Pipelines are critical to the oil and gas industry, but their vast scale and exposure make them vulnerable to third-party interference (TPI)—a leading cause of failures. Traditional monitoring methods, such as aerial patrols and ground inspections, often miss critical threats, contributing to 35-40% of catastrophic incidents. A more advanced approach is needed.

This session explores how satellite data and AI-driven analytics are transforming pipeline monitoring by enabling near real-time risk detection. By integrating high-resolution satellite imagery with machine learning models, operators can proactively identify threats and mitigate risks before they escalate. The presentation will highlight how AI-powered insights support faster, more informed decision-making.

A case study featuring a major oil pipeline operator demonstrates the impact of this approach. The operator struggled with delayed threat detection, false alarms, and inefficient monitoring workflows. By adopting an AI- and satellite-based solution, they improved detection accuracy, reduced operational inefficiencies, and enhanced their risk management strategy.

The results were compelling:

73% of previously undetected threats were identified.

Threat prediction accuracy improved by 80% over seven monitoring cycles.

Monitoring workflows were streamlined, reducing operator workload by four hours per week.

Attendees will gain insights into how AI and satellite technology enable predictive risk detection, improve operational efficiency, and enhance pipeline integrity. A live demonstration will showcase how these technologies provide scalable, near real-time surveillance, delivering precise, actionable insights for proactive pipeline safety.