Rapid neuronet inversion of 2D magnetotelluric data for monitoring of geoelectrical section parameters
Main Article Content
Abstract
The inverse MagnetoTelluric (MT) operator is approximated by means of the Neural Network (NN). The
methodology of the NN interpretation in classes of the geoelectrical sections described by the hundreds of parameters
is proposed. Error of the NN inversion and field misfit are evaluated. A rapid NN algorithm solving the
inverse problem and detecting changes of time-dependent dynamic parameters of the section is applied to 2D
synthetic data.
methodology of the NN interpretation in classes of the geoelectrical sections described by the hundreds of parameters
is proposed. Error of the NN inversion and field misfit are evaluated. A rapid NN algorithm solving the
inverse problem and detecting changes of time-dependent dynamic parameters of the section is applied to 2D
synthetic data.
Article Details
How to Cite
Shimelevich, M. I., Obornev, M. A. and Gavryushov, S. (2007) “Rapid neuronet inversion of 2D magnetotelluric data for monitoring of geoelectrical section parameters”, Annals of Geophysics, 50(1). doi: 10.4401/ag-3090.
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