基于人工智能的复杂海上成熟油田油藏自动快速保障和油藏健康诊断

M. Elwan, M. Surendra, S. Ghedan, Rami Kansao, Mahmoud Koresh, Hesham Mousa, Agustin Maqui, E. Shahin, M. Valle, I. Arslan, M. Ibrahim, Lamia Rouis, T. Eid
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引用次数: 0

摘要

苏伊西湾QQ油田是一个成熟的地质复杂油气藏,具有多层叠置、断陷、不同储层间混产的特点。本文阐述了自动化工具在系统、快速、详细地评估储层动态、识别关键采收率障碍和制定补救计划方面的强大功能,从而使储层能够充分发挥其生产潜力。对井和油藏数据进行处理,计算出一系列不同级别(井、层、油藏、井组等)的指标和关键性能指标。该工具有几个自动化模块,可实现快速、参数驱动的油藏保证和管理。这些模块包括:(i)井生产/注入分配,(ii)井下降曲线分析(包括事件检测),(iii)压力和电压分析,以及(iv)接触面分析。通过性能分析,该研究迅速确定了改善储层健康状况并最大化其价值的方法。QQ油田主要产自两个地层:努比亚和Nezzazat。此外,每个地层中都有多个子层。可靠的流量单元分配对于衡量每一层的贡献、确定油藏的不排水区域以及确定未来的开发机会至关重要。流动单元分配模块整合了所有可用的数据,如PLT/ILT数据、完井历史、每个流动单元在井位的渗透率、相对压力和水侵模型。根据分配的产量,努比亚和Nezzazat目前的采收率分别约为60%和20%。对RFT数据的分析显示,整个努比亚的垂直通信状况良好。然而,在某些地区,地层间压力存在明显的不连续性。两个地层的储层压力都降到了气泡点以下。因此,开始注水。努比亚各地的气压都恢复到泡点以上。含水层流入足以支持当前的采收率,无需进一步注水。然而,Nezzazat的储层复杂程度要高得多,因此压力变化很大。需要注水来维持储层各部分的压力在泡点以上。在流量单元分配的基础上,计算各区域、各层的空隙置换比(VRR)。尽管水淹区总体VRR大于1,但注入水分布不均匀。重新分配注入水,确保所有区域和所有层都得到充分的支撑,将有助于最大限度地提高采收率。油价的长期下跌需要极高的效率。搞好水库管理,不得占用不合理的时间和人力。快速、自动化的分析能够快速识别关键区域,以改进油藏管理实践,实现资产价值最大化。
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Artificial Intelligence-Based, Automated Rapid Reservoir Assurance and Reservoir Health Diagnostics in a Complex Offshore Mature Field
The QQ Field in the Gulf of Suez is a mature, geologically complex with multiple stacked, faulted reservoirs, with commingled production between different reservoirs. This paper illustrates the power of an automated tool to perform systematic, rapid, and detailed assessment of the reservoir performance, identify the key recovery obstacles and prepare remedial plans to enable the reservoir to produce to its full potential. The well and reservoir data were processed to compute a series of metrics and key performance indicators at various levels (well, layer, reservoir, well groups, etc.). The tool has several automated modules to facilitate rapid, metric-driven reservoir assurance and management. These modules include: (i) well production/injection allocation, (ii) wells decline curve analysis including event-detection, (iii) pressure and voidage analysis, and (iv) Contact analysis. Using performance analytics, the study quickly identified ways to improve the health of the reservoir and maximize its value. The QQ Field predominantly produces from two formations: Nubia and Nezzazat. Furthermore, there are multiple sub-layers in each formation. Reliable flow unit allocation is critical to gauge contribution of each layer, identify the undrained areas of the reservoir, and locate future development opportunities. The flow unit allocation module incorporates all available data such as PLT/ILT data, completion history, permeability of each flow unit at well level, relative pressures, and water influx model. Based on the allocated production, the current recovery factors in Nubia and Nezzazat are approximately 60% and 20% respectively. Analysis of RFT data reveals good vertical communication across Nubia. However, in some areas there is clear pressure discontinuity across layers. The reservoir pressure has dropped below the bubble point in both formations. As a result, water injection was initiated. The pressure in all parts of Nubia was restored above bubble point. Aquifer influx is sufficient to support the current withdrawal rates and further water injection is unnecessary. However, Nezzazat has a significantly higher reservoir complexity and therefore, shows a large variation in pressure behavior. It needs water injection to maintain the reservoir pressure above the bubble point in all parts of the reservoir. Based on the flow-unit allocation, the voidage replacement ratio (VRR) was calculated for each area and each layer. Even though the overall VRR in the waterflooded areas is above one, the distribution of the injected water is uneven. Redistributing injected water and ensuring that all the areas and all the layers are adequately supported will help to maximize recovery. The prolonged dip in oil price demands extreme efficiency. Sound reservoir management must not require unreasonable time or manpower. The rapid, automated analysis enables quick identification of the key areas for improvement in reservoir management practices and maximize the value of the asset.
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