"Fast" algorithm for solving some three-dimensional inverse problems of magnetometry
Matematičeskoe modelirovanie, Tome 36 (2024) no. 1, pp. 41-58.

Voir la notice de l'article provenant de la source Math-Net.Ru

Typical three-dimensional inverse problems of magnetic prospecting are considered, namely: determination of the vector density of magnetic dipoles in the studied area of the earth's crust from the components of the vector (and/or gradient tensor) of magnetic induction measured on the surface. These problems, being, as a rule, ill-posed, can be solved by standard regularization methods. However, for such a solution on sufficiently detailed grids, significant computing resources (computing clusters, supercomputers, etc.) are required to solve the problem in minutes. The article proposes a new "fast" regularizing algorithm for solving such three-dimensional problems, which makes it possible to obtain their approximate solution on a personal computer of average performance in tens of seconds or in a few minutes. In addition, the approach used allows us to calculate an aposteriori error estimate of the found solution in a comparable time, and this makes it possible to evaluate the quality of the solution when interpreting the results. Algorithms for solving the inverse problem and a-posteriori error estimation for found solutions are tested in solving model inverse problems and used in the processing of experimental data.
Keywords: magnetic prospecting, theree-dimensional inverse ill-posed problems, fast solution algorithm, a-posteriori error estimate.
@article{MM_2024_36_1_a3,
     author = {A. S. Leonov and D. V. Lukyanenko and A. G. Yagola},
     title = {"Fast" algorithm for solving some three-dimensional inverse problems of magnetometry},
     journal = {Matemati\v{c}eskoe modelirovanie},
     pages = {41--58},
     publisher = {mathdoc},
     volume = {36},
     number = {1},
     year = {2024},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/MM_2024_36_1_a3/}
}
TY  - JOUR
AU  - A. S. Leonov
AU  - D. V. Lukyanenko
AU  - A. G. Yagola
TI  - "Fast" algorithm for solving some three-dimensional inverse problems of magnetometry
JO  - Matematičeskoe modelirovanie
PY  - 2024
SP  - 41
EP  - 58
VL  - 36
IS  - 1
PB  - mathdoc
UR  - http://geodesic.mathdoc.fr/item/MM_2024_36_1_a3/
LA  - ru
ID  - MM_2024_36_1_a3
ER  - 
%0 Journal Article
%A A. S. Leonov
%A D. V. Lukyanenko
%A A. G. Yagola
%T "Fast" algorithm for solving some three-dimensional inverse problems of magnetometry
%J Matematičeskoe modelirovanie
%D 2024
%P 41-58
%V 36
%N 1
%I mathdoc
%U http://geodesic.mathdoc.fr/item/MM_2024_36_1_a3/
%G ru
%F MM_2024_36_1_a3
A. S. Leonov; D. V. Lukyanenko; A. G. Yagola. "Fast" algorithm for solving some three-dimensional inverse problems of magnetometry. Matematičeskoe modelirovanie, Tome 36 (2024) no. 1, pp. 41-58. http://geodesic.mathdoc.fr/item/MM_2024_36_1_a3/

[1] P. W. Schmidt, D. A. Clark, K. E. Leslie, M. Bick, D. L. Tilbrook, C. P. Foley, “GETMAG: a SQUID magnetic tensor gradiometer for mineral and oil exploration”, Exploration Geophysics, 35:4 (2004), 297–305 | DOI

[2] M. S. Zhdanov, H. Z. Cai, G. A. Wilson, “3D inversion of SQUID magnetic tensor data”, Journal of Geology and Geosciences, 1 (2012), 1000104

[3] M. Schiffler, M. Queitsch, R. Stolz, A. Chwala, W. Krech, H. G. Meyer, N. Kukowski, “Calibration of SQUID vector magnetometers in full tensor gradiometry systems”, Geophysical Journal International, 198:2 (2014), 954–964 | DOI

[4] O. Portniaguine, M. S. Zhdanov, “Focusing geophysical inversion images”, Geophysics, 64:3 (1999), 874–887 | DOI

[5] O. Portniaguine, M. S. Zhdanov, “3-D magnetic inversion with data compression and image focusing”, Geophysics, 67:5 (2002), 1532–1541 | DOI

[6] A. Pignatelli, I. Nicolosi, M. Chiappini, “An alternative 3D inversion method for magnetic anomalies with depth resolution”, Annals of Geophysics, 49:4/5 (2006), 1021–1027

[7] D. V. Lukyanenko, A. G. Yagola, “Some methods for solving of 3d inverse problem of magnetometry”, Eurasian J. of Mathematical and Computer Applications, 4:3 (2016), 4–14 | DOI | MR

[8] Y. Wang, D. Lukyanenko, A. Yagola, “Magnetic parameters inversion method with full tensor gradient data”, Inverse Problems and Imaging, 13:4 (2019), 745–754 | DOI | MR | Zbl

[9] V. K. Ivanov, V. V. Vasin, V. P. Tanana, Teoriia lineinykh nekorrektnykh zadach i ee prilozheniia, Nauka, M., 1978

[10] A. S. Leonov, “Reshenie nekorrektno postavlennykh obratnykh zadach”, Ocherk teorii, prakticheskie algoritmy i demonstratsii v MATLAB, 2010 (2013), Librokom, M.

[11] Y. F. Wang, I. E. Stepanova, V. N. Titarenko, A. G. Yagola, Inverse Problems in Geophysics and Solution Methods, Higher Education Press, Beijing, 2011

[12] A. S. Leonov, “Extra-optimal methods for solving ill-posed problems”, J. Inverse and III-posed Probl., 20:5-6 (2012), 637–665 | DOI | MR | Zbl

[13] M. S. Zhdanov, Integral Transforms in Geophysics, Springer, Berlin, 1988 | MR | MR

[14] A. N. Tikhonov, A. V. Goncharsky, V. V. Stepanov, A. G. Yagola, Numerical methods for the solution of ill-posed problems, Kluwer, Dordrecht, 1995 | MR | Zbl

[15] A. N. Tikhonov, A. S. Leonov, A. G. Yagola, Nelineinye nekorrektnye zadachi, Nauka, M., 1995; Второе изд., Курс, М., 2017; A. N. Tikhonov, A. S. Leonov, A. G. Yagola, Nonlinear ill-posed problems, v. 1, 2, Chapman and Hall, London, 1998 | MR | Zbl

[16] A. B. Bakushinsky, A. S. Leonov, “Fast numerical method of solving 3D coefficient inverse problem for wave equation with integral data”, J. of Inverse and Ill-Posed Problems, 26:4 (2018), 477–492 | DOI | MR | Zbl

[17] A. B. Bakushinskii, A. S. Leonov, “Low-cost numerical method for solving a coefficient inverse problem for the wave equation in three-dimensional space”, Comput. Math. Math. Phys., 58:4 (2018), 548–561 | DOI | MR | Zbl

[18] H. W. Engl, M. Hanke, A. Neubauer, Regularization of Inverse Problems, Kluwer, Dordrecht, 1996 | MR | Zbl

[19] A. Bakushinsky, A. Goncharsky, Ill-Posed Problems: Theory and Applications, Kluwer, Dordrecht, 1994 | MR

[20] A. B. Bakushinsky, M. Yu. Kokurin, Iterative methods for approximate solution of inverse problems, Mathematics and Its Applications, Springer, Dordrecht, 2004 | MR | Zbl

[21] K. Yu. Dorofeev, V. N. Titarenko, A. G. Yagola, “Algorithms for constructing a posteriori errors of solutions to ill-posed problems”, Comput. Math. Math. Phys., 43:1 (2003), 10–23 | MR

[22] A. S. Leonov, “A posteriori accuracy estimations of solutions of ill-posed inverse problems and extra-optimal regularizing algorithms for their solution”, Num. Anal. Appl., 5:1 (2012), 68–83 | DOI | MR | Zbl

[23] A. S. Leonov, “Effective algorithms for computing global and local posterior error estimates of solutions to linear ill-posed problems”, Russian Math. (Iz. VUZ), 64:2 (2020), 26–34 | DOI | MR | MR | Zbl