Dynamic Database for Proactive and Predictive Risk Management of Underground Pipelines: A Comprehensive Review

The integrity of underground pipelines is vital for the safe transport of resources like oil, gas, and water, but they face a variety of risks such as geohazard, third-party damage, and corrosion. These risks, coupled with the unpredictable nature of geohazards, demand innovative management strategies. This paper reviews existing pipeline risk management frameworks, which often rely on static data sets and reactive approaches. The review explores methodologies for pipeline hazard identification, risk assessment models, data integration techniques, and decision support tools. The paper also evaluates publicly available data sources, including those from NOAA, USGS, and NASA, alongside industry-specific databases and technologies like GIS-based visualization and machine learning. By identifying gaps and opportunities in current practices, this study establishes the current understanding for developing a dynamic, data-driven system to enhance proactive and predictive pipeline risk management. The findings offer a straightforward approach to enhancing pipeline safety, reliability, and resilience in challenging environments and operations.