The principal features of the adaptive approach to digital geological modeling of oil and gas objects are considered, primarily related to the uncertainty of the initial data. It is shown that the adaptive approach, without requiring minimal discrepancies between the actual parameters and the results of modeling, allows to create the digital geological models of oil and gas objects adequate to the existing level of reliability of the input information, sufficiently accurate and acceptable in terms of labor costs, which take into account the most significant features of their geological structure. The adaptive geological model contains as many layers as can be identified from the results of detailed correlation, i.e. no upscaling of this model is required for its transformation into a hydrodynamic one. In the adaptive geological model, the actual and model parameters of wells may not coincide with each other, because such a model is a kind of averaged “surface” designed to minimize errors to the points of wells. To create an adaptive geological model of each layer, fuzzy-logical functions are used that describe the relationships between the parameters of wells and the seismic data. Due to the impossibility of selecting one function for the whole object, a field of fuzzy-logical functions is formed, in other words, a fuzzy-grid, which makes it possible to more flexibly model the geological structure of the object and its properties. A multi-layer adaptive model is formed by combining single-layer models. As an example, the results of adaptive geological modeling of the Permian-Carboniferous reservoir of the Usinskoye field which is the largest one in the Russian Timan-Pechora oil and gas province are presented. It is concluded that due to its mathematical apparatus based on fuzzy logic functions that are capable of adjusting themselves to specific initial data, the adaptive approach is an effective tool for operational forecasting of geological parameters necessary for solving different problems of originally oil and gas in place calculations as well as performance monitoring of the petroleum reservoirs.
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