Mechanisms of sand production, prediction–a review and the potential for fiber optic technology and machine learning in monitoring
Author:
Funder
Universiti Teknologi Petronas
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s13202-024-01860-1.pdf
Reference149 articles.
1. Abduljabbar A, Amadi A, Mohyaldinn ME, Ridha S, Younis O, Alakbari FS (2024) Sand screens application and performance for sand control: a review of selection criteria, screen materials, and causes of failure. Heliyon 10(10):e30731. https://doi.org/10.1016/j.heliyon.2024.e30731
2. Abdelghany WK, Hammed MS, Radwan AE, Nassar T (2023) Implications of machine learning on geomechanical characterization and sand management: a case study from Hilal field, Gulf of Suez, Egypt. J Petrol Explor Prod Technol 13(1):297–312. https://doi.org/10.1007/s13202-022-01551-9
3. Aborisade OM (2011) Practical approach to effective sand prediction , control and management.
4. Ahad NA, Jami M, Tyson S (2020) A review of experimental studies on sand screen selection for unconsolidated sandstone reservoirs. J Petrol Explor Prod Technol 10(4):1675–1688. https://doi.org/10.1007/s13202-019-00826-y
5. Ajayi TJ, Adeogun OY, Omeru T (2022) Predicting sanding potential using empirical method in ‘Ebendo’ field, Niger Delta, Nigeria. J Appl Sci Environ Manag 26(9):1557–1564. https://doi.org/10.4314/jasem.v26i9.15
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