Authors :
Mohaned Alhaj A. Mahdi; M. Amish; G. Oluyemi
Volume/Issue :
Volume 9 - 2024, Issue 3 - March
Google Scholar :
https://tinyurl.com/48pevvf9
Scribd :
https://tinyurl.com/4jve8uv6
DOI :
https://doi.org/10.38124/ijisrt/IJISRT24MAR2108
Abstract :
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 the process. The role of
various factors such as production and reservoir data and
economic and environmental considerations is
highlighted. The article also examines the use of machine
learning (ML) techniques in the AL selection process,
emphasising their potential to increase the accuracy of
selection and reduce data analysis time. The findings of
this article provide valuable insights for researchers and
practitioners in the oil and gas industry, as well as for
those interested in the development of AL selection
methods.
Keywords :
Artificial Lift, Selection, Conventionals, Unconventionals, Machine Learning.
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 the process. The role of
various factors such as production and reservoir data and
economic and environmental considerations is
highlighted. The article also examines the use of machine
learning (ML) techniques in the AL selection process,
emphasising their potential to increase the accuracy of
selection and reduce data analysis time. The findings of
this article provide valuable insights for researchers and
practitioners in the oil and gas industry, as well as for
those interested in the development of AL selection
methods.
Keywords :
Artificial Lift, Selection, Conventionals, Unconventionals, Machine Learning.
