Chandigarh, Sep 25:Vedanta Oil and Gas Limited, the upstream oil and gas company held its Rajasthan operating cost broadly steady in the last financial year even as output from its ageing fields declined. The company attributes the result to operating discipline and an expanding layer of digital and artificial intelligence systems across its operations.
For the year to 31 March 2026, the Rajasthan operating cost was USD 16.4 a barrel, against USD 16.6 the year before. Across the oil and gas business, operating cost was USD 15.5 per barrel of oil equivalent, down from USD 15.6. Over the same period, gross operated production fell to 87.2 thousand barrels of oil equivalent a day from 103.2, a decline of 16 percent that the company attributes to the natural ageing of its fields. Rajasthan alone was down by the same margin.
In a maturing field, the cost of producing each barrel usually rises, because the fixed cost of running the operation is carried by fewer barrels. Here the per barrel cost moved the other way.
The company points to three measures behind the cost performance: optimised polymer injection, a more cost effective approach to chemical spend, and efficiency in maintenance activities. Maintenance is where its digital and AI tooling comes in.
“A rod pump usually tells you it is going to fail before it does. The signal was always in the data. What has changed is how fast it reaches the engineer who can act on it. Running digital twins, predictive analytics and advanced process control across our Rajasthan fields is a large part of how we have kept lifting costs steady while the fields naturally decline,” said a spokesperson from Vedanta Oil and Gas Limited.
How the fields are run
Across its Rajasthan facilities, Vedanta Oil and Gas runs digital twins alongside its physical equipment. These are software models built to mirror how each pump should behave, and when the equipment in the ground diverges from the model, the system flags it. An advanced process control layer keeps the pump within its operating limits while a production engineer decides on a response. Sitting on the same production data is a set of machine learning tools. Predictive analytics run against the live well feed, a centralised system the company calls Data Driven Reservoir Management pulls production data and forecasts into its reservoir models, and iCairn, an in house generative AI platform, supports safety monitoring, equipment analytics and the retrieval of information from technical records.
The digital build extends beyond day to day production. A portfolio management system built on the Quorum platform has cut planning and analysis time by about 30 percent. A cloud based seismic imaging tool, tested in the Aishwariya and Krishna Godavari deepwater areas, runs processing 20 to 30 times faster than the method it replaced, sharpening the company's view of the subsurface as it plans new wells.
The company is working the decline from two directions. During the year it drilled 21 infill wells across its Rajasthan assets, in the Mangala, Bhagyam, Aishwariya, Tight Oil, Raageshwari Deep Gas and Saraswati fields, to slow the fall in output. It drilled a further nine exploration wells, six in the OALP Cambay region and three in the Rajasthan Barmer region.
