AI-POWERED FORECASTING AND OPTIMIZATION IN OIL AND GAS PIPELINE OPERATIONS WITH RESEARCH TOOLS, TRENDS AND OPPORTUNITIES

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Published: 2026-04-25
DOI: https://doi.org/10.26483/ijarcs.v17i2.7415
Keywords:
Artificial Intelligence (AI), Oil and Gas Pipelines; Predictive Maintenance, Preventive Maintenance, Leak Detection and Corrosion Monitoring ,

Main Article Content

Aravindh Balan

Abstract

The oil and gas pipeline industry is one of the sectors that moving towards using AI for enhancing equipment reliability, safety of operations and maintenance effectiveness in?complex transmission networks' operation. The paper presents a complete summary of predictive and preventive maintenance measures in pipeline systems with the focus on AI-guided predictive analytics used in asset integrity management. The condition-based and risk-based maintenance models, time series prediction, classification, regression and anomaly detection algorithms that are used in failure forecasting and leak detection. Advanced sensing devices, such as smart sensors embedded in SCADA, and distributed monitoring systems, aid in real-time data capture and make it possible to make intelligent decisions. The mechanisms of corrosion and leakage in CO? pipelines are given special consideration as thermodynamic and environmental factors exacerbate operational risks in CO? pipelines. New trends like digital twins, edge computing, hybrid energy optimization, sustainability-driven metrics, etc. are analyzed as well. Although there has been a great improvement, the issues of the heterogeneity of data, model generalization, interpretability, and cybersecurity continue to be a major limitation to scalable AI implementation in high-stakes oil and gas environments.

Article Details

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Vol. 17 No. 2 (2026): March-April- 2026

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Articles

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