Abstract To maximize the value of limited steam capacity and achieve short-term production targets for a thermally developed project in the north of Kuwait, an automated workflow was developed. This workflow optimizes both steam distribution and operating modes—Cold, Cyclic Steam Stimulation (CSS), or Steam Flooding (SF)—for 35 active patterns, encompassing over 1,000 wells. The automated workflow begins by extracting historical injections and production data from the corporate database. It then generates three performance-based production forecasts (Cold, CSS, and SF) for each pattern using historical data and reservoir characteristics, which are validated against simulation results. An optimization tool evaluates the optimal combination of operating modes based on defined constraints, aiming to maximize production while adhering to steam capacity and facility constraints. The workflow produces an optimized steam plan and corresponding production forecast from multiple steaming scenarios within minutes, significantly accelerating and supporting the decision-making process. The steam optimization tool successfully generated an optimal steam plan for a 100 MBCWEPD steam capacity across the 35 active patterns. Additionally, the tool enabled rapid evaluation of multiple development opportunities. Key findings from these assessments include prioritizing newly commissioned patterns, reducing steam rates in SF patterns to reallocate steam more effectively, and identifying additional pattern conversion opportunities, all contributing to cost reduction and production enhancement. This study introduces a novel, efficient approach to steam optimization, enabling faster and more informed decisions. By optimizing steam allocation and distribution, the automated workflow helps reduce operational costs and maximize short-term production. The adopted methodology significantly improves planning through automation and can be effectively extended to other thermal recovery projects.
Ali et al. (Tue,) studied this question.