The traditional exploration approach in oil and gas sector is expensive, risky, and prone to mistakes, as it heavily relies on human fieldwork. Even drilling dry holes hit oil and gas companies where it hurts – their wallets. The investment poured into geological assessment, drilling and testing goes up in smoke when the well doesn’t deliver. Artificial intelligence (AI) reduces the likelihood of such costly surprises and Oil and Natural Gas Corporation (ONGC) is showing the way forward. This state-owned enterprise, which produces nearly 68% of indigenous crude oil and 54% of country’s gas production, has made judicious use of AI technologies, such as machine learning and data analytics, thereby improving the accuracy of exploration predictions and resource estimation.
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ONGC has deployed AI/ML techniques at its Gandhar oil field, Cambay basin, near Bharuch town in Gujarat, to enhance its explorative and operational efficiency. “The project is top-down reservoir modelling in the GS-3A sand of the Gandhar oil field,” said Arun Kumar Singh, chairman & CEO, ONGC. This field has been in production for over 35 years and has a complex history involving oil, gas, water, and water injection. The project leveraged spatio-temporal learning, a machine-learning algorithm designed for fluid flow through porous media.
“Using the neural networks techniques and model training, 98% accuracy in history matching and production forecasting could be achieved. The AI-driven workflow also identified a new infill development well; the location was drilled to extract remaining oil and enhance recovery from the field,” Singh said. Similar top-down reservoir modelling is planned for Heera field in western offshore of ONGC, indicating the potential for broader application of this AI-driven approach.
The ONGC chairman said the integration of AI in the oil and gas upstream industry has emerged as a big enabler. AI technologies, such as machine learning and data analytics, have enabled companies to extract valuable insights from vast datasets, optimise processes, and enhance decision-making. During the exploratory phase, AI may help facilitate advanced seismic interpretation and reservoir modelling, improving the accuracy of exploration predictions and resource estimation. Smart drilling systems powered by AI may enhance drilling efficiency, reduce downtime, and optimise well performance through real-time data analysis during drilling operations. AI algorithms can analyse production data to identify patterns,
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