普拉德霍湾三阶段井位产量分配

F. E. Bergren, D. Lagerlef, Scott Feldman
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引用次数: 4

摘要

在过去的19年里,三个阶段的生产分配计划在普拉德霍湾东部作区(PBEOA)不断发展。这些程序是必要的,因为只有在测试井时才能测量井的实际产量。由于每口井每周测试约6小时,因此需要在未测试时实时估计油井产量的方法。随着地面处理和产品运输限制的变化,这些估计用于优化井和油田生产。这些估计值还可用于实时估计油田产量,跟踪油井性能,并为核算和油藏管理目的分配油井产量。大多数自然流动井和所有气举井的速率表都是基于Fetkovich流入动态模型和油管性能关系2 (TPR’s),这些关系是从各种油管水力模型中开发出来的。特殊的速率表程序允许工程师将产量分配给总是在同一节流阀设置下生产的井,以及正在排气的井,并自动分配保持稳定产量的井。最近对分配系统的升级,利用了当前一代的计算机硬件、通信硬件和软件,使生产分配所需的工程时间减少了60%。本文讨论的分配过程可以应用于许多其他领域,以改善现场试井数据与油田产量优化之间的联系,实时估计油井和油田产量,跟踪油井动态,并将油田产量分配给油井,以实现油藏管理和会计目的。
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Three-Phase Well-Level Production Allocation at Prudhoe Bay
Three phase production allocation programs have continuously evolved in the Prudhoe Bay Eastern Operating Area (PBEOA) over the past 19 years. These programs are necessary because the actual production rate of a well can be measured only when a well is being tested. Since each well is tested for about 6 hours per week, some method of estimating well production rates in real time while the well is not being tested is required. These estimates are used to optimize well and field production as surface processing and product shipping constraints vary. These estimates are also used to estimate field production rates in real time, track well performance, and allocate production volumes to wells for accounting and reservoir management purposes. Rate tables for most naturally flowing wells and all gas lifted wells are based upon the Fetkovich inflow performance model and tubing performance relationships 2 (TPR's) developed from various tubing hydraulics models. Specialty rate table programs allow engineers to allocate production to wells which always produce at the same choke setting, wells which are in the process of gassing out, and to automatically allocate wells which maintain consistent performance. A recent upgrade of the allocation system, utilizing current generation computer hardware, communications hardware, and software has resulted in a 60% reduction in engineering time required for production allocation. The allocation process discussed here can be applied to many other fields to improve the link between field well test data and the optimization of field production rate, estimation of well and field production rates in real time, well performance tracking and allocation of field production to wells for reservoir management and accounting purposes.
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