Abstract

This paper describes the construction, calibration, and analysis of a multi-field integrated asset operations model (IAOM). The strategy is based on a hierarchical approach that introduces process concepts to assure simplicity, flexibility, and scalability as well as integration with external platforms without compromising on accuracy.

As a part of ADNOC Onshore's implementation of the IAOM, well and network models were constructed and calibrated for modelling field scenarios, identifying bottlenecks, and replicating business requirements. The new approach is rooted in concepts to assure maintainability of the network model. A hierarchical approach implemented during construction and calibration was defined in levels from wells to processing facilities, and was later standardized for ease of replication of structures.

Without compromising on accuracy, the new approach delivered ease of construction, calibration, and analysis that was not possible in an earlier field model. The flexibility in the hierarchical construction approach facilitated faster analyses of scenarios such as commingled flow-line effects and the impact of gas lift conversion. Additionally, model convergence time was reduced by half. The embedded scalability features increased efficiency in the modelling process such that the addition of a newly commissioned field to the network model became a simplified task, ensuring the model will be kept up to date. Hierarchy features facilitated ease of scenario definitions at different levels in the network and supported specific analyses.

A nomenclature structure provided flexibility in classifying grouped or related objects for changes in status in defining scenarios. Additional benefits were gained through the ability to easily integrate with other analytical tools such as forecasting software and other intelligent monitoring platforms owing to standardizations built into the network model.

This new approach allows engineers to understand the nuances of modeling and execute associated tasks in a structured and simplified manner, which can be replicated across other assets for increased efficiency and model performance.

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