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A Pore-Scale Network Modeling Study of Gravitational Effects During Solution Gas Drive: Results From Macroscale Simulations

机译:孔径稳定网络建模研究解决气体驱动过程中的重力效应:宏观模拟的结果

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Although experimental work for solution gas drive processes is routinely carried out and interpreted for the purpose of defining critical gas saturations and relative permeability data, developing a thorough understanding of the results to facilitate confident application to the field is a hard task. Unfortunately, existing macroscopic models are unable to reproduce or take into account several different features of solution gas drive experiments. For example: (ⅰ) the impact of outlet boundary conditions upon the formation of saturation gradients, and ( ⅱ) transitions between different flow regimes (disconnected immobile gas, disconnected mobile gas, continuous gas flow) that are characterized by different pore-scale dynamics. These features can be considered using pore-scale modeling techniques. However, such microscopic applications, even in the few cases where they are refined enough to include viscous or gravitational forces, have perhaps their greatest limitation in the number of pores that can be simulated. This consequently makes it virtually impossible to simulate flow regimes that are not capillary dominated at an appropriate physical length scale. In this work a pore scale network modeling approach is presented which is capable of reproducing gravitational effects during oil depressurization through simulation in samples of macro-scale height. The models used comprise several hundred thousand pore elements. The primary objective is to fully simulate the physical height of routinely used laboratory samples, in this way reproducing the real scale and pressure dependent balance of forces: this allows us to show how the ratio of gravity to capillarity changes in relation to the rates of depletion (bubble densities), the rock, the fluid properties and the scale of the sample, and how this contributes to affect relative permeabilities and critical gas saturations. In particular it is shown that relative permeabilities can be predicted according to the particular flow regime operating during a given experiment (dispersed and/or continuous). Moreover we show that flow is largely determined by the size and density of gas clusters, whether originating from nucleation or from break-up of larger structures during migration. Furthermore, the ways in which different saturation gradients can develop over the length of a sample and the effects of the outlet boundary conditions upon such gradients are explained. The results are compared to available experimental data.
机译:尽管用于解决溶液气体驱动过程的实验工作是常规进行和解释的,但目的是定义临界气体饱和和相对渗透性数据,彻底了解对结果的彻底理解,以促进对该领域的自信应用是一项艰巨的任务。不幸的是,现有的宏观模型无法复制或考虑解决方案气体驱动实验的几种不同特征。例如:(Ⅰ)出口边界条件对形成饱和梯度的形成时的影响,(Ⅱ)不同流动制度(断开的固态气体,断开连接的移动气体,连续气体流量)的过渡,其特征在于不同的孔径动态。可以使用孔径建模技术考虑这些特征。然而,这种微观应用,即使在少数情况下,它们足够含有粘性或重力的情况,也可能在可以模拟的孔的数量中具有最大的限制。因此,这几乎不可能模拟不以适当的物理长度尺度主导的毛细管的流动制度。在这项工作中,提出了一种孔隙级网络建模方法,其能够通过宏观高度样本中的模拟在油减压期间再现重力效应。使用的模型包括几十万孔元件。主要目标是通过这种方式充分模拟常规使用实验室样本的物理高度,以这种方式再现实际规模和压力依赖性的力量:这使我们能够展示重力与耗尽率的变化如何变化(气泡密度),岩石,流体性质和样品的规模,以及如何影响相对渗透率和临界气体饱和。特别地,示出了根据在给定实验(分散和/或连续)期间操作的特定流动状态可以预测相对渗透性。此外,我们表明流动主要由气体簇的大小和密度决定,无论是均匀的核心还是在迁移过程中较大的结构的分解。此外,解释了不同饱和梯度可以在样本的长度上发展的方式以及出口边界条件在这种梯度上的效果。将结果与可用的实验数据进行比较。

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