Prediction of carbon dioxide phase at bottomhole by adaptive factorization network considering well geometry
Accurate carbon dioxide (CO2) phase prediction at the bottomhole of injection wells is essential for ensuring safe and efficient CO2 storage and enhanced gas recovery (EGR). Phase misclassification can cause operational inefficiencies, equipment failure, and compromised storage integrity, posing sig...
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| Main Authors: | Sungil Kim, Tea-Woo Kim, Yongjun Hong, Hoonyoung Jeong |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-06-01
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| Series: | Applied Computing and Geosciences |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590197425000369 |
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