Россия
УДК 537.67 Земной магнетизм
УДК 55 Геология. Геологические и геофизические науки
УДК 550.34 Сейсмология
УДК 550.383 Главное магнитное поле Земли
ГРНТИ 37.01 Общие вопросы геофизики
ГРНТИ 37.15 Геомагнетизм и высокие слои атмосферы
ГРНТИ 37.25 Океанология
ГРНТИ 37.31 Физика Земли
ГРНТИ 38.01 Общие вопросы геологии
ГРНТИ 36.00 ГЕОДЕЗИЯ. КАРТОГРАФИЯ
ГРНТИ 37.00 ГЕОФИЗИКА
ГРНТИ 38.00 ГЕОЛОГИЯ
ГРНТИ 39.00 ГЕОГРАФИЯ
ГРНТИ 52.00 ГОРНОЕ ДЕЛО
ОКСО 05.00.00 Науки о Земле
ББК 26 Науки о Земле
ТБК 63 Науки о Земле. Экология
BISAC SCI SCIENCE
The downward continuation of an anomalous magnetic field is used for many applications in geophysics. However, such a problem is ill-posed, so it does not have a unique and stable solution. In this paper, we propose an artificial neural network architecture for the downward continuation of the vertical component of an anomalous geomagnetic field measured in a plane at a given height. The inverse problem is solved here by a direct method: the neural network is trained to reconstruct such a distribution of the magnetic field Bdown, which after a stable upward continuation corresponds to the measured field Bup. The performance of the neural network was demonstrated using the example of an anomalous geomagnetic field obtained using the Enhanced Magnetic Model.
stray magnetic field, magnetic anomaly, untrained neural networks, inverse modeling, downward continuation
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