Decarbonization using operation data intelligence and digital twin technology

To achieve net-zero targets by 2070, ONGC has prepared a roadmap to reach net-zero for its Scope 1 and Scope 2 emissions by 2038. Currently, Scope 1 emissions account for 26.5% of total emissions and the primary contributors to these emissions include captive power generation, fuel combustion, gas flaring, and fugitive emissions.

One of the first step towards reducing Scope 1 emissions is to adopt decarbonization methods through operational data intelligence and digital transformative solutions, particularly digital twin technology. The digital twin technology provides real-time insights into operations and continuously monitors the health and condition of critical assets, allowing for the identification of excessive emissions and undetected leakages. Furthermore, it optimizes production and maintenance processes, enhancing operational efficiency and reinforcing ONGC's commitment to sustainability.

Presently, ONGC is implementing its first digital twin Integrated Operations project in the Eastern Offshore fields with a view to optimize production, enhance reservoir recovery and maximize reliability of the existing assets. As a part of the Integrated Operations, a standardized data historian platform is being developed to collect, manage, and analyze historical and real-time process, reservoir and asset data. This available real- time data supports various data analytics modules, including Production Management, Reservoir Management, and Asset Performance Management Solutions. These tools provide valuable insights and advisories, facilitating effective and collaborative decision-making across operations.

The presentation discusses the functionality of the Production, Reservoir and Asset management modules which simulates the various operational scenarios based on the real-time data and help in optimizing the production operations thereby reducing the fuel consumption and emissions. The predictive analytics from the Asset Management solution helps to prevent unplanned downtime by analyzing historical and real-time performance of the equipment data which encompass anomaly detection, fault diagnostics, time-to-failure forecast, and prescriptive guidance. With predictive analytics, maintenance engineers can identify inefficiencies and proactively address potential equipment failures before they escalate, optimize resource usage, and reduce fugitive emissions.

The presentation also covers on the capabilities of this operational data intelligence which enables ONGC to take informed decisions and implement targeted strategies for emission reduction. The continuous data analysis helps tracks progress against emissions reduction targets, ensuring accountability and transparency. Further, these enhanced communication and collaboration tools enable teams to share insights and best practices for emissions management.

From a sustainability perspective, this digital twin technology can help ONGC to eliminate fugitive emissions, decarbonize supply chains, and reduce the carbon generated as a result of operations, thereby accelerating it to achieve the net zero targets.