The Use of 3D Convolutional Autoencoder in Fault and Fracture Network Characterization

Conventional pattern recognition methods directly use 1D poststack data or 2D prestack data for the statistical pattern recognition of fault and fracture network, thereby ignoring the spatial structure information in 3D seismic data. As a result, the generated fault and fracture network is not disti...

Celý popis

Uložené v:

Podrobná bibliografia
Vydané v:	Geofluids Ročník 2021; s. 1 - 11
Hlavní autori:	Xu, Feng, Li, Zhiyong, Wen, Bo, Huang, Youhui, Wang, Yaojun
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Chichester Hindawi 2021 John Wiley & Sons, Inc Wiley
Predmet:	Cluster analysis Clustering Coders Convolution Deep learning Dimensions Fault lines Feature extraction Feature selection Fractured reservoirs Geology Neural networks Pattern recognition Principal components analysis Seismic activity Seismic data Seismic simulators Seismological data Teaching methods Training Wavelet transforms China
ISSN:	1468-8115, 1468-8123
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!

Buďte prvý, kto okomentuje tento záznam!