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DFA Asphaltene Gradients for Assessing Connectivity in Reservoirs under Active Gas Charging

机译:DFA沥青质梯度用于评估活性气体充电下储层连通性的梯度

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Identification of reservoir compartmentalization, quantification of flow connectivity, and assessment of compositional gradients are critical for optimal reservoir characterization, production, and management, especially in deepwater developments. Downhole fluid analysis (DFA) provides a useful tool to measure composition, gas/oil ratio (GOR), density, and color (linearly associated with asphaltene content). In particular, DFA is the method of choice to measure gradients of reservoir fluids vertically and laterally. Based on DFA measurements and advanced asphaltene science, a new modified Flory-Huggins regular solution model that has been referred to as the Flory-Huggins-Zuo EOS has successfully been developed and used to delineate reservoir connectivity recently. It provides the industry’s first predictive asphaltene grading equation of state (EOS) and has proven reliable to predict connectivity in equilibrated oil columns. The theory shows that asphaltene gradients can be large owing to both the gravity term and GOR gradients. In this case study, we demonstrate that the methodology for equilibrated reservoirs can be extended to nonequilibrium oil columns. We employ the new asphaltene Flory-Huggins-Zuo (FHZ) EOS for a reservoir currently undergoing active charging of biogenic gas. Isotope analysis shows that the biogenic methane is not equilibrated in this column. Nevertheless, the local asphaltene concentration within the column is shown to be equilibrated with the local GOR value and gradient. Based on the properties computed by the Peng-Robinson EOS with methane influx, the FHZ EOS for asphaltenes - originally formulated for equilibrium columns - may also be used to model the asphaltene (color) gradient in this nonequilibrium oil column. The obtained 2-nm asphaltene diameter is also consistent with field and laboratory data and is part of the Yen-Mullins model of asphaltene science (size of asphaltene nanoaggregates). This methodology establishes a powerful new approach for conducting DFA color grading analysis by coupling the Yen-Mullins model, and the FHZ EOS with DFA to address reservoir connectivity in reservoirs under active gas charging.
机译:储存局分子化的识别,流动连接量化,以及组成梯度的评估对于最佳的储层特征,生产和管理至关重要,特别是在深水发展中。井下液体分析(DFA)提供了一种有用的工具来测量组成,气体/油比(GOR),密度和颜色(与沥青质含量线性相关)。特别地,DFA是选择垂直和横向测量储层流体梯度的方法。基于DFA测量和先进的Asphaltene Science,已经成功地开发了一种新的修改谷常规解决方案模型,该模型已成功开发并用于最近描绘储层连接。它提供了行业的第一种预测性沥青质方程(EOS),并证明可靠地预测平衡油柱中的连接。该理论表明,由于重力术语和GOR梯度,沥青质梯度可以很大。在这种情况下,我们证明了平衡储层的方法可以扩展到非纤维柱。我们采用新的沥青内麦克伦 - Huggins-Zuo(FHZ)EOS用于目前正在进行生物气体积极充电的储层。同位素分析表明,生物甲烷在该柱中不平等。然而,塔内的局部沥青质浓度显示出与局部GOR值和梯度平衡。基于PENG-Robinson EOS与甲烷流入计算的性质,沥青质的FHz EOS - 最初配制用于平衡柱 - 也可用于将该非管纤维柱中的沥青质(颜色)梯度模拟。获得的2-NM沥青质直径也与现场和实验室数据一致,是沥青质科学的Yen-Mullins模型的一部分(沥青质纳米聚集的大小)。该方法通过耦合YEN-MULLINS模型和DFA的FHZ EO来建立一种强大的新方法,用于通过耦合YEN-MULLINS模型和使用DFA来解决积极气体充电下储层中的储层连通性。

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