Intelligent monitoring of large-scale distributed plants is known to exceed capabilities of SCADA systems. In order to perform plant-wide analysis and optimal planning tasks, global self-consistent state of a plant needs to be constructed at the start of each planning cycle as an input to them. State parameters values deviation shall be verifiably small at the planning horizon. The paper addresses issues associated with automatic computing an informational representation (model) of a global plant state. Its generation is presented as processing of two databases: the information model of a plant, and time series of measured parameters and state-dependant events. The technological transport road map optimization problem for an oil production enterprise is considered as an example. The aspect-oriented programming paradigm is regarded to be the most efficient for implementation of software modules that generate information model of state.