1887
Volume 73, Issue 6
  • E-ISSN: 1365-2478

Abstract

ABSTRACT

The transformation of elastic impedance (EI) from partial‐angle‐stacked seismic data is a crucial technique in the domains of reservoir modelling. Conventionally, EI inversion is performed on a per‐angle basis, leading to significant discrepancies in EI values across different angles, which may not accurately represent actual conditions. When the signal‐to‐noise ratio (SNR) of seismic data is low, the inverted EI tends to be unstable, resulting in poor‐quality inversion outcomes. This research proposes a novel method that allows for enabling the derivation of EI for various angles simultaneously inverted from multiple partial angle‐stack seismic datasets in one process. The aim of simultaneous inversion is to potentially ensure consistent EI results. To obtain this aim, we utilize an advanced regularization method called the Gramian constraint. Consequently, the objective function for the simultaneous inversion of multiple EIs is developed. Results from both synthetic and field data demonstrate improved stability in EI inversion, especially for the case of low SNR.

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/content/journals/10.1111/1365-2478.70056
2025-07-15
2026-02-11
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References

  1. Aster, R. C., B.Borchers, and C. H.Thurber. 2019, Parameter Estimation and Inverse Problems. 3rd ed.Elsevier Academic Press.
    [Google Scholar]
  2. CaiH., R.Kong, Z.He, et al. 2024. “Joint Inversion of Potential Field Data With Adaptive Unstructured Tetrahedral Mesh.” Geophysics89, no. 3: G45–G63.
    [Google Scholar]
  3. Connolly, P.1999. “Elastic Impedance.” Leading Edge18: 438–452.
    [Google Scholar]
  4. Dai, R., C.Yin, S.Yang, and F.Zhang. 2018. “Seismic Deconvolution and Inversion With Erratic Data.” Geophysical Prospecting66: 1684–1701.
    [Google Scholar]
  5. Gholami, A.2015. “Nonlinear Multichannel Impedance Inversion by Total‐Variation Regularization.” Geophysics80, no. 5: R217–R224.
    [Google Scholar]
  6. JiaW., Z.Zong, D.Qin, and T.Lan. 2023. “A Method for Predicting the TOC in Source Rocks Using a Machine Learning‐Based Joint Analysis of Seismic Multi‐Attributes.” Journal of Applied Geophysics216: 105143.
    [Google Scholar]
  7. Kong, R. J., X. Y.Hu, and H. Z.Cai. 2023. “Three‐Dimensional Joint Inversion of Gravity and Magnetic Data Using Gramian Constraints and Gauss‐Newton Method.” Chinese Journal of Geophysics (in Chinese)66: 3493–3513.
    [Google Scholar]
  8. Lin, W., and M. S.Zhdanov. 2019. “The Gramian Method of Joint Inversion of the Gravity Gradiometry and Seismic Data.” Pure and Applied Geophysics176: 1659–1672.
    [Google Scholar]
  9. MalovichkoM., N.Khokhlov, N.Yavich, and M. S.Zhdanov. 2020. “Incorporating Known Petrophysical Model in the Seismic Full‐Waveform Inversion Using the Gramian Constraint.” Geophysical Prospecting68: 1361–1378.
    [Google Scholar]
  10. Maurya, S. P., N. P.Singh, and K. H.Singh. 2020. Seismic Inversion Methods: A Practical Approach. Springer.
    [Google Scholar]
  11. PlakhtienkoM. P.2012. “Nonclassical Relations Between Elements of Gramian Matrices of Vector Systems of a Unitary Hilbert Space.” Journal of Mathematical Sciences181: 529–540.
    [Google Scholar]
  12. Sharifi, J., N. H.Moghaddas, G. R.Lashkaripour, A.Javaherian, and M.Mirzakhanian. 2019. “Application of Extended Elastic Impedance in Seismic Geomechanics.” Geophysics84, no. no. 3: R429–R446.
    [Google Scholar]
  13. Verwest, B., R.Masters, and A.Sena. 2000. “Elastic Impedance Inversion.” In 70th Annual International Meeting, SEG, Expanded Abstracts, 1580–1582. SEG.
  14. Wang, B. L., X. Y.Yin, and F. C.Zhang. 2006. “Lame Parameters Inversion Based on Elastic Impedance and Its Application.” Applied Geophysics3: 174–178.
    [Google Scholar]
  15. Wang, Y.2017. Seismic Inversion: Theory and Applications. Wiley Blackwell.
    [Google Scholar]
  16. Whitcombe, D. N.2002. “Elastic Impedance Normalization.” Geophysics67: 60–62.
    [Google Scholar]
  17. Whitcombe, D. N., P. A.Connolly, R. L.Reagan, and T. C.Redshaw. 2002. “Extended Elastic Impedance for Fluid and Lithology Prediction.” Geophysics67: 63–67.
    [Google Scholar]
  18. Yilmaz, O.2001. Seismic Data Analysis: Processing, Inversion, and Interpretation of Seismic Data. Society of Exploration Geophysicists.
    [Google Scholar]
  19. Zhang, F., and R.Dai. 2016. “Nonlinear Inversion of Pre‐Stack Seismic Data Using Variable Metric Method.” Journal of Applied Geophysics129: 111–125.
    [Google Scholar]
  20. Zhang, S., X.Yin, and G.Zhang. 2011. “Dispersion‐Dependent Attribute and Application in Hydrocarbon Detection.” Journal of Geophysics and Engineering8: 498–507.
    [Google Scholar]
  21. ZhdanovM. S.2015. Inverse Theory and Applications in Geophysics, 2nd ed.Elsevier.
    [Google Scholar]
  22. ZhdanovM. S.2023. Advanced Methods of Joint Inversion and Fusion of Multiphysics Data. Springer.
    [Google Scholar]
  23. ZhouH., Z.Zong, Y.Yang, and K.Luo. 2024. “In Situ Stress Prediction Method for Decoupled Overburden Pressure Undertectonic Constraints.” Journal of Geophysics and Engineering21: 738–757.
    [Google Scholar]
  24. Zong, Z., X.Yin, and G.Wu. 2016. “Frequency Dependent Elastic Impedance Inversion for Interstratified Dispersive Elastic Parameters.” Journal of Applied Geophysics131: 84–93.
    [Google Scholar]
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