Alexander Podnebesnykh

The paper investigated the problem of selecting/finding the optimal process conditions for gas condensate wells. The well process conditions imply a set of parameters that characterize its operation. The optimization of process conditions provides for the efficient operation of an oil and gas field while meeting the defined boundary and initial conditions, and allows for the process/production goal to be achieved. This paper proposed using the tree-structured Parzen estimator (TPE), which allows for the results from previous iterations to be considered, in order to identify the most promising region of conditions, thereby increasing the optimization efficiency. The movement of multiphase fluid inside the pipeline system (also in the borehole) must be calculated to solve the process optimization problem. The optimization module was integrated into the hydraulic and unsteady state multiphase flow calculations inside the well and the pipeline. The platform created allows for the process conditions at gas condensate fields to be identified via the use of numerical methods. The proposed optimization algorithm was tested in delivering the task of optimizing the process conditions in 13 producing wells in a part of a real gas condensate field in Western Siberia. The engineering problem of optimizing the production of gas and the gas condensate was solved as a consequence of the calculations performed.

The work aimed to solve the problem of determining, validating, and transferring model parameters of flooding using chemical enhanced oil recovery (EOR) from a core experiment to a full-scale hydrodynamic model. For this purpose, a digital hydrodynamic model describing the process of oil displacement by the surfactant and polymer solution on the core is created and the digital model is matched to achieve convergence with the historical data. This approach allows the uncertainties associated with the limited number of experiments to be removed to fully describe the parameters of the chemical surfactant polymer flooding model and form a database that could subsequently be replicated at various field sites, having the composition of reservoir fluids and distribution of rock composition in the core material as the basis. Besides, the digital model allows for verification of physical and chemical properties of surfactants and polymers, values of the adsorption of chemical agents on rocks, and the behavior of relative permeability in the hydrodynamic model of EOR before making predictions on the full-scale model and to improve the quality of forecast cases.