 1987. Slow waves trapped in a fluid-filled infinite crack: Implication for volcanic tremor. 92 (B9): 9215–9223. https://doi.org/10.1029/JB092iB09p09215
Goloshubin, G. M., Korneev V. A., Silin, D. B. 2006. Reservoir imaging using low frequencies of seismic reflections. The Leading Edge. 25: 527–531. https://escholarship.org/uc/item/1bz9r3q1
Gurevich, B. and Lopatnikov, S. L. 1995. Velocity and attenuation of elastic waves in finely layered porous rocks. Geophysical Journal International. 121 (3): 933–947. https://doi.org/10.1111/j.1365-246X.1995.tb06449.x
Gurevich, B. and Makarynska, D. 2012. Rigorous bounds for seismic dispersion and attenuation due to wave-induced fluid flow in porous rocks. Geophysics. 77 (6): L45 - L51. https://doi.org/10.1190/geo2012-0039.1
Korneev, V. A. 2008. Slow waves in fractures filled with viscous fluid. Geophysics. 73 (1): N1–N7. http://dx.doi.org/10.1190/1.2802174
Korneev, V. A., Danilovskaya, L., Nakagawa, S. 2014. Krauklis wave in a trilayer. Geophysics. 79 (4): L33–L39. https://10.1190/geo2013-0216.1
Korneev, V. A., Goloshubin, G. M., Daley, T. V. 2004. Seismic low-frequency effects in monitoring fluid-saturated reservoirs. Geophysics. 69: 522–532. https://10.1190/1.1707072
Li, X-P. 1997. Dispersion Removal from Seismic Signals by Frequency Rescaling. SEG-1997-1147. https://doi.org/10.1190/1.1885596
Liner, C. L. 2008. A column on the history and culture of geophysics and science in general. The Leading Edge. 27: 1300–1302. https://doi.org/10.1190/1.2996540
Liner, C. L. 2012. Elements of Seismic Dispersion: A Somewhat Practical Guide to Frequency-dependent Phenomena, SEG Distinguished Instructor Series, 15: 1–22. https://doi.org/10.1190/1.9781560802952
Liu W., Cao S. and Chen Y. 2016. Applications of variational mode decomposition in seismic time-frequency analysis. Geophysics. 81 (5): V365–V378. https://doi.org/10.1190/geo2015-0489.1
Lu, Z-H., Zhang Z-H. and Gu, J-N. 2018. Analysis on the Synthetic Seismograms of Seismic Wave Caused by Low Frequency Sound Source in Shallow Sea with Porous Seabed. Journal of Theoretical and Computational Acoustics. 26 (4): 1850001 1–15. https://doi.org/10.1142/S2591728518500019
Müller, T. M., Lambert, G. and Gurevich, B. 2007. Dynamic permeability of porous rocks and its seismic signatures. Geophysics. 72 (5): E149–E158. https://doi.org/10.1190/1.2749571
Müller, T. M., Toms-Stewart, J., Wenzlau, F. 2008. Velocity-saturation relation for partially saturated rocks with fractal pore fluid distribution. Geophys. Res. Lett. 26: L09306. http://dx.doi.org/10.1190/1.3073007
Müller, T. M., Gurevich, B. and Lebedev, M. 2010. Seismic wave attenuation and dispersion resulting from wave-induced flow in porous rocks — A review. Geophysics. 75 (5): A147–A164. https://doi.org/10.1190/1.3463417
Murphy, W. F. 1982. Effects of partial water saturation on attenuation in Massilon sandstone and Vycor porous glass: Journal of the Acoustical Society of America. 71: 1458–1468. https://doi.org/10.1121/1.387843
Pride, S. R., Berryman, J. G. and Harris, J. M. 2004. Seismic attenuation due to wave induced flow. J. Geophys. Res. 109: B01201. https://doi.org/10.1029/2003JB002639
Rubino, G. J., Ravazzoli, C. L. and Santos, J. E. 2009. Equivalent viscoelastic solids for heterogeneous fluid-saturated porous rocks. Geophysics. 74 (1): N1. http://dx.doi.org/10.1190/1.3008544
Rubino, G. J., Velis, D. R. and Sacchi, M. D. 2011. Numerical analysis of wave-induced fluid flow effects on seismic data: Application to monitoring of CO2 storage at the Sleipner field. Journal of Geophysical Research. 116: B03306 https://doi.org/10.1029/2010JB007997
Sams, M. S., Neep, J. P., Worthington, M. H. 1997. The measurement of velocity dispersion and frequency-dependent intrinsic attenuation in sedimentary rocks. Geophysics. 62: 1456–1464. https://doi.org/10.1190/1.1444249
Sidorovskaia, N. A., Lockard, E. S and Lawrence, M. 1999. Velocity Dispersion as a Tool for Reservoir Imaging. SPE-53886-MS. https://doi.org/10.2118/53886-MS
Spencer, J. W. 1981. Stress relaxations at low frequencies in fluid-saturated rocks: Attenuation and modulus dispersion. J. Geophys. Res., 86: 1803–l812. https://doi.org/10.1029/JB086iB03p01803
Sun, L. F. and Milkereit, B. 2006. Velocity dispersion in Vibroseis VSP data. SEG-2006-3506. https://doi.org/10.1190/1.2370264
Toms-Stewart, J., Müller T. M., Gurevich, B., 2009. Geophysics. 74 (2): 1MA–Z35. https://doi.org/10.1190/1.3073007
Xue, Y., Cao, J. and Tian, R. 2013. A comparative study on hydrocarbon detection using three EMD-based time-frequency analysis methods. Journal of Applied Geophysics, 89: 108–115. https://doi.org/10.1016/j.jappgeo.2012.11.015