A data-driven approach to successfully analyze and evaluate production-fluid impact during facility system divert events is presented. The work flow effectively identifies opportunities for prompt event mitigation and system optimization. The methodology used includes data streaming, advanced computations on high-frequency data, visualization, data mining, and rules extraction. The paper demonstrates that applied data-driven analytics led to learnings and observations that had a positive effect on the management of facility systems during divert events.
Background
The subject field is a heavy-oil reservoir, using steam for enhanced oil recovery.
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