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Tytuł artykułu

Generalisation and improvement of the compact gravity inversion method

Wybrane pełne teksty z tego czasopisma
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Compact gravity inversion (CGI) is widely used to invert gravity data following the principle of minimising the volume of the causative body due to its simplicity, high efciency, and sharp-boundary inversion results. In this study, the compactness weighting function is generalised and the depth weighting function is introduced to CGI to obtain the reweighted CGI (RCGI) method. Although RCGI exhibits better fexibility than CGI, selecting an appropriate compactness factor α and depth weighting function β is difcult, and we design a parameter selection rule to search the proper α and β quantitively. Furthermore, we improve RCGI for boasting superior computational efciency by gradually eliminating the model blocks that reach the designated boundaries in the iterative algorithm of inversion. This approach is termed the reweighted and element-elimination CGI (REECGI) method. The inversion results show that both RCGI and REECGI result in better inversion accuracy than CGI, and REECGI has higher computational efciency than RCGI and CGI, which increases with the number of iterations.
Czasopismo
Rocznik
Strony
1667--1677
Opis fizyczny
Bibliogr. 28 poz.
Twórcy
autor
  • China University of Geosciences (Beijing), Beijing 100083, China
  • The First Crust Monitoring and Application Centre, China Earthquake Administration, Tianjin 300180, China
autor
  • China University of Geosciences (Beijing), Beijing 100083, China
autor
  • The First Crust Monitoring and Application Centre, China Earthquake Administration, Tianjin 300180, China
  • The First Crust Monitoring and Application Centre, China Earthquake Administration, Tianjin 300180, China
autor
  • The First Crust Monitoring and Application Centre, China Earthquake Administration, Tianjin 300180, China
  • The First Crust Monitoring and Application Centre, China Earthquake Administration, Tianjin 300180, China
Bibliografia
  • 1. Acar R, Vogel CR (1994) Analysis of total variation penalty methods. Inverse Prob 10:1217–1229
  • 2. Barbosa VCF, Silva JBC (1994) Gen Compact Gravity Invers Geophys 59(1):57–68
  • 3. Blakely RJ (1995) Potential theory in gravity and magnetic applications. Cambridge University Press, Cambridge
  • 4. Chen S, Zhang J, Shi YL (2008) Gravity inversion using the frequency characteristics of the density distribution. Appl Geophys 5(2):99–106
  • 5. Constable SC, Parker RC, Constable GG (1987) Occam’s inversion: a practical algorithm for generating smooth models from EM sounding data. Geophys 52:289–300
  • 6. Ghalehnoee MH, Ansari A, Ghorbani A (2017) Improving compact gravity inversion using new weighting functions. Geophys J Int 28(1):546–560
  • 7. Guillen A, Menichetti V (1984) Gravity and magnetic inversion with minimization of a specific functional. Geophys 49:1354–1360
  • 8. Hadamard J (1902) Sur les problèmes aux derivées partielles et leur signification physique. Princeton Univ Bull 13: 49–52. Reprinted in his Oeuvres, Centre Nat Rech Sci, Paris, 3:1099–1105
  • 9. Karaoulis K, Revil A, Minsley B et al (2014) Time-lapse gravity inversion with an active time constraint. Geophys J Int 196:748–759
  • 10. Last BJ, Kubik K (1983) Compact gravity invers Geophys 34:65–74
  • 11. Levenberg K (1944) A method for the solution of certain nonlinear problems in least squares. Q Appl Math 2:164–168
  • 12. Li YG, Oldenburg DW (1998) 3-D inversion of gravity data. Geophys 63(1):109–119
  • 13. Marquardt DW (1963) An algorithm for least squares estimation of nonlinear parameters. SIAM J 11:431–441
  • 14. Mendonca CA, Silva JBC (1994) The equivalent data concept applied to the interpolation of potential field data. Geophys 59(5):722–732
  • 15. Mendonca CA, Silva JBC (1995) Interpolation of potential field data by equivalent layer and minimum curvature: a comparative analysis. Geophys 60(2):399–407
  • 16. Menke W (1989) Geophysical data analysis: discrete inverse theory, Revised edn. Academic Press, Cambridge
  • 17. Pilkington M (1997) 3-D magnetic imaging using conjugate gradients. Geophys 62:1132–1142
  • 18. Pilkington M (2009) 3D magnetic data-space inversion with sparseness constraints. Geophys 74(1):L7–L15
  • 19. Portniaguine O, Zhdanov MS (1999) Focusing Geophys Invers Images Geophys 64(3):874–887
  • 20. Roland M, Vadim M, Dimitri K et al (2013) Gravity inversion using wavelet-based compression on parallel hybrid CPU/GPU systems: application to southwest Ghana. Geophys J Int 195:1594–1619
  • 21. Rosas-Carbajal M, Jourde K, Marteau J et al (2017) Three-dimensional density structure of La Soufrière de Guadeloupe lava dome from simultaneous muon radiographies and gravity data. Geophys Res Lett 44(13):6743–6751
  • 22. Rudin LI, Osher S, Fatemi E (1992) Nonlinear total variation-based noise removal algorithms. Phys D 60:259–268
  • 23. Silva FJS, Barbosa CF, Silva JBC (2009) 3D gravity inversion through an adaptive-learning procedure. Geophys 74(3):I9–I21
  • 24. Silva FJS, Barbosa CF, Silva JBC (2011) Adaptive learning 3D gravity inversion for salt-body imaging. Geophys 76(3):I49–I57
  • 25. Silva JBC, Barbosa VCF (2006) Interactive gravity inversion. Geophysics 71(1):J1–J9
  • 26. Smith RT, Zoltani CK, Klem GJ, Coleman MW (1991) Reconstruction of the tomographic images from sparse data sets by a new finite element maximum entropy approach. Appl Opt 30:573–582
  • 27. Williams NC (2008) Geologically-constrained UBC-GIF gravity and magnetic inversion with examples from the Agnew-Wiluna greenstone belt, Western Australia. PhD thesis, The University of British Colombia, Faculty of Geophysics
  • 28. Zhdanov MS (2015) Inverse theory and applications in geophysics. Elsevier, Amsterdam
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-38399a56-26ad-4db8-ae2e-cd20f8568cb4
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