Zobrazeno 1 - 2
of 2
pro vyhledávání: '"Cauligi S. Raghavenda"'
Autor:
Ke-Thia Yao, Cauligi S. Raghavenda, Cyrus Ashayeri, Dhruvil Trivedi, Tirth Patel, Manish Lal, Richard Row, Attila Aksehirli, Iraj Ershaghi
Publikováno v:
Day 3 Wed, October 05, 2022.
This paper presents a physics based and data driven machine learning approach for chemical treatment candidate well selection in fields producing heavy oil. In heavy oil fields, cyclic steam is often used to not only to stimulate the formation around
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ac36701d3af6fc40a5e6c580c3de821d
https://doi.org/10.2118/209999-ms
https://doi.org/10.2118/209999-ms
Autor:
Jingwen Zheng, Lanre Olabinjo, Ke-Thia Yao, Anqi Wu, Yintao Liu, Cauligi S. Raghavenda, Oluwafemi Opeyemi Balogun, Dong Guo, Iraj Ershaghi
Publikováno v:
All Days.
This paper presents a new generalized global model approach for failure prediction for rod pumps. By embedding domain knowledge into an Expectation Maximization clustering algorithm, the proposed global model is able to statistically recognize pre-fa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5e80fb0419da91aaf8394f7e1886a3f3
https://doi.org/10.2118/165374-ms
https://doi.org/10.2118/165374-ms