Dynamical counterfactual inference under time-series model for waterflooding oilfield
The performances of numerical simulation and machine learning in production forecasting are severely dependent on precise geological modeling and high-quality history matching. To address these challenges, causal inference is an effective methodology since it can provide a causality for formalizing...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
KeAi Communications Co., Ltd.
2025-02-01
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| Series: | Petroleum |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405656124000476 |
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