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Fast Algorithm for Solving Some Three-Dimensional Inverse Problems of Magnetometry
Typical three-dimensional inverse problems of magnetic prospecting are considered: 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...
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Published in: | Mathematical models and computer simulations 2024, Vol.16 (3), p.352-363 |
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Main Authors: | , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites |
Online Access: | Get full text |
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Summary: | Typical three-dimensional inverse problems of magnetic prospecting are considered: 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 an 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 a posteriori 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 the solutions found are tested in solving model inverse problems and used in the processing of experimental data. |
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ISSN: | 2070-0482 2070-0490 |
DOI: | 10.1134/S2070048224700030 |