The Oil and Natural Gas Corporation (ONGC) is the largest producer of crude oil and natural gas in the country and contributes about 70 per cent of the domestic oil production. Over the years, it has established a strong presence in the upstream and downstream oil and gas segments by developing significant onshore and offshore facilities. It has also deployed various technology solutions for optimising operations and improving decision-making. At a recent India Infrastructure conference, K.N. Ramesh, executive director and head, operational technology, ONGC, talked about the various technology solutions adopted by the company, the key challenges faced and the road ahead. Excerpts…
Key technology solutions deployed
The company started by leveraging information technology (IT) for its business processes about 20 years ago. It began with an enterprise-wide SCADA system, which consists of a two-tier architecture spread over 147 installations across onshore and offshore locations. Efficient monitoring of plant operations is being done using SCADA system. The system provides seamless integration of production data from meter to enterprise resource planning (ERP) system without any manual intervention. The SCADA system is used to remotely monitor and automate the control of offshore oil wells. It accomplishes these functions by integrating with networks, programmable logic controllers, remote terminal units, and sensors and equipment, allowing them to collect, analyse, translate and display real-time data.
Apart from this, ONGC is in the process of implementing a real-time production surveillance system and integrating some of the modelling software solutions such as eclipse-100, Petrel RE (reservoir modelling), PIPESIM (well modelling), and ReO (network modelling) for an integrated asset digital model (IADM). It is also using video analytics for plant safety, which is an algorithm-based processing of real-time camera feeds for ensuring 24×7 monitoring. The initiative will help the company improve maintenance standard compliance through real-time video-based monitoring to detect anomalies and conduct inspections through image recognition algorithms. This will also act as a warning on violations related to HSE and is also used for detecting process leakages.
Asset integrity management services help in enhancing reliability and availability of critical equipment helping in diligent monitoring of various parameters of high-speed rotating machines. Real-time monitoring data will be leveraged for predictive analytics, facilitating pre-emptive measures to avert unit failure or breakdown. Further, original equipment manufacturer (OEM) experts are required to remotely monitor gas turbines and crucial assets to enhance equipment availability and reliability. Predictive maintenance, a cornerstone of this paradigm shift, enables proactive equipment upkeep by leveraging advanced analytics to predict potential failures before they occur, saving both time and resources.
The company has deployed common reporting platform, which is basically an information system for drilling and work over rigs. It provides simple, visual solutions to speed up data entry and leverages the industry standard engineering database to store, manage and share data with ONGC’s existing suite of drilling engineering applications. This solution also creates a foundation for artificial intelligence/machine learning (AI/ML) workflows or analysis such as offset well analysis, well cost analytics and real-time drilling analytics. Statistical analytical system analytics (SAS) is used for building analytics for drilling and reservoir modelling. ONGC has also upgraded its ERP system to SAP S4 HANA.
ONGC is using real-time data analytics to monitor drilling operations continuously, analyse data and provide insights for optimising the rate of penetration. In this regard, the company collects comprehensive drilling data from various sources, including surface sensors, downhole tools, rig instrumentation, drilling reports and historical data repositories. Thereafter, analysis is done by the company to optimise drilling operations. Obtaining real-time data is possible through multiple means of connectivity technologies (broadband wireless access, lease lines, satellite communication and GSM) to reach the last mile.
Besides, it remains critical to detect faults in drilling operations beforehand so as to prevent accidents and ensure drilling safety. This requires developing predictive models using ML algorithms to forecast drilling behaviour and anticipate potential kicks based on historical drilling data, formation characteristics and drilling parameters. Moreover, stuck pipe analysis involves utilising AI/ML algorithms to analyse various data sources in real time and detect patterns indicative of a potential stuck pipe situation. Predictive models that forecast the likelihood of a stuck pipe occurrence are based on current drilling conditions and historical data.
Further, the remote well monitoring system helps monitor onshore wells via internet of things (IoT)-based devices at the asset and central levels.
A key initiative is DARPAN, which is used to enable the monitoring of the data from various sources. It is a first-of-its-kind digital hub in the country, which enables the monitoring of the company’s oil and gas wells and drilling units (including offshore) centrally, on a real-time basis. The state-of-the-art monitoring system can help reduce human intervention and downtime, optimising operations and facilitating predictive maintenance.
The company is at advanced stages of implementing an integrated digital analytics system (IDAS) for an offshore project in Mumbai. IDAS involves monitoring, surveillance and optimisation of wells and flow line network of offshore fields. It facilitates the creation of workflows, dashboards, use cases and functionalities through digitalisation.
Issues and concerns
As the oil and gas industry is capital intensive and complex, it poses several challenges, which at times hamper operations. Thus, safeguarding the oil and gas industry’s operational technology against cyberthreats is crucial for maintaining energy security, stability and safety. To this end, collaboration and collective action are essential for enhancing cyber resilience. The industry increasingly relies on remotely connected operational technology (OT). OT systems generate vast amounts of data from sensors, meters and control devices, which must be processed and analysed in real time to optimise production efficiency and detect anomalies or equipment failures. Besides, limited bandwidth and latency issues in remote locations can impact the timeliness and accuracy of data analytics. Oil fields are spread across the country and a key challenge is providing remote technical support. For instance, ONGC has to rely on radio links to connect to the remotest of locations. Cloud policy is another concern due to the limited availability of vendors on GCC for on-boarding. Through cloud solutions, it is easy to deploy a system of remote servers hosted on the internet to store, administer and process their information.
Future digital roadmap
Gas operators are increasingly relying on IT-OT for optimising operations. However, some of these technologies are being adopted in isolation and their convergence is essential for ensuring greater control over distributed systems and safeguarding critical data. Therefore, one of the emerging digitalisation needs of the oil and gas sector is the integration of digital platforms to reshape their operating landscape.
Notably, OT systems generate critical business data from flow meters and custody meters. The business requirement is such that the data needs to be integrated with the enterprise IT system for monitoring, analytics, production, accounting, etc. This reflects the need for IT-OT integration in the oil and gas industry. Moreover, for SCADA-ERP integration, the production values right from the meter get updated to the central ERP system for the purpose of production accounting without any human intervention.
Besides, there is a need to implement predictive maintenance solutions powered by AI/ML algorithms, which can help identify equipment failures before they occur, thus reducing downtime and optimising maintenance schedules. Digital twins are another emerging technology that helps in creating virtual replicas of physical assets, allowing operators to simulate and optimise operations in a virtual environment. It will enable better decision-making, performance optimisation and scenario planning. This can result in higher extraction rates and increased profitability for businesses. As drilling operations are complex and costly, digital twins and AI/ML can identify the optimal drilling speed and direction, improving the overall drilling accuracy.
