Bakbergen Bekbau delivered a presentation titled “Modeling of Hydrodynamic Processes: From Developing a Hydrodynamic Simulator to Machine Learning Applications”

            On March 2, 2026, a research seminar was held at the Department of Mechanics of L.N. Gumilyov Eurasian National University, where PhD Bakbergen Bekbau delivered a presentation titled “Modeling of Hydrodynamic Processes: From Developing a Hydrodynamic Simulator to Machine Learning Applications.”

            The talk addressed modern approaches to numerical modeling of complex processes in petroleum engineering and environmental systems.

            The core focus of the research is the development of domestic software tools for reservoir simulation and their application to practical engineering problems. In this context, the KMGEsim software suite was introduced, consisting of two reservoir simulators based on black-oil and compositional models. The software suite is positioned as an alternative to commercial reservoir simulators such as ECLIPSE and tNavigator and has been successfully validated on field-scale problems.

            The presentation also covered modeling of near-wellbore flow processes, water coning phenomena, flow diversion technologies using gel injection, and acid fracturing simulations. The results demonstrate that the developed models can significantly improve the efficiency of production technologies and support optimization of oil recovery processes.

            In addition, the final part of the seminar focused on the application of machine learning for predicting remediation of contaminated soils and aquifers. Data-driven models based on large datasets enable capturing complex nonlinear relationships and achieving high prediction accuracy, offering new opportunities for engineering decision-making.