University staff at the 27th Scientific and Practical Conference on Geological Exploration and Development of Oil and Gas Fields "Geomodel 2025"

From September 8 to 11, 2025, the 27th Scientific and Practical Conference on Geological Exploration and Development of Oil and Gas Fields "Geomodel 2025" was held in Gelendzhik.

This event is rightfully considered one of the largest in Russia in the field of geology and geophysics. For over a quarter of a century, the conference has annually brought together leading scientists and engineers with extensive experience in solving both theoretical and practical problems.

The conference traditionally attracts 200-300 specialists, experts, and scientists representing approximately 100 public and commercial companies, as well as leading universities across the country. The 27th scientific and practical conference on geological exploration and development of oil and gas fields, "Geomodel 2025," featured over 150 presentations, and leading oil and gas companies showcased their latest technological developments. Participants also enjoyed lecture courses on current topics, roundtable discussions, and discussion sessions.

Gubkin University was represented at the conference by faculty members from the Department of Exploration Geophysics and Computer Systems:

Associate Professor Alexey Shubin opened the conference with a course on petroelastic modeling for quantitative interpretation of seismic data;

Associate Professor Dmitry Danko presented two papers: "Wavefield Decomposition Method Based on Orthogonal Decomposition of Seismic Traces Using Principal Component Analysis" and "Application of Machine Learning Methods for Constructing Low-Frequency Models of Elastic Properties in Seismic Inversion Problems." The second paper was recognized as the best in the "Machine Learning and Artificial Intelligence in Geosciences" section;

Associate Professor Evgeny Rozhenkov presented the paper "Stochastic Modeling of Reservoir Properties to Improve the Robustness of Regression Analysis in Predicting Flow and Capacity Properties."