Designing an intelligent system for global search of hydrocarbon reservoir rock fracture zones using discrete technologies

Abstract

The study is devoted to developing new approaches for predicting the zones of the destruction of hydrocarbon reservoir rocks using the formal logical apparatus of category theory and the ant colony algorithm. Upon further examination of the problem, it was revealed that the efficiency of predicting the distribution of hydrocarbon deposits significantly increases in the case of using knowledge about the dynamics of processes that create favorable conditions for the formation of hydrocarbon accumulations. The key information flows that describe the object of research are identified, and two types of parameters are distinguished: parameters that directly characterize the presence or absence of destructions and parameters that indirectly characterize the presence or absence of destructions. The main stage in analyzing existing methods and ways of predicting destruction is processing large data arrays characterized by weak structuring and low reliability. As a result, it is suggested that the formal-logical apparatus of category theory be combined with discrete structural components and a multi-agent method. The least- squares method was used to form the objective functions, which will mathematically formulate already structured data with sufficient accuracy. An organizational structure for anticipating the destruction zones of hydrocarbon reserve rocks is proposed. The major parameters that influence it are discovered during the formalization of the strategy for the prediction process. The existence or absence of reservoir rocks is anticipated using the principal agent classifications. To achieve this purpose, the ant colony approach was used to create a worldwide search using discrete technologies