Predictive Modelling, Corrosion Control, and Human-Induced Failures in Pipeline Systems: A Review with Focus on Niger Delta region of Nigeria (American Journal of Engineering , Mechanics and Architecture (2993-2637), 2025)
Pipeline systems form the backbone of petroleum transport infrastructure, yet their integrity is increasingly threatened by a confluence of technical, environmental, and socio-political factors. This review consolidates current knowledge on the prediction and prevention of pipeline failures, particularly in Nigeria’s oil-rich Niger Delta, where corrosion, sabotage, and regulatory lapses converge to undermine operational sustainability. The central problem addressed is the persistent incidence of pipeline failures, both natural and human-induced, which continue to cause environmental degradation, economic loss, and social unrest. This problem is significant not only for energy security and national revenue but also for ecological preservation and public health. The review adopts a thematic synthesis approach, integrating findings from empirical studies, predictive modelling frameworks, regulatory analyses, and technology evaluations. It examines pipeline failure classifications, internal and external corrosion mechanisms, and the predictive capabilities of tools such as Artificial Neural Networks, Genetic Algorithms, and Polynomial Regression. It also explores the socio-environmental drivers of pipeline sabotage, assesses mitigation technologies (including repair welding, sleeving, and risk-based inspection), and evaluates the role of regulatory instruments such as the Petroleum Industry Act and NOSDRA protocols. Key findings reveal that while advanced predictive models and integrity monitoring systems are increasingly available, their effectiveness in Nigeria is constrained by poor data infrastructure, inconsistent regulation, and limited local adaptation. The current AI largely overlook sabotage prediction, despite its predominance in pipeline failure statistics. The review identifies critical gaps in data integration, community surveillance, digital twin utilization, and policy enforcement. These findings highlights the need for a thorough approach to pipeline integrity management, one that combines advanced diagnostics with community engagement, regulatory reform, and localized modelling. The study offers a conceptual foundation for future research and policy action, making it a valuable resource for engineers, environmental scientists, energy economists, and institutional stakeholders seeking sustainable solutions in pipeline infrastructure management.