he paper under consideration summarizes the results of a group of authors' work on monitoring, analyzing, and managing well stock in complex geological and technological conditions. Application of a Model-Based System Engineering (MBSE) approach to managing the artificial lifting process is considered as the core concept. It is shown that traditional management methods based on the isolated consideration of individual objects are ineffective when operating wells in hard-to-recover reserves that are characterized by low-permeability, high water cut, and unstable flow regimes. The proposed approach implements a hierarchical system of interconnected models: from data models and physical models of wells and infrastructure to constraint models and optimization models. The key principles of the methodology are the following: structured system decomposition by levels, requirements traceability from the supersystem level down to specific control actions, model interoperability through standardized interfaces, and validation and verification at each level of the model hierarchy. Practical implementation was carried out through the integration of an intelligent automated gas-lift gas flow control system and the installation of an electric submersible pump, providing group optimization of well stock operations accounting for mutual influence of wells through common gathering infrastructure. Results of applying the approach to stabilize well network operations are presented, demonstrating the possibility of achieving systemic effects through application of the proposed approach.
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