Attaining information of the source mechanism involved in micro-seismic events will greatly help us understand the reservoir fracturing and the stress evolved. The components of moment tensor can tell us the information involving magnitudes, modes, and orientations of fractures. Meanwhile, its singular value decomposition (SVD) exposes the difference between three main kinds of source types that may present itself in a moment tensor solution. We propose to use support vector machine (SVM), which is a type of machine learning approach, to classify the source type of a micro-seismic event by using the normalized eigenvalues of moment tensor matrix as classification principal components. The tests on moment tensor matrices based on typical source type and real cases yield reliable classification results.
|Original language||English (US)|
|Title of host publication||80th EAGE Conference and Exhibition 2018|
|Publisher||EAGE Publications BV|
|State||Published - Oct 16 2018|
Bibliographical noteKAUST Repository Item: Exported on 2020-10-01
Acknowledgements: We thank KAUST for its support and the SWAG group for the collaborative environment. We also thank H. Wang and Q. Guo for their fruitful discussions and suggestions.