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首页> 外文期刊>Transport in Porous Media >A Feature-Based Stochastic Permeability of Shale: Part 2-Predicting Field-Scale Permeability
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A Feature-Based Stochastic Permeability of Shale: Part 2-Predicting Field-Scale Permeability

机译:页岩的基于特征的随机渗透率:第2部分-预测油田规模的渗透率

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In a recent numerical study, it was demonstrated that characterizing reservoir permeability in terms of rock's quality, as observed in lab and field, is the most important step before implementing an enhanced oil recovery operation or drilling a new well in a tight formation. In that study, it was shown that permeable features in shale-like organic matter (OM) and fractures were the only regions that allowed some reasonable movement of fluid, whereas inorganic matter (iOM) that occupies larger pore volume with significant saturation of hydrocarbons has extremely low permeability that did not allow any reasonable fluid movement to affect production. That study demonstrated the importance of characterizing reservoir heterogeneity in shale in order to economically exploit the shale resource. This study proposes a method to predict spatially heterogeneous field-scale permeability of shale in terms of natural fractures, and matrix (iOM and OM). The method developed in Part 1 is combined with a history-matching process that uses only readily available information from lab-scale and outcrop (information from geologists) to predict field-scale permeability. The method also ensures consistency between the underlying fracture distribution and optimally matched fracture lengths and their apertures, in addition to accounting for random distribution of fractures and their abundance. Optimized parameters of fracture distribution are used to generate multiple realizations of geological model, and the best-fitting (most-likely) permeability scenario is chosen by generating production response of each realization of the geological model and comparing them against the observed field production history. The novelty of the proposed to predict field-scale permeability is that it uses only readily available information while also ensuring consistency between the underlying fracture distribution and optimally matched fracture lengths and their apertures, in addition to accounting for random distribution of fractures and their abundance.
机译:在最近的一项数值研究中,已证明在实验室和野外观察到的根据岩石质量表征储层渗透率是实施强化采油作业或在致密地层中钻新井之前最重要的步骤。在该研究中,表明页岩样有机质(OM)和裂缝中的渗透特征是唯一允许流体合理运动的区域,而占据较大孔隙体积且烃显着饱和的无机物(iOM)具有极低的渗透率,不允许任何合理的流体运动影响生产。该研究证明了表征页岩储层非均质性的重要性,以经济地开发页岩资源。这项研究提出了一种根据天然裂缝和基质(iOM和OM)来预测页岩在空间上非均质的田间渗透率的方法。第1部分中开发的方法与历史匹配过程相结合,该过程仅使用实验室规模和露头(地质学家提供的信息)的现成信息来预测油田规模的渗透率。除了考虑裂缝的随机分布及其丰度以外,该方法还确保了潜在的裂缝分布与最佳匹配的裂缝长度及其孔径之间的一致性。使用优化的裂缝分布参数生成地质模型的多种实现,并通过生成每种地质模型实现的生产响应并将其与观测的田间生产历史进行比较,来选择最适合(最可能)的渗透率方案。提议的预测油田规模渗透率的新颖性在于,除了考虑裂缝的随机分布及其丰度外,它仅使用易于获得的信息,同时还确保了潜在的裂缝分布与最佳匹配的裂缝长度及其孔径之间的一致性。

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