The paper is devoted to the problem of adaptive forecasting of thermal efficiency in carbonate reservoirs of the high-viscosity oil Permian-Carboniferous reservoir of the Usinskoye field. The need to obtain reliable predictions has recently increased significantly due to the expansion of the steam flooding and steam-cycle stimulation applications in the reservoir. The lack of comprehensive understanding of physical processes occurring in the reservoir carbonate strata, as well as the lack of complete information on the wells operation, limits the abilities of deterministic models and method of water displacement curves to forecast the thermal efficiency. The detail of the adaptive geological model corresponds to the amount of available initial information, which is showed, for example, in cutting its layers, the boundaries of which are drawn from the results of detailed correlation and therefore their thickness is 5-10 m. The increased vertical dimensions of the layers make it possible to use the seismic data to reproduce the parameters of the interwell space due to their correlation with the well-data by fuzzy-logic functions. At the same time, the model parameters in those cells through which the wells pass do not necessarily similar with the data of these wells, since they are calculated taking into account the data of neighboring wells. The calculation of the adaptive hydrodynamic model is based on the redistribution of cumulative fluid production and injection among the cells in such a way as to obtain the actual dynamics of reservoir pressure, while the mechanism of this movement is similar to the method of cellular automata. It is shown that, based on the adaptive approach, it is possible to control the process of well thermal interaction, to determine the number of reacting wells, and to evaluate the actual additional oil production of steam flooding. In the paper, the results of adaptive forecasting of different options of the reservoir further development, allowing assessing the technological efficiency of steam flooding for the future are also shown. The performed comparison of predicted and actual values of well oil production rates after carrying out cyclic steam stimulations on them confirmed the effectiveness of the adaptive forecasting for the reservoir conditions.
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