- Oil and Gas
Pipeline Integrity Management
The Infosys Oil and Gas practice partners with pipeline and downstream enterprises to mitigate risks in transporting hazardous cargo through pipelines across challenging terrains. We extend the life of aging pipeline infrastructure and ensure structural integrity through predictive maintenance. Our solutions help you rationalize the cost of pipeline maintenance, reduce insurance liability, and comply with regulations.
Our pipeline integrity management solution provides functional modules to meet the business requirements of complex pipeline networks. We combine 3-D visualization with Geographic Information System (GIS) for an integrated, real-time view of assets. Our threat identification and risk assessment solution incorporates tools for root-cause analysis.
Our augmented reality systems and protocols for sharing real-time information between the oil field and control room empower your mobile workforce. We reduce the time lag between problem detection and resolution by eliminating paper-based processes. Our record management system captures, consolidates, and retrieves information across diverse systems, and maintains an archive of business data.
Patented algorithm calculates pipeline integrity risk score by aggregating business, commercial, operational, and structural risks.
Alliances with product vendors for data management, physical and inline inspection, and simulation.
Web-based architecture adapts to existing technology stack and IT infrastructure.
Comprehensive portfolio of pipeline integrity management services, including business process blueprinting, future state mapping and realization, systems integration, data migration, and engineering assessment.
Customized reports for regional and international regulatory agencies such as Pipeline and Hazardous Materials Safety Administration (PHMSA), USA; Agency for the Cooperation of Energy Regulators (ACER), European Union; and National Energy Board (NEB), Canada. Applications and data models comply with Pipeline Open Data Standards (PODS).