Predictive Analytics for Natural Gas Infrastructure and Pipeline Integrity

Abstract

Natural gas pipeline infrastructure forms the backbone of global energy transportation and distribution systems, yet its aging asset base, extensive geographic footprint, and exposure to corrosion, mechanical stress, and third-party damage create persistent integrity risks with severe safety, environmental, and economic consequences when failures occur. Conventional pipeline integrity management relies on periodic inline inspection, hydrostatic testing, and expert-driven risk assessment, approaches that are costly, operationally disruptive, and limited in their ability to anticipate failures between scheduled inspection intervals. Predictive analytics, powered by machine learning and deep learning, has emerged as a transformative complement to these conventional approaches, enabling continuous, data-driven prediction of corrosion rates, fatigue life, anomaly occurrence, and failure risk across pipeline networks. This article presents a research synthesis of predictive analytics applications for natural gas infrastructure and pipeline integrity, examining machine learning-based corrosion rate prediction, interpretable fatigue life modeling, anomaly and leak detection, and systematic evidence from the broader oil and gas pipeline failure prediction literature. It draws on case studies from heterogeneous depleted gas reservoir management, geothermal-analogue reactive heat exchanger engineering, and high-resolution petrophysical characterization relevant to reservoir-to-pipeline infrastructure planning, and further considers methodological parallels with large-scale AI-driven predictive analytics, administrative automation, and economic impact frameworks developed for national healthcare systems. The article concludes by identifying persistent challenges in data scarcity, model interpretability, and industry-wide standardization, and proposes a research agenda for advancing predictive analytics toward routine, trustworthy use in natural gas infrastructure integrity management as the field continues to mature in 2026 and beyond.