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Shear wave velocity prediction using seismic attributes and well log data

Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Formation’s properties can be estimated indirectly using joint analysis of compressional and shear wave velocities. Shear wave data is not usually acquired during well logging, which is most likely for cost saving purposes. Even if shear data is available, the logging programs provide only sparsely sampled one-dimensional measurements: this information is inadequate to estimate reservoir rock properties. Thus, if the shear wave data can be obtained using seismic methods, the results can be used across the field to estimate reservoir properties. The aim of this paper is to use seismic attributes for prediction of shear wave velocity in a field located in southern part of Iran. Independent component analysis (ICA) was used to select the most relevant attributes to shear velocity data. Considering the nonlinear relationship between seismic attributes and shear wave velocity, multi-layer feed forward neural network was used for prediction of shear wave velocity and promising results were presented.
Czasopismo
Rocznik
Strony
818--848
Opis fizyczny
Bibliogr. 22 poz.
Twórcy
autor
  • Department of Mining, Petroleum and Geophysics, Shahrood University of Technology, Shahrood, Iran, Raoof.Gholami@Gmail.com
  • Department of Mining, Petroleum and Geophysics, Shahrood University of Technology, Shahrood, Iran
autor
  • Department of Petroleum Engineering, Curtin University, Perth, Australia
autor
  • Petroleum Geology, Tehran, Iran
Bibliografia
  • 1.Ameen, M.S., B.G.D. Smart, J.M. Somerville, S. Hammilton, and N.A. Naji (2009), Predicting rock mechanical properties of carbonates from wireline logs (A case study: Arab-D reservoir, Ghawar field, Saudi Arabia), Mar. Petrol. Geol. 26, 4, 430-444, DOI: 10.1016/j.marpetgeo.2009.01.017.
  • 2.Barnes, A.E. (1997), Genetic classification of complex seismic trace attributes. In: Proc. 67th Annual Meeting, Society of Exploration Geophysicists, 2-7 November 1997, Dallas, USA, Conf. paper SEG-1997-1151, 1151-1154.
  • 3.Barnes, A.E. (2000), Attributes for automating seismic facies analysis. In: Proc. 70th Annual Meeting, Society of Exploration Geophysicists, 6-11 August 2000, Calgary, Canada, Conf. paper SEG-2000-0553, 553-556.
  • 4.Bell, A.J., and T.J. Sejnowski (1997), The “independent components” of natural scenes are edge filters, Vision Res. 37, 23, 3327-3338, DOI: 10.1016/S0042-6989(97)00121-1.
  • 5.Birch, F. (1960), The velocity of compressional waves in rocks to 10 kbars – Part 1, J. Geophys. Res. 65, 4, 1083-1102, DOI: 10.1029/JZ065i004p01083.
  • 6.Brocher, T.M. (2005), Empirical relations between elastic wavespeeds and density in the earth’s crust, Bull. Seismol. Soc. Am. 95, 6, 2081-2092, DOI: 10.1785/0120050077.
  • 7.Brocher, T.M. (2008), Key elements of regional seismic velocity models for long period ground motion simulations, J. Seismol. 12, 2, 217-221, DOI:10.1007/s10950-007-9061-3.
  • 8.Brown, A.R. (1996), Seismic attributes and their classification, The Leading Edge 15, 10, 1090-1090, DOI: 10.1190/1.1437208.
  • 9.Brown, A.R. (2004), Interpretation of Three-Dimensional Seismic Data, 6th ed., AAPG Memoir 42, American Association of Petroleum Geologists, Tulsa.
  • 10.Burlini, L., and D.M. Fountain (1993), Seismic anisotropy of metapelites from the Ivrea-Verbano zone and Serie dei Laghi (northern Italy), Phys. Earth Planet. In. 78, 3-4, 301-317, DOI: 10.1016/0031-9201(93)90162-3.
  • 11.Carroll, R.D. (1969), The determination of the acoustic parameters of volcanic rocks from compressional velocity measurements, Int. J. Rock Mech. Min. 6, 6, 557-579, DOI: 10.1016/0148-9062(69)90022-9.
  • 12.Castagna, J.P., M.L. Batzle, and T.K. Kan (1993), Rock physics – The link between rock properties and avo response. In: J.P. Castagna and M.M. Backus (eds.), Offset-Dependent Reflectivity – Theory and Practice of AVO Analysis, Society of Exploration Geophysicists, 135-171.
  • 13.Chao, W., Ch. Mian, and J. Yan (2009), A prediction method of borehole stability based on seismic attribute technology, J. Petrol. Sci. Eng. 65, 3-4, 208-216, DOI: 10.1016/j.petrol.2008.12.033.
  • 14.Chen, Q., and S. Sidney (1997), Seismic attribute technology for reservoir forecasting and monitoring, The Leading Edge 16, 5, 445-448, DOI: 10.1190/1.1437657.
  • 15.Christensen, N.I. (1974), Compressional wave velocities in possible mantle rocks to pressures of 30 kilobars, J. Geophys. Res. 79, 2, 407-412, DOI: 10.1029/JB079i002p00407.
  • 16.Comon, P. (1994), Independent component analysis, a new concept? Signal Process. 36, 3, 287-314, DOI: 10.1016/0165-1684(94)90029-9.
  • 17.Cosentino, L. (2001), Integrated Reservoir Studies, Editions Technip, Paris. Eberhart-Phillips, D., D.-H. Han, and M.D. Zoback (1989), Empirical relationships among seismic velocity, effective pressure, porosity, and clay content in sandstone, Geophysics 54, 1, 82-89, DOI: 10.1190/1.1442580.
  • 18.Gassmann, F. (1951), Elasticity of porous media, Vierteljahrsschrift der NaturforschendennGesellschaft in Zürich 96, 1, 1-23 (in German).
  • 19.Greenberg, M.L., and J.P. Castagna (1992), Shear-wave velocity estimation in porous rocks: theoretical formulation, preliminary verification and applications, Geophys. Prospect. 40, 2, 195-209, DOI: 10.1111/j.1365-2478.1992.tb00371.x.
  • 20.Hampson, D.P., J.S. Schuelke, and J.A. Quirein (2001), Use of multiattribute transforms to predict log properties from seismic data, Geophysics 66, 1, 220-236, DOI: 10.1190/1.1444899.
  • 21.Hart, B.S., and R.S. Balch (2000), Approaches to defining reservoir physical properties from 3-D seismic attributes with limited well control: An example from the Jurassic Smackover Formation, Alabama, Geophysics 65, 2, 368-376, DO Hyvärinen, A. (1999a), Survey on independent component analysis, Neural. Comput. Surv. 2, 94-128.
  • 22.Hyvärinen, A. (1999b), Fast and robust fixed-point algorithms for independent component analysis, IEEE Trans. Neural Networks. 10, 3, 626-634, DOI:10.1109/72.761722.I: 10.1190/1.1444732.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-ea1540b5-cc53-4a17-86cf-c701cf616f56
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