What once relied on the instinct of engineers is today being steered by algorithms, sensors, and artificial intelligence. In 2025, we see the oilfield no longer as merely a site of extraction, but a smart, integrated energy hub where data shapes every decision and efficiency is engineered in real time. This shift is not incremental; it is transformational.
A recent Rystad Energy analysis estimates that accelerated digital adoption across exploration, drilling, asset maintenance, reservoir management, and logistics could unlock savings of over US $320 billion for the global oil and gas industry in the next five years. McKinsey & Company similarly reports that digital technologies can reduce upstream capital expenditure by up to 20 per cent and operating costs by 3–5 per cent, underscoring the scale of change underway.
In the oil and gas industry, there are constant new challenges and increasing complexity. This creates a continuous need to innovate—to work with greater efficiency and precision. In response, oil & gas companies have adopted advanced technologies across diverse onshore and offshore fields.
The Digital Imperative
Ageing fields with declining production, lower recovery rates, and rising exploration challenges in deep seas and harsh terrains directly impact India’s energy security. With India importing more than 88% of its crude oil needs, we stand at a critical juncture where increasing domestic production is essential to strengthen the nation’s energy independence. Considering operational pressures and geopolitical uncertainties, traditional exploration and production methods no longer sufficiently mitigate risk.
Digitalisation and artificial intelligence have moved from competitive advantages to operational essentials. Artificial Intelligence (AI) and Machine Learning (ML) are not just technological upgrades; but foundational to reducing costs and enhancing energy security.
AI and ML-driven optimisation is enabling smarter, faster, and more efficient operations in an industry where precision is paramount. Operational parameters of the plant, which used to be set up solely on the basis of human knowledge, now rely on optimised data from the Digital Twin (virtual replica). The outcome is clear: lower costs, reduced manual intervention, and significantly higher accuracy. Predictive maintenance powered by AI further allows us to anticipate equipment wear, prevent failures, and dramatically cut unplanned downtime. Further, by using AI, we are monitoring operations continuously - moving from reactive safety to proactive prevention. Across sites, oil & gas companies have also installed AI-based safety surveillance cameras, detecting over 20 different safety violations.
Furthermore, with the help of predictive tools, oil and gas companies can now anticipate equipment wear and tear, and potential failures, reducing unplanned downtime and maintenance costs. The key to such analysis is always data and its co-relation. According to an IEA report, the widespread use of existing digital technologies could reduce costs by around 10-20%, leading to significant long-term advantages.
Unlocking Unconventional Fields
From the Mangala block in Rajasthan, home to India’s largest onshore producing field, to long-producing offshore assets on the West and East Coasts - AI and digitalisation are helping manage declining output from conventional wells. As the industry leans more heavily on unconventional reserves such as Tight Oil and Gas and deploys enhanced recovery techniques like Alkaline Surfactant Polymer (ASP) - sensors and real-time monitoring systems have become indispensable to improving recovery and reducing downtime. Advances in subsurface imaging, drilling automation, and data-driven reservoir modelling are extending the productive life of legacy fields.
In Cambay (Gujarat) and Hazarigaon in the Northeast; robotics, drones, and zero-touch sensors have been deployed to automate inspections and enable continuous monitoring with minimal human intervention. First-of-its-kind LiDAR (Light Detection and Ranging) survey in Northeast operations was carried out using drones, enabling a faster, safer, and more cost-effective process for data collection, generation of precise 3D models, and accurate planning of civil works. Similar drone-based LiDAR and surveillance technologies are deployed at Bombay High offshore fields for pipeline inspections, corrosion detection, and 3D mapping of platforms, and at Duliajan oil fields for autonomous crude oil pipeline monitoring, leak detection, and security under the DRIVE initiative.
In gas fields, Digital Twins are helping optimise fuel usage, monitor pressure, and reduce gas flaring through real-time insights.
Looking ahead, Agentic AI is set to revolutionise the oil and gas industry by autonomously executing complex, goal-oriented tasks with a high degree of predictability. This AI-powered system, equipped with advanced reasoning and task execution capabilities, can accelerate productivity by integrating human input through multi-modal interfaces.
Collaboration As A Force Multiplier
Technology is evolving at a rapid pace, and keeping up with it is imperative to maximise the potential of industry and drive operational excellence. Alliances between government and private enterprises to fast-track the adoption of modern technology from across the globe will be a progressive step for India’s energy security. Beyond cost and operational efficiency, the benefits of digitalisation and AI also extend to environmental stewardship. Technologies such as CCUS and advanced analytics are enabling us to reduce emissions, optimise resource use, and contribute meaningfully to India’s Net Zero goals.
The year 2025 marked a turning point with the widespread adoption of AI and ML across the sector. In the coming years, the oil and gas industry will likely accelerate the transition from pilot projects to full-scale deployment of AI by integrating these tools in every aspect of operations. Targeted and innovative solutions in Gen AI and Agentic AI will help address some of the key challenges currently faced in terms of data quality and integration barriers.
As AI matures, it will play a decisive role in meeting global energy demand, enhancing operational resilience, and strengthening India’s energy security. |
