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Key Insights from Production Data Analysis and Mechanistic Modeling of an Extra Heavy Oil Field

机译:超重油田生产数据分析与机械建模的关键见解

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Extra heavy oil (< 10° API) reservoirs in South America contain upwards of 500 Billion barrels of crude oil with few fields on production and several new projects being planned. This paper presents results of a large extra heavy oil (XHO) field, under production since 2001 and developed using long (about 6000 ft.) horizontal wells. Data from more than 600 horizontal wells provided an extensive set for detailed analysis. This study includes production and logging while drilling (LWD) data analysis, detailed mechanistic modeling and field-scale dynamic simulation to improve understanding of production mechanisms and quantify effects of important reservoir parameters on primary production performance of XHO reservoirs. The LWD information was used to determine effective well lengths. The average effective well length was found to be 80% of the main trunk section, and is an important factor that impacts horizontal well performance. Production data from this field were analyzed to obtain initial production rate (IP). The IP show a strong and clear trend with depth, with lower IP for shallower reservoirs, caused by higher oil viscosity (due to lower temperature) and lower pressure in shallower reservoirs. Note that for extra heavy oils, viscosity is a strong function of temperature, unlike typical light oils. A large variation in individual well performance at wells in the same pad (or depth range) is also observed due to variation in reservoir quality and thickness. Detailed dynamic simulation was used to quantify impacts of key uncertainties. We also found that gas production rate may be underestimated and oil recovery may be overestimated in typical field scale XHO models because they may not properly capture pressure and saturation changes in the near-well region. As a result, gas saturations in the near-well region may remain below critical for a longer duration in models using coarse grid blocks impacting forecasts. We recommend using models with finer grids normal to horizontal well trajectory. Learnings from data analysis and mechanistic modeling were validated using a heterogeneous dynamic simulation model. Predicted fluid production rates and reservoir pressure compared well with measured data. This study provides clearer insights into XHO performance. The improved understanding will result in a more reliable production forecast and an optimal development plan, critical for improved assessment or design of new projects.
机译:南美洲的额外重油(<10°API)水库含有1000亿桶原油,生产少数田地,正在举办几个新项目。本文提出了自2001年以来生产的大型额外重油(XHO)场的结果,并使用长(约6000英尺)的水平井开发。来自600多个水平井的数据提供了一个广泛的详细分析。本研究包括在钻井(LWD)数据分析的同时生产和测井,详细的机制建模和现场规模的动态模拟,以提高生产机制的理解,并量化重要储层参数对XHO水库初级生产性能的影响。 LWD信息用于确定有效井长度。发现平均有效井长度为主干部分的80%,是影响水平井性能的重要因素。分析来自该领域的生产数据以获得初始生产率(IP)。该IP展示了强大而明显的趋势,深度,较低的储层IP,由较高的油粘度(由于较低的温度)和较低的水库中的较低压力引起。请注意,对于额外的重油,粘度是温度的强功能,与典型的轻油不同。由于储层质量和厚度的变化,还观察到相同焊盘(或深度范围)中的孔的个体井的性能的大变化。详细的动态仿真用于量化关键不确定性的影响。我们还发现,气体生产率可能被低估,并且在典型的场比例XHO模型中可能会高估储油,因为它们可能无法正确地捕获近孔区域的压力和饱和度变化。结果,近阱区中的气体饱和在使用粗网块冲击预测的模型中的较长持续时间下可以保持致力于。我们建议使用具有较好网格的模型正常到水平井轨迹。使用异构动态仿真模型验证了从数据分析和机械建模的学习。预测流体生产率和储层压力均匀与测量数据相比。本研究规定了更清晰的洞察力对XHO性能。改进的理解将导致更可靠的生产预测和最佳的开发计划,可用于改进新项目的评估或设计至关重要。

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