A real-time production surveillance and optimization system has been developed to integrate available surveillance data with the objective of driving routine production optimization. The system aims to streamline data capture, automate data quality assurance, integrate high and low frequency data to extract maximum value, optimize the design and analysis of commingled well tests, and provide real-time multiphase well rate estimates for continuous well performance evaluation. A key challenge identified was the need to understand individual well contribution during commingled well tests, as traditional approaches may provide unrepresentative results. Additionally, the well tests are typically infrequent, thus further limiting the reliability of estimated well rates as production system dynamics between well tests are not accounted for. A third challenge recognized was the need for efficient testing procedures in order to minimize deferred production. To address these issues, a fully integrated model of the production system was used, and is driven by a computational algorithm that automatically calibrates the model to real-time sensor data.
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