通过盲轮测试提高储层流体表征测试的准确性和精密度

A. Mawlod, Afzal Memon, J. Nighswander
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引用次数: 2

摘要

目标/范围:油气运营商除了使用油藏、生产和地面设施模拟工具外,还使用各种油藏工程工作流程来量化储量并完成油田开发规划活动。储层流体性质数据和模型是所有这些工作流程的基础输入。因此,了解由实验室流体性质测量数据和相应的模型不确定性引起的各种工作流程中的不确定性传播是很重要的。了解实验室数据不确定性影响的第一步是测量它,因此,ADNOC陆上进行了详细的研究,评估了四个选定的油藏流体实验室的性能。对选定的实验室进行了盲循环研究,包括储罐液体密度和摩尔质量测量、储层流体闪蒸气体和闪蒸液体C30+储层成分气相色谱测量,以及使用多种选定的储层和纯组分测试流体进行的恒定质量膨胀(CME)压力-体积-温度(PVT)测量。在分析研究完成并建立测量不确定度范围后,利用状态方程(EoS)模型完成敏感性分析研究,研究储层流体组成和分子量测量不确定度对EoS模型预测的影响。方法、程序、过程:设计并实施盲轮测试,以评估四个实验室的表现。严格保密,通过盲测协议隐瞒样品的身份。研究人员也见证了循环测试。EoS敏感性研究是使用Peng Robinson EoS和一个市售软件包完成的。结果、观察、结论:本文将介绍全盲储层流体实验室测试结果以及不确定度的统计分析。其中一个实验室在黑油参考标准样品上测量的正馏分组成存在系统性偏差。正分数浓度通常是黑油体系中重量百分比最大的组成部分,与正分数摩尔质量一起,在确定整体油藏流体组成的摩尔百分比方面起着至关重要的作用。另一个实验室存在与色谱成分集成误差相关的系统性问题,导致各种成分的碳数浓度趋势不一致。所有实验室都未能对参考样品进行一致的分子量测量。最后,一个实验室的P-V测量的相对偏差明显超出了可接受范围。EoS敏感性研究表明,当所有其他参数固定时,流体成分和储罐油摩尔质量测量对EoS模型预测有显著影响,因此对储/生产模型的输入也有显著影响。新颖/附加信息:据我们所知,这是第一次对商业油藏流体表征实验室进行如此广泛和完全盲的循环测试,并在公开文献中发表。该行业将从这种首次向所有人开放的盲循环数据集中受益匪浅。该研究为流体表征实验室在更大范围内进行这种独立的循环测试提供了基础、方案、期望和建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Accuracy and Precision of Reservoir Fluid Characterization Tests Through Blind Round-Robin Testing
Objectives/Scope: Oil and gas operators use a variety of reservoir engineering workflows in addition to the reservoir, production, and surface facility simulation tools to quantify reserves and complete field development planning activities. Reservoir fluid property data and models are fundamental input to all these workflows. Thus, it is important to understand the propagation of uncertainty in these various workflows arising from laboratory fluid property measured data and corresponding model uncertainty. The first step in understanding the impact of laboratory data uncertainty was to measure it, and as result, ADNOC Onshore undertook a detailed study to assess the performance of four selected reservoir fluid laboratories. The selected laboratories were evaluated using a blind round-robin study on stock tank liquid density and molar mass measurements, reservoir fluid flashed gas and flashed liquid C30+ reservoir composition gas chromatography measurements, and Constant Mass Expansion (CME) Pressure-Volume-Temperature (PVT) measurements using a variety of selected reservoir and pure components test fluids. Upon completion of the analytical study and establishing a range of measurement uncertainty, a sensitivity analysis study was completed using an equation of state (EoS) model to study the impact of reservoir fluid composition and molecular weight measurement uncertainty on EoS model predictions. Methods, Procedures, Process: A blind round test was designed and administered to assess the performance of the four laboratories. Strict confidentiality was maintained to conceal the identity of samples through blind test protocols. The round-robin tests were also witnessed by the researchers. The EoS sensitivity study was completed using the Peng Robinson EoS and a commercially available software package. Results, Observations, Conclusions: The results of the fully blind reservoir fluid laboratory tests along with the statistical analysis of uncertainties will be presented in this paper. One of the laboratories had a systemic deviation in the measured plus fraction composition on black oil reference standard samples. The plus fraction concentration is typically the largest weight percent component in black oil systems and, along with the plus fraction molar mass, plays a crucial role in establishing the mole percent overall reservoir fluid compositions. Another laboratory had systemic issues related to chromatogram component integration errors that resulted in inconsistent carbon number concentration trends for various components. All laboratories failed to produce consistent molecular weight measurements for the reference samples. Finally, one laboratory had a relative deviation for P-V measurements that were significantly outside the acceptable range. The EoS sensitivity study demonstrates that the fluid composition and stock tank oil molar mass measurements have a significant impact on EoS model predictions and hence the reservoir/production models input when all other parameters are fixed. Novel/Additive Information: To the best of our knowledge, this is the first time such an extensive and fully blind round-robin test of commercial reservoir fluid characterization laboratories has been completed and published in the open literature. The industry should greatly benefit from this first-of-its-kind blind round-robin dataset being made available to all. The study provides the basis, protocols, expectations, and recommendations for such independent round-robin testing for fluid characterization laboratories on a broader scale.
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