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- Title
Applicability of artificial intelligence to reservoir induced earthquakes.
- Authors
Samui, Pijush; Kim, Dookie
- Abstract
This paper proposes to use least square support vector machine (LSSVM) and relevance vector machine (RVM) for prediction of the magnitude ( M) of induced earthquakes based on reservoir parameters. Comprehensive parameter ( E) and maximum reservoir depth ( H) are used as input variables of the LSSVM and RVM. The output of the LSSVM and RVM is M. Equations have been presented based on the developed LSSVM and RVM. The developed RVM also gives variance of the predicted M. A comparative study has been carried out between the developed LSSVM, RVM, artificial neural network (ANN), and linear regression models. Finally, the results demonstrate the effectiveness and efficiency of the LSSVM and RVM models.
- Subjects
LEAST squares; RESERVOIR-triggered seismicity; INDUCED seismicity; COMPARATIVE studies; ANALYSIS of variance; ARTIFICIAL neural networks
- Publication
Acta Geophysica, 2014, Vol 62, Issue 3, p608
- ISSN
1895-6572
- Publication type
Article
- DOI
10.2478/s11600-014-0201-1