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Artificial lift selection methods in conventional and unconventional wells: a summary and review from old techniques to machine learning applications. (2024)
Journal Article
MAHDI, M.A.A., AMISH, M. and OLUYEMI, G. 2024. Artificial lift selection methods in conventional and unconventional wells: a summary and review from old techniques to machine learning applications. International journal of innovative science and research technology [online], 9(3), pages 2342-2356. Available from: https://doi.org/10.38124/ijisrt/IJISRT24MAR2108

Artificial lift (AL) selection is an important process in enhancing oil and gas production from reservoirs. This article explores the old and current states of AL selection in conventional and unconventional wells, identifying the challenges faced in... Read More about Artificial lift selection methods in conventional and unconventional wells: a summary and review from old techniques to machine learning applications..

A summary of artificial lift failure, remedies and run life improvements in conventional and unconventional wells. (2023)
Journal Article
MAHDI, M.A.A., AMISH, M., OLUYEMI, G. and ABDULMONIEM, M. 2023. A summary of artificial lift failure, remedies and run life improvements in conventional and unconventional wells. International journal of innovative science and research technology [online], 8(11), pages 1589-1596. Available from: https://doi.org/10.5281/zenodo.10251115

Artificial lift (AL) systems are crucial for enhancing oil and gas production from reservoirs. However, the failure of these systems can lead to significant losses in production and revenue. This paper explores the different types of AL failures and... Read More about A summary of artificial lift failure, remedies and run life improvements in conventional and unconventional wells..

An artificial lift selection approach using machine learning: a case study in Sudan. (2023)
Journal Article
MAHDI, M.A.A., AMISH, M. and OLUYEMI, G. 2023. An artificial lift selection approach using machine learning: a case study in Sudan. Energies [online], 16(6), article number 2853. Available from: https://doi.org/10.3390/en16062853

This article presents a machine learning (ML) application to examine artificial lift (AL) selection, using only field production datasets from a Sudanese oil field. Five ML algorithms were used to develop a selection model, and the results demonstrat... Read More about An artificial lift selection approach using machine learning: a case study in Sudan..