Real-Time Performance Optimization to Prevent Productivity Decline in Deep Offshore Producers

B. Izgec, L. Kalfayan
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Abstract

This paper presents a continuous well performance analysis technique that identifies formation damage and/or productivity loss real-time. It also provides insights into expected damage mechanisms enabling successful and efficient stimulation treatments. The analytical technique recognizes damage patterns at inception. The diagnostics to drive operational decisions are then presented as simple cartesian plots that grant easy access to users of all levels of experience. During initial well ramp-ups, the diagnostic plots can be automated with high frequency data. After reaching target drawdowns, low frequency data provides optimum surveillance. Case studies from several deepwater Gulf of Mexico wells demonstrate how the technique has been successfully operationalized to eliminate productivity loss, gain early insight into damage mechanisms, and investigate the impact of well interventions. Comparisons with pressure transient analysis and numerical history matching studies with all completion details corroborate the robustness of the method. Shutting in the wells is not required for the analysis, therefore lost production and additional stress cycles on the completion are eliminated. The analysis also identifies the maximum drawdown limit, thereby helping the operator optimize well performance real-time.
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实时性能优化,防止深海生产商产能下降
本文介绍了一种连续井动态分析技术,可以实时识别地层损害和/或产能损失。它还提供了对预期损伤机制的深入了解,从而实现了成功和有效的增产措施。分析技术在一开始就识别损伤模式。然后,驱动操作决策的诊断以简单的笛卡尔图的形式呈现,使所有经验水平的用户都可以轻松访问。在最初的油井增产过程中,可以使用高频数据自动绘制诊断图。在达到目标降压后,低频数据提供最佳监测。墨西哥湾几口深水井的案例研究表明,该技术成功地消除了产能损失,获得了早期损害机制的信息,并研究了油井干预的影响。与所有完井细节的压力瞬态分析和数值历史匹配研究的比较证实了该方法的鲁棒性。分析不需要关井,因此可以消除生产损失和完井时的额外应力循环。该分析还可以确定最大压降极限,从而帮助作业者实时优化油井性能。
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