Abstract
Recent advances in application of the artificial neural networks in EM induction studies are discussed. Special attention is paid to 3D reconstruction of the target macroparameters, initial resistivity model construction without prior information about 1D layering, inversion of inhomogeneous magnetotelluric (MT) data, compensation for lack of MT data by estimating the resistivity values using related proxy parameters, joint cluster analysis of the resistivity and other physical properties as well as their indirect estimation from surface EM data.
Keywords
- Artificial Neural Network
- Resistivity Image
- Resistivity Model
- Artificial Neural Network Training
- Electromagnetic Data
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Acknowledgements
The author acknowledges the Russian Basi Research Foundation (grants 11-05-00045, 11-05-12000) for support of this study.
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Spichak, V.V. (2011). Application of ANN-Based Techniques in EM Induction Studies. In: Petrovský, E., Ivers, D., Harinarayana, T., Herrero-Bervera, E. (eds) The Earth's Magnetic Interior. IAGA Special Sopron Book Series, vol 1. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-0323-0_2
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