Abstract
Cellular neural network is adopted for seismic pattern recognition. We design cellular neural network to behave as associative memory according to the stored patterns, and finish the training process of the network. Then we use this associative memory to recognize seismic testing patterns. In the experiment of seismic images, the bright spot pattern can be detected. The result of seismic pattern recognition can help the analysis and interpretation of seismic data.
| Original language | English |
|---|---|
| Pages | 2221-2225 |
| Number of pages | 5 |
| DOIs | |
| State | Published - 1 Jan 2019 |
| Event | 88th Society of Exploration Geophysicists International Exposition and Annual Meeting, SEG 2018 - Anaheim, United States Duration: 14 Oct 2018 → 19 Oct 2018 |
Conference
| Conference | 88th Society of Exploration Geophysicists International Exposition and Annual Meeting, SEG 2018 |
|---|---|
| Country | United States |
| City | Anaheim |
| Period | 14/10/18 → 19/10/18 |
Fingerprint Dive into the research topics of 'Cellular neural network for seismic pattern recognition'. Together they form a unique fingerprint.
Cite this
Huang, K-Y., & Hsieh, W. H. (2019). Cellular neural network for seismic pattern recognition. 2221-2225. Paper presented at 88th Society of Exploration Geophysicists International Exposition and Annual Meeting, SEG 2018, Anaheim, United States. https://doi.org/10.1190/segam2018-2997758.1