Optimizing Gas Production Networks Through Automated Surveillance, Diagnostics and Scenario Comparison

Abstract This paper presents an efficient framework for automating surveillance, diagnostics, and scenario analysis in gas production networks via an interactive user interface. Utilizing well models with the latest operational data, the framework enhances the result's accuracy and minimizes uncertainties. These models can seamlessly integrate with database systems to initiate automated workflows that support continuous monitoring, predictive detection of flow assurance challenges in the system, and optimize production based on real-time field conditions. For precise assessment of network performance, a steady state flow simulator is used to prepare both the gas production network and individual gas wells finely tuned with the latest well test data. Data from digital oilfield instrumentation integrates into a structured query language (SQL) based production data management system (PDMS). Users initiate automated workflows via the PDMS and interactive dashboards, triggering requests through a specialized messaging system. These tailored workflows support: Network validation, which solves a network containing the latest operating conditions and validates against allocated rates. Network diagnostics, which identifies potential flow assurance issues, such as liquid loading, erosion, corrosion, and hydrate risk within the network. Scenario comparison, which allows on-demand what-if scenario analysis for evaluating network performance by adjusting subsurface and surface parameters. Production optimization, which suggests optimum choke sizes by prioritizing the maximization of gas rate. The results are presented via interactive dashboards, enabling proactive management and field engineer oversight on network performance. A robust surface network forms the backbone for orchestrating and evaluating what-if scenarios, comparing operational and planning cases. This tool visualizes both physical and quantitative alterations within the surface network, pre-emptively mitigating potential risks, and minimizing losses. Integrating network-based optimization enhances efficiency and reduces expenses. Furthermore, automated workflows save engineers’ time, reduces manual errors, and improves the accuracy and reliability of results, increasing overall work efficiency. The surveillance system includes pre- and post-separation assessments of rates and pressures, and continuous CO2 and H2S emission monitoring at manifold points. Flow assurance issues are promptly flagged for immediate visual identification and de-bottlenecking. Scenario analysis allows users to set subsurface and surface constraints directly via an intuitive interface, evaluating network-wide impacts against the base case. This workflow can be initiated directly from the dashboard, offering convenience and accessibility anytime, anywhere. Asynchronous notifications are initiated throughout the implementation process, empowering asset teams to make well-informed decisions; thereby optimizing resource management and refining production strategies for maximum effectiveness.