Application of neural networks modeling for interpretation of acoustic logging traces
The neural networks are proposed for application as a method for automatic P- and S-waves onset time-picking on sonic logging. The neural network models of acoustic emission preceding phase onset are trained and used to discriminate noise and desired signal, the last one being packets of longitudin...
Збережено в:
| Дата: | 2015 |
|---|---|
| Автори: | , |
| Формат: | Стаття |
| Мова: | rus |
| Опубліковано: |
Subbotin Institute of Geophysics of the NAS of Ukraine
2015
|
| Теми: | |
| Онлайн доступ: | https://journals.uran.ua/geofizicheskiy/article/view/111160 |
| Теги: |
Додати тег
Немає тегів, Будьте першим, хто поставить тег для цього запису!
|
| Назва журналу: | Geofizicheskiy Zhurnal |
Репозитарії
Geofizicheskiy Zhurnal| Резюме: | The neural networks are proposed for application as a method for automatic P- and S-waves onset time-picking on sonic logging. The neural network models of acoustic emission preceding phase onset are trained and used to discriminate noise and desired signal, the last one being packets of longitudinal and transversal waves. The given algorithm is easily adapted to existing systems and is able to provide both processing of logging tracks in online regime and high productivity of archive materials interpretation. |
|---|