Publications

This paper introduces a comprehensive approach for reservoir-to-surface network coupling, addressing challenges and uncertainties in the early stages of field development. The prevalent industry workflow, often time-consuming and domain-centric, tends to escalate uncertainty and yield optimistic predictions. In response, this study introduces a novel methodology for implementing reservoir-to-surface network coupling simulation in the context of deepwater gas condensate field development in the Kutai Basin. Utilizing industry-wide technology, this approach offers seamless integration and construction of a detailed dynamic reservoir and surface network models. The implementation of reservoir-to-surface network coupling using customized scripting to integrate two different simulators. By accounting for pressure losses and considering interactions between reservoir and surface components, this methodology ensures a more realistic representation of production allocation from well to gathering system, enhancing forecasting accuracy.

Key aspects of this paper include the analysis of uncertainties during early field development stages, the shortcomings of domain-centric workflows, and the step-by-step of reservoir-to-surface network coupling method. A field-scale reservoir dynamic model was initially developed, coupled with various well-and-network models representing different development scenarios. Results revealed a realistically reduced hydrocarbon recovery compared to the standalone case, due to additional pressure losses from the surface network system. The reservoir-surface model is solved in simultaneous manner iteratively, providing a faster solution while honouring boundary conditions. This integrative workflow enables comprehensive evaluation for production improvement opportunities, such as debottlenecking, adding compressors, or redesigning the production system to maximise hydrocarbon recovery.

The presented methodology not only enhances prediction accuracy in the development stage, but also offers a valuable tool for optimizing field performance in later field stage by capturing the synergies between reservoir and surface system dynamics. The findings presented in this paper contribute to advancing industry practices in reservoir engineering and field development optimization.