Advanced Methods of Joint Inversion and Fusion of Multiphysics Data
Different physical or geophysical methods provide information about distinctive physical properties of the objects, e.g., rock formations and mineralization. In many cases, this information is mutually complementary, which makes it natural for consideration in a joint inversion of the multiphysics d...
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| Coauteur: | |
| Formaat: | Elektronisch E-boek |
| Taal: | Engels |
| Gepubliceerd in: |
Singapore :
Springer Nature Singapore : Imprint: Springer,
2023.
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| Editie: | 1st ed. 2023. |
| Reeks: | Advances in Geological Science,
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| Onderwerpen: | |
| Online toegang: | https://doi.org/10.1007/978-981-99-6722-3 |
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Inhoudsopgave:
- Introduction to inversion theory
- Elements of probability theory
- Vector spaces of models and data
- Principles of regularization theory
- Linear inverse problems
- Probabilistic methods of inverse problem solution
- Gradient-type methods of non-linear inversion
- Joint inversion based on analytical and statistical relationships between different physical properties
- Joint inversion based on structural similarities
- Joint focusing inversion of multiphysics data
- Joint minimum entropy inversion
- Gramian method of generalized joint inversion
- Probabilistic approach to gramian inversion
- Simultaneous processing and fusion of multiphysics data and images
- Machine learning in the context of inversion theory
- Machine learning inversion of multiphysics data
- Modeling and inversion of potential field data
- Case histories of joint inversion of gravity and magnetic data. .