Name
Abstract | ||
|---|---|---|
The seismic response of geological reservoirs is a function of the elastic properties of porous rocks, which depends on rock types, petrophysical features, and geological environments. Such rock characteristics are generally classified into geological facies. We propose to use the convolutional neural networks in a Bayesian framework to predict facies based on seismic data and quantify the uncerta... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/TGRS.2020.3049012 | IEEE Transactions on Geoscience and Remote Sensing |
Keywords | DocType | Volume |
Uncertainty,Training,Bayes methods,Deep learning,Training data,Monte Carlo methods,Rocks | Journal | 59 |
Issue | ISSN | Citations |
10 | 0196-2892 | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Runhai Feng | 1 | 0 | 1.01 |
| Niels Balling | 2 | 0 | 0.34 |
| Dario Grana | 3 | 1 | 2.10 |
| Jesper Soren Dramsch | 4 | 0 | 0.34 |
| Thomas Mejer Hansen | 5 | 7 | 3.86 |