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Extractive industry
17:18, 22 September 2025
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Gazprom Neft and Innopolis Forge Digital Alliance for Oilfield Transformation

As digitalization advances, resource extraction is becoming increasingly knowledge-intensive. One example is the alliance between Gazprom Neft and Innopolis University, aimed at co-developing industry-specific software for the oil and gas sector.

Developing Reagents, Software, and Specialists

The agreement was formalized at the Tyumen Industrial and Energy Forum (TNF). The partnership will deliver predictive analytics tools, monitoring systems, and automation solutions for operations at autonomous oilfields.

A major advantage is the ability to test and refine products directly in the field, with Gazprom Neft providing industrial sites. Innopolis University contributes its competence centers and research laboratories.

The partners also agreed to establish unified standards for all data and processes. Each technology will pass through three stages of testing: a laboratory prototype, a pilot launch at a real facility, and only then—full-scale deployment.

A Team of the Best

This is not the first time academia and industry have joined forces. Cooperation between Gazprom Neft and Innopolis University began in 2018, when the sector required software for geomechanical and integrated modeling of in-house assets.

Partnership with Innopolis University helps us not only to implement advanced digital solutions but also to build an engineering talent pipeline for the future. Joint projects in artificial intelligence, robotics, and digital twins are already boosting the efficiency of our operations and ensuring the company’s technological resilience. We are confident that the synergy of science and business will accelerate our digital transformation journey
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Innopolis University is recognized as a center of excellence in distributed ledger technology (DLT). It is a key developer of blockchain solutions for logistics and supply chain management in the oil and gas sector. The university is also part of a consortium of scientific and industrial companies in Tatarstan, with which Gazprom Neft has long partnered to develop reagents for enhanced oil recovery at mature fields.

Forging Sovereignty

Replacing imported software in critical industries has shifted from theory to urgent practice under global technological realignment and sanctions pressure.

Expanding strategic cooperation between Gazprom Neft and Innopolis University represents a model case of shaping a new technological paradigm in Russia’s upstream sector.

What began in 2018 with solutions for specific tasks—such as geomechanics—has evolved into the creation of comprehensive domestic digital products.

Today, resource extraction is primarily about data. Predictive algorithms are enabling a shift from responding to accidents to preventing them. Accurate forecasts of pump wear in offshore or Arctic conditions help avoid multimillion-dollar losses and ecological disasters, while minimizing human error.

At autonomous fields—where logistics can take months and downtime costs can reach hundreds of thousands of rubles per hour—predictive maintenance and automation are critical for both economic efficiency and national security. Cutting operational expenses by 10–15% through digital solutions reflects results already validated across global operators.

Those Who Came Before

Russia’s oil and gas industry did not start its digital journey from scratch. Gazprom Neft had already built a strong base at its R&D center, developing digital tools for modeling and asset management.

Today, Russia’s challenge is to match and surpass international majors that pioneered digital oilfields and twin technologies. Having once imported such solutions, the country is now aiming to create and export its own technological standards.

In the coming years, prototypes and pilots will be rolled out at individual assets, while unified requirements for equipment and data will be developed. Large-scale deployment across the holding is expected in the medium term—three to five years.

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