An intellectual system for supporting decision making in the control of the borring process
DOI:
https://doi.org/10.31471/1993-9981-2020-1(44)-119-137Keywords:
fuzzy control system, non-stationary process identification, Fuzzy modeling, dynamic control object (drilling), logic-linguistic rulesAbstract
The problem of development of the method of identification of complications arising in the process of drilling of oil and gas wells, which operates under the conditions of a priori and current uncertainty under the influence of various perturbations based on methods of fuzzy set theory and fuzzy logic, is considered.
A methodological approach to the estimation of the level of complications in the drilling of oil and gas wells, based on the principles of linguistic parameters of the drilling process, linguistic and hierarchical knowledge about the complications in the drilling of wells is proposed.
Mathematical models of a controlled object have been developed that, unlike deterministic mathematical models, allow to describe in natural language the cause and effect relationships between the parameters of the drilling process and the possible complication. These models reflect the logic of the operator's reasoning with the involvement of non-numerical and fuzzy information from an expert to formalize Fuzzy Logic decision-making procedures using the parameters and indicators of the oil and gas drilling process.
The structure of the decision support system for controlling the drilling of wells in the conditions of complications is proposed.
The results of simulation modeling of the developed methods of modeling of complications based on the methods of fuzzy set theory and fuzzy logic are presented. Their advantages over the well-known in accuracy of the tasks of identification of an estimation and control in the conditions of uncertainty concerning structure and parameters of object are shown.
The real complications have been identified, the elimination of which will increase the level of safety of the drilling process. It is shown that the developed methods and models can find application for modeling and identification of a wide class of complications on drilling rigs operating under the conditions of a priori and current uncertainty regarding their structure, parameters and geographic environment.
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