Predicting pressure losses in the water-assisted flow of unconventional crude with machine learning
Machine learning (ML) is recognized as an efficient prediction tool. However, very few attempts have been made to apply it to model pressure losses in the water-assisted pipeline transportation of unconventional crudes. The performances of conventional ML algorithms for predictions were analyzed in...
| Published in: | Petroleum Science and Technology |
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| Main Author: | |
| Format: | Article |
| Language: | English |
| Published: |
Taylor and Francis Ltd.
2021
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| Online Access: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85115717461&doi=10.1080%2f10916466.2021.1980012&partnerID=40&md5=e49af5c174986d6efc76595b08c03f78 |