Translation. Region: Russian Federation –
Source: Peter the Great St. Petersburg Polytechnic University –
An important disclaimer is at the bottom of this article.
A panel discussion, "Visioning Digital Twins: Strategic Issues and Global Trends," was held at the Europa Hotel as part of the "Integrated Digital Twins 2025" conference. The event served as a platform for dialogue between Gazprom Neft and SPbPU. Oleg Tretyak, Head of the Digital Transformation Department at Gazprom Neft, opened the discussion.
At the beginning of the conference, Gazprom Neft's Director of Science, Mars Khasanov, presented the company's strategic approach to artificial intelligence. He emphasized that the value of AI is determined by its ability to solve production problems with measurable economic impact—from accelerating field modeling to risk management.
Modern intelligent systems are based on the synergy of neural and symbolic approaches, creating the foundation for conceptual engineering—a key discipline in managing the lifecycle of complex systems. The future of digital transformation is defined by a combination of hybrid AI methods with a focus on solving applied problems. In his presentation, he described the company's methodology in detail. This hybrid strategy combines the power of machine learning with the precision of physical models and the logic of expert systems.
Yuri Fomin, SPbPU Vice-Rector for Research, spoke from an academic perspective. He noted that effective collaboration between science and industry requires finding a balance between different planning horizons: businesses aim for quick results, while the university operates within a longer research cycle, combining both fundamental and applied research.
"We understand the business need for operational solutions and are actively developing applied areas ourselves," the vice-rector noted. "However, some tasks require more in-depth scientific research, which doesn't always fit into annual planning cycles."
The key challenge, according to the vice-rector, remains access to data due to security requirements and its incompleteness.
In such cases, digital twins come to our rescue—they allow us to work with the client to develop solutions and demonstrate their effectiveness, added Yuri Fomin.
He also discussed the current 2025 results of the POLANIS platform. The "Automation of Seismic Data Processing Using Artificial Neural Networks (ANN)" project, part of the Scientific and Technical Complex 3 (KNTN-3), is integrated into the universal POLANIS platform-ecosystem at SPbPU. The platform's development is being implemented within the framework of the "Priority 2030" program.
Alexander Paivin, Head of Asset Potential Management Methodology at Gazprom Neft, discussed the value of digital twins in the oil and gas industry and application examples. Dmitry Makeenko, Advisor to the Deputy Chairman of the Management Board at Gazprom Neft, discussed scalability: how to move from pilot projects to industrial applications.
Ilya Odnokolov, Head of the Prospective Development Program at Gazprom Neft, emphasized data as a foundation for determining the standards and approaches needed.
The conference was organized by the Industrial Innovations Association, intellectual partner Skoltech, general partner Gazprom Neft, and Peter the Great Polytechnic University.
Participants concluded that a strategic alliance between science and industry is necessary to create breakthrough technologies and ensure the technological sovereignty of the domestic fuel and energy sector.
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