Optimized Flare Performance Analysis Through Multi-Modal Machine Learning and Temporal Standard Deviation Enhancements

Optimized Flare Performance Analysis Through Multi-Modal Machine Learning and Temporal Standard Deviation Enhancements

Flaring is a routine practice in the upstream gas industry to dispose of waste gases, but its efficiency can drop significantly under non-ideal conditions such as crosswinds, over-aeration, or over-steaming. These inefficiencies lead to incomplete combustion, producing harmful substances like carbon...

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Bibliographic Details
Main Authors: Said Boumaraf, Pengfei Li, Muaz Al Radi, Fares Oussama Abdelhafez, Abderaouf Behouch, Khalid Yousef Al Awadhi, Hamad Karki, Sajid Javed, Jorge Dias, Naoufel Werghi
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Flare stacks
combustion efficiency
temporal standard deviation
deep learning
CatBoost regression
Online Access:https://ieeexplore.ieee.org/document/10879335/
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