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Abstract

Summary

We have developed a novel probabilistic approach to the joint inversion of multi-modal geophysical data based on the Gramian constraint. The multi-modal geophysical survey is the most effective technique for geophysical exploration because different physical data reflect distinct physical properties of the different components of the geological system. The joint inversion of multi-modal data can produce enhanced subsurface images of the physical property distributions, which enhances our ability to explore natural resources. One effective method of joint inversion is based on the Gramian constraint. This technique enforces the relationships between different model parameters during the inversion process. We demonstrate that the Gramian can be interpreted as a determinant of the covariance matrix between different physical models representing subsurface geology in the framework of the probabilistic approach to inverse theory. This interpretation enables us to use all the power of the modern probability theory and statistics in developing new methods for the joint inversion of multi-modal geophysical data. We apply the developed joint inversion methodology to inversion of gravity gradiometry and magnetic data in the Nordkapp Basin, Barents Sea to image salt diapirs.

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/content/papers/10.3997/2214-4609.202310065
2023-06-05
2026-01-20

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References

  1. Cuma, M. and Zhdanov, M. S. [2014] Massively parallel regularized 3D inversion of potential fields on CPUs and GPUs. Computers and Geosciences, 62, 80–87.
     [Google Scholar]
  2. Hokstad, K., Fotland, B., Mackenzie, G., Antonsdottir, V., Foss, S., Stadtler, C., et al. [2011] Joint imaging of geophysical data: Case history from the Nordkapp Basin, Barents Sea. SEG Technical Program Expanded Abstracts, 1098–1102.
     [Google Scholar]
  3. Hoversten, G. M., Cassassuce, F., Gaskeripova, E., Newman, G. A., Chen, J., Rubin, Y., et al. [2006] Direct reservoir parameter estimation using joint inversion of marine seismic AVA and CSEM data. Geophysics, 71, –C13.
     [Google Scholar]
  4. Jorgensen, M. and Zhdanov, M. S. [2021] Recovering magnetization of rock formations by jointly inverting airborne gravity gradiometry and total magnetic intensity data. Minerals, 11(4), 366.
     [Google Scholar]
  5. Moorkamp, M., Lelievre, P., Linde, N. and Khan, A. [2016] Integrated imaging of the Earth: theory and applications. Wiley.
     [Google Scholar]
  6. Paoletti, V., Milano, M., Baniamerian, J. and Fedi, M. [2020] Magnetic field imaging of salt structures at Nordkapp Basin, Barents Sea. Geophysical Research Letters, 47(18).
     [Google Scholar]
  7. Tao, M., Jorgensen, M. and Zhdanov, M. S. [2021] Mapping the salt structures from magnetic and gravity gradiometry data in Nordkapp Basin, Barents Sea. SEG/AAPG International Meeting for Applied Geoscience & Energy, Houston, Texas, USA, 874–878.
     [Google Scholar]
  8. Tarantola, A. [1987] Inverse problem theory. Elsevier.
     [Google Scholar]
  9. Tu, X. and Zhdanov, M. S. [2022] Joint focusing inversion of marine controlled-source electromagnetic and full tensor gravity gradiometry data. Geophysics87, K35–K47.
     [Google Scholar]
  10. Zhdanov, M. S., Gribenko, A. V. and Wilson, G. [2012] Generalized joint inversion of multimodal geophysical data using Gramian constraints. Geophysical Research Letters, 39, L09301.
     [Google Scholar]
  11. Zhdanov, M. S. [2015] Inverse theory and applications in geophysics. Elsevier.
     [Google Scholar]
/content/papers/10.3997/2214-4609.202310065
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Joint Inversion of Gravity Gradiometry and Magnetic Data in the Barents Sea using the Probabilistic Gramian
Conference Proceedings 2023, 1 (2023); https://doi.org/10.3997/2214-4609.202310065
/content/papers/10.3997/2214-4609.202310065
/content/papers/10.3997/2214-4609.202310065
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