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Multiscale imaging, modeling, and principal component analysis of gas transport in shale reservoirs

机译:页岩气藏输气的多尺度成像,建模和主成分分析

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Characterization and upscaling of gas transport in shales is challenging because of the multiple spatial scales. Rock characterization using high-resolution imaging (e.g., X-ray computed tomography [CT] and scanning electron microscope [SEM]) captures fundamental geometrical and transport properties, but the obtained information is usually highly localized and contains significant uncertainties. An effective upscaling method is thus needed to propagate the pore-scale information across multiple spatial scales. A modified dual-porosity model was proposed to study multiscale gas transport in shales. The model consists of two domains, a kerogen domain, and an inorganic matrix. Within kerogen, gas transport is dominated by molecular diffusion and nonlinear adsorption and desorption. Within inorganic matrix, gas transport is dominated by viscous flow driven by a pressure gradient. A mass-exchange-rate coefficient is used to describe gas transport between kerogen and inorganic matrix. The modified dual-porosity model was used to perform history matching of a pressure-pulse-decay experiment in the laboratory. The long tail of the pressure decline curve was well-captured by the model, suggesting that it accounted for both fast and slow transport mechanisms. Sensitivity analysis was conducted to study the impact of input variation on model output. We found that the impact of the transport processes within the slower domain (kerogen) depends primarily on the transport rate within the faster domain (inorganic matrix). The principal component analysis (PCA) method was applied to study the continuous movement of the upstream pressure decline curve resulting from input parameter variation. This study is the first to apply the PCA method in analysis of pressure decline curve in reservoir engineering. We found that increased convective transport rate within inorganic matrix expedited upstream pressure decline; conversely, increased mass-exchange rate and desorption-rate coefficients slowed down upstream pressure decline in the short term, but expedited it in the long term, when convective transport within inorganic matrix was fast. We also conducted primary recovery simulations to study the impacts of adsorbed gas ratio and Klinkenberg effect on upstream pressure decline, recovery factor, and recovery rate. We found that a higher adsorbed gas ratio led to a longer recovery rate curve. This confirms that a higher adsorbed gas ratio increases the longevity of a gas-producing well. Furthermore, Klinkenberg effect significantly enhanced initial recovery rate while lowering recovery rate at later times. Therefore, it is critical to accurately evaluate adsorbed gas ratio because it determines the shape and longevity of production curves; when reservoir pressure is relatively low, Klinkenberg effect might affect both early- and later-time production and thus cannot be simply ignored. (C) 2016 Elsevier Ltd. All rights reserved.
机译:由于存在多个空间尺度,页岩气中气体传输的特征化和规模化具有挑战性。使用高分辨率成像(例如X射线计算机断层扫描[CT]和扫描电子显微镜[SEM])对岩石进行表征,可以捕获基本的几何和运输特性,但是所获得的信息通常高度局限,并且存在很大的不确定性。因此,需要一种有效的放大方法来在多个空间尺度上传播孔隙尺度信息。提出了一种改进的双孔隙度模型来研究页岩中的多尺度天然气运移。该模型包含两个域,一个干酪根域和一个无机基质。在干酪根中,气体传输主要由分子扩散以及非线性吸附和解吸控制。在无机基质中,气体输送主要由压力梯度驱动的粘性流控制。质量交换率系数用于描述干酪根和无机基质之间的气体传输。修改后的双孔隙率模型用于在实验室中进行压力脉冲衰减实验的历史匹配。该模型很好地捕获了压力下降曲线的长尾巴,表明它解释了快速和缓慢的传输机制。进行了敏感性分析,以研究输入变量对模型输出的影响。我们发现,较慢域(干酪根)中运输过程的影响主要取决于较快域(无机基质)中的运输速率。应用主成分分析(PCA)方法研究了由输入参数变化导致的上游压力下降曲线的连续运动。这项研究是首次将PCA方法应用于油藏工程压力下降曲线分析中。我们发现,无机基质内对流输运速率的增加加速了上游压力的下降。相反,当无机基质内的对流输运速度很快时,增加的质量交换速率和解吸速率系数可以在短期内减缓上游压力的下降,但从长远来看可以加快这种压力。我们还进行了一次采收率模拟,以研究吸附气比和克林根贝格效应对上游压力下降,采收率和采收率的影响。我们发现较高的吸附气体比导致更长的回收率曲线。这证实了较高的吸附气体比增加了产气井的寿命。此外,克林根贝格效应可显着提高初始恢复率,同时降低以后的恢复率。因此,准确评估吸附气体比率至关重要,因为它决定了生产曲线的形状和寿命。当储层压力相对较低时,克林根贝格效应可能会影响早期和后期产量,因此不能简单地忽略。 (C)2016 Elsevier Ltd.保留所有权利。

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