Work

Predicting the Lifespan of Electric Submersible Pumps Using Random-Forest Machine-Learning

Year: 2024

Type: conference-paper

DOI: 10.2118/221203-ms

Authors: James O. Arukhe, Torty C. Kalu-Ulu, Ammal F. Anazi, Hamad M. Almarri

Institution: Saudi Aramco (Saudi Arabia)

Language: English

Topic: Oil and Gas Production Techniques

Subfield: Ocean Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: closed

OpenAlex ID: W4403287743

FWCI: 0.962

Cites: 26

Cited by: 1

Related to: 10