1887
Volume 71 Number 9
  • E-ISSN: 1365-2478

Abstract

Abstract

Litho‐prediction is a non‐unique process that requires more than integrated techniques to reinforce the final results and harmonize hydrocarbon probability. Consequently, integrated procedures have been started with log data of the Mishrif formation in different site locations and involve petrophysics and rock physics analyses altogether to evaluate the general situation of the formation. In the second stage, we performed seismic inversion for 3D seismic data in the Kumaite and Dhafriyah oil fields. A brand‐new technique called pseudo–post‐stack simultaneous inversion has been used to calculate all the elastic engineering properties of the seismic cube. This method is performed by utilizing a real genetic inversion model that would be used to calibrate a low‐frequency model of simultaneous inversion to enhance the resolution and event isolation of the final inverted cube to identify reservoir characterization. The final output then is used to perform quantitative analysis and determine the productive layers within the area of interest. Density–velocity analysis also plays an extraordinary role in establishing the main relationship between different elastic parameters. Finally, by using the local equation and global density–velocity equations, different velocities of carbonate succession have been calculated.

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2023-11-10
2025-03-16
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References

  1. Abe, S.J., Olowokere, M.T. & Enikanselu, P.A. (2018) Development of model for predicting elastic parameters in ‘bright’ field, Niger Delta using rock physics analysis. NRIAG Journal of Astronomy and Geophysics, 7(2), 264–278.
    [Google Scholar]
  2. Ahmed, Z. (2014) Pre‐stack simultaneous inversion of 3D seismic data for velocity attributes to delineate channel sand reservoir. International Journal of Emerging Technology and Advanced Engineering., 4, 69–78.
    [Google Scholar]
  3. Al‐Chalabi, M. (2014) Principles of seismic velocities and time‐to‐depth conversion. Anthropocene, 26, 488.
    [Google Scholar]
  4. Ali, M., Ma, H., Pan, H., Ashraf, U. & Jiang, R. (2020) Building a rock physics model for the formation evaluation of the Lower Goru sand reservoir of the Southern Indus Basin in Pakistan. Journal of Petroleum Science and Engineering, 194, 107461.
    [Google Scholar]
  5. Al‐Sakini, J.A. (1992) Summary of petroleum geology of Iraq and the Middle East. Kirkuk, Iraq: Northern Oil Company Press (Naft‐Al Shamal Co.).
    [Google Scholar]
  6. Amigun, J.O. & Odole, O.A. (2013) Petrophysical properties evaluation for reservoir characterisation of Seyi oil field (Niger‐Delta). International Journal of Innovation and Applied Studies, 3(3), 756–773.
    [Google Scholar]
  7. Avseth, P., Mukerji, T. & Mavko, G. (2010) Quantitative seismic interpretation: applying rock physics tools to reduce interpretation risk. Cambridge: Cambridge University Press.
    [Google Scholar]
  8. Avseth, P.A. & Odegaard, E. (2004) Well log and seismic data analysis using rock physics templates. First Break, 22(10), 37–43.
    [Google Scholar]
  9. Avseth, P. & Veggeland, T. (2015) Seismic screening of rock stiffness and fluid softening using rock physics attributes. Interpretation, 3(4), SAE85–SAE93.
    [Google Scholar]
  10. Cannon, S. (2015) Petrophysics: a practical guide. Hoboken, NJ: John Wiley & Sons.
    [Google Scholar]
  11. Castagna, J.P. & Backus, M.M.e. (1993) Offset‐dependent reflectivity—theory and practice of AVO analysis. Houston, TX: Society of Exploration Geophysicists.
    [Google Scholar]
  12. Chopra, S. & Castagna, J.P. (2014) AVO. Investigations in Geophysics, 16, 122.
    [Google Scholar]
  13. Christensen, N.I. & Mooney, W.D. (1995) Seismic velocity structure and composition of the continental crust: a global view. Journal of Geophysical Research: Solid Earth, 100(B6), 9761–9788.
    [Google Scholar]
  14. Darwin, C. & Bynum, W.F. (2009) The origin of species by means of natural selection: or, the preservation of favored races in the struggle for life. New York: AL Burt.
    [Google Scholar]
  15. Dvorkin, J., Gutiérrez, M.A. & Grana, D. (2014) Seismic reflections of rock properties. Cambridge: Cambridge University Press.
    [Google Scholar]
  16. Dvorkin, J., Gutiérrez, M.A. & Nur, A. (2002) On the universality of diagenetic trends. The Leading Edge, 21(1), 40–43.
    [Google Scholar]
  17. Eberli, G.P., Baechle, G.T., Anselmetti, F.S. & Incze, M.L. (2003) Factors controlling elastic properties in carbonate sediments and rocks. The Leading Edge, 22(7), 654–660.
    [Google Scholar]
  18. Evenick, J. (2008) Introduction to well logs and subsurface maps. Tulsa, OK: PennWell.
    [Google Scholar]
  19. Gardner, G.H.F., Gardner, L.W. & Gregory, A.R. (1974) Formation velocity and density: the diagnostic basics for stratigraphic traps. Geophysics, 39(6), 770–780.
    [Google Scholar]
  20. Gassmann, F. (1951) Elastic waves through a packing of spheres. Geophysics, 16(4), 673–685.
    [Google Scholar]
  21. Geertsma, J. & Smit, D.C. (1961) Some aspects of elastic wave propagation in fluid‐saturated porous solids. Geophysics, 26(2), 169–181.
    [Google Scholar]
  22. Gercek, H. (2007) Poisson's ratio values for rocks. International Journal of Rock Mechanics and Mining Sciences, 44(1), 1–13.
    [Google Scholar]
  23. Glover, P.W. (2000) Petrophysics. UK: University of Aberdeen.
    [Google Scholar]
  24. Godfrey, N.J., Beaudoin, B.C. & Klemperer, S.L. (1997) Ophiolitic basement to the Great Valley forearc basin, California, from seismic and gravity data: implications for crustal growth at the North American continental margin. Geological Society of America Bulletin, 109(12), 1536–1562.
    [Google Scholar]
  25. Golikov, P., Avseth, P., Stovas, A. & Bachrach, R. (2013) Rock physics interpretation of heterogeneous and anisotropic turbidite reservoirs. Geophysical Prospecting, 61(2), 448–457.
    [Google Scholar]
  26. Goodway, B., Chen, T. & Downton, J. (1997) Improved AVO fluid detection and lithology discrimination using Lamé petrophysical parameters; ‘λρ’, ‘μρ’, and ‘λ/μ fluid stack’, from P and S inversions. SEG Technical Program Expanded Abstracts, 183–186.
    [Google Scholar]
  27. Hampson, D., Todorov, T. & Russell, B. (2000) Using multi‐attribute transforms to predict log properties from seismic data. Exploration Geophysics, 31(3), 481–487.
    [Google Scholar]
  28. Hampson, D.P., Russell, B.H. & Bankhead, B. (2005) Simultaneous inversion of pre‐stack seismic data. SEG Technical Program Expanded Abstracts, 1633–1637.
    [Google Scholar]
  29. Hampson, D.P., Russell, B.H. & Bankhead, B. (2005) Simultaneous inversion of pre‐stack seismic data. SEG Technical Program Expanded Abstracts, 1633–1637.
    [Google Scholar]
  30. Hejazi, F., Toloue, I., Jaafar, M.S. & Noorzaei, J. (2013) Optimization of earthquake energy dissipation system by genetic algorithm. Computer‐Aided Civil and Infrastructure Engineering, 28(10), 796–810.
    [Google Scholar]
  31. Jassim, S.Z. & Goff, J.C. (2006) Geology of Iraq. Prague: Dolin.
    [Google Scholar]
  32. Jiang, L. & Castagna, J.P. (2020) On the rock physics basis for seismic hydrocarbon detection. Geophysics, 85(1), MR25–MR35.
    [Google Scholar]
  33. Liu, Z. & Sun, S.Z. (2015) The differential Kuster–Toksöz rock physics model for predicting S‐wave velocity. Journal of geophysics and engineering, 12(5), 839–848.
    [Google Scholar]
  34. Lowrie, W. (2011) A student's guide to geophysical equations. Cambridge: Cambridge University Press.
    [Google Scholar]
  35. Ludwig, W.J. (1970) Seismic refraction. The Sea, 4, 53–84.
    [Google Scholar]
  36. Maurya, S.P., Singh, N.P. & Singh, K.H. (2019) Use of genetic algorithm in reservoir characterisation from seismic data: a case study. Journal of Earth System Science, 128(5), 1–15.
    [Google Scholar]
  37. Mavko, G., Mukerji, T. & Dvorkin, J. (2020) The rock physics handbook. Cambridge: Cambridge University Press.
    [Google Scholar]
  38. Moghanloo, H.G., Riahi, M.A. & Bagheri, M. (2018) Application of simultaneous prestack inversion in reservoir facies identification. Journal of Geophysics and Engineering, 15(4), 1376–1388.
    [Google Scholar]
  39. Ogbamikhumi, A. & Igbinigie, N.S. (2020) Rock physics attribute analysis for hydrocarbon prospectivity in the Eva field onshore Niger Delta Basin. Journal of Petroleum Exploration and Production Technology, 10(8), 3127–3138.
    [Google Scholar]
  40. Padhi, A. & Mallick, S. (2013) Accurate estimation of density from the inversion of multicomponent prestack seismic waveform data using a nondominated sorting genetic algorithm. The Leading Edge, 32(1), 94–98.
    [Google Scholar]
  41. Pamungkas, A.Y., Rosid, M.S. & Haidar, M.W. (2019) Identification of hydrocarbon gas and discriminate CO2 using Lamé parameter and Batzle‐Wang model. In E3S Web of Conferences, 125, 15003. Les Ulis, France: EDP Sciences.
    [Google Scholar]
  42. Reza, M.F., Rosid, M.S. & Haidar, M.W. (2019) Carbonate reservoir characterization using simultaneous inversion in field ‘X’. In AIP Conference Proceedings (Vol. 2168(1)). College Park, MD: AIP Publishing LLC, p. 020023.
    [Google Scholar]
  43. Schön, J. (2011) Physical properties of rocks: a workbook (Vol. 8). Netherlands: Elsevier.
    [Google Scholar]
  44. Sergios Theodoridis . (2020) Machine learning. Chapter 7—Classification: a tour of the classics. Cambridge, MA: Academic Press, pp. 301–350.
    [Google Scholar]
  45. Sharland, P.R., Archer, R., Casey, D., Davies, R., Hall, S.H., Heward, A., Horbury, A. & Simmons, M. (2001) Arabian plate sequence stratigraphy (Vol. 2). Bahrain: Gulf PetroLink.
    [Google Scholar]
  46. Simm, R., Bacon, M. & Bacon, M. (2014) Seismic amplitude: an interpreter's handbook. Cambridge: Cambridge University Press.
    [Google Scholar]
  47. Taner, M.T. (2000) Attributes Revisited, Rock Solid Images, Houston, Texas. Retrieved in, 4, 102004. https://library.seg.org/doi/abs/10.1190/1.1822709
  48. Veeken, P.C.H. & Da Silva, A.M. (2004) Seismic inversion methods and some of their constraints. First Break, 22(6). https://doi.org/10.3997/1365‐2397.2004011.
    [Google Scholar]
  49. Yilmaz, Ö. (2001) Seismic data analysis: processing, inversion, and interpretation of seismic data. Houston, TX: Society of Exploration Geophysicists.
    [Google Scholar]
  50. Yoong, A.A., Almanna Lubis, L. & Ghosh, D.P. (2016) Application of simultaneous inversion method to predict the lithology and fluid distribution in “X” Field, Malay Basin. In IOP Conference Series: Earth and Environmental Science (Vol. 38(1)). Bristol, UK: IOP Publishing.
    [Google Scholar]
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