Intelligent Control System for Gas-Condensate Field: A Holistic Automated Smart Workflow Approach

摘要

Gas condensate fields present unique challenges regarding data acquisition, data quality, exception-based surveillance, flow modeling, nodal analysis, well testing, allocation, and visualization. Although existing tools and methods address many of these aspects, it is possible to streamline processes and explore increased production efficiency methods. This paper addresses these challenges; it presents a case study of an intelligent control system implementation for a gas-condensate field based on a unified data model, integrated modeling, and cross-domain workflows. This paper presents a transformative, intelligent, and automated work process, referred to here as "smart workflows." As part of these workflows, virtual gauges are used that are based on inflow models and lifts, adjustable valves, and modular networks. The workflows are implemented on a truly open end-to-end platform that enables the coupling of multiple databases, streamlining of data for an integrated analysis of the measurements and model calculations, and ascertaining the mismatch between the two. The workflows also initialize adaptive self-tuning procedures. The smart workflows enable engineers to achieve various improvements, including an integrated structure of process data model to enable quick access to validated data, monitoring and control functions to a gas-condensate field in real time, and reduced downtime and operational costs. The smart workflow also supports functions that include collection and verification of measurement data, configuration of the integrated solution component models, evaluation of the action of root causes, and planning of operation scenarios. As part of the implemented system, an integrated information system data structure sets the degree of relatedness of tasks, each of which can be initialized depending on work situations and/or operator commands. Such comprehensive analysis of the data provides reliable integrated system configuration parameters of the model, which increases the accuracy of the calculations used in the optimal planning of the operational scenarios.