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A Rigorous Pore-to-Field-Scale Simulation Methodology for Single-Phase Flow Based on Continuous Time Random Walks

机译:基于连续时间随机散步的单相流的严格孔隙对域仿真方法

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We demonstrate a pore-to-reservoir simulation methodology and apply it to singe-phase flow. Traditional numerical methods are based on the discretization of partial differential equations with known spatially-dependent coefficients, such as porosity and permeability. However, in porous media flow we do not know a priori what the governing transport equations are – for instance, single-phase transport cannot be accurately described by an advection-dispersion equation – nor do we know the reservoir properties everywhere. We propose a different approach that does not pre-suppose the functional form of the upscaled transport equations and which automatically accounts for uncertainty in the reservoir description. Single-phase transport is modeled as a continuous time random walk. Particles make a series of transitions between nodes with a probability psi(t)dt that a particle will first arrive at a node from a nearest neighbor in a time t to t+dt. A top-down multiscale approach is used to find the flow field. At the micron scale, psi(t) for particle transitions from pore to pore are found from modeling advection and molecular diffusion in a geologically representative network model. This psi(t) is used to compute transport on the mm to cm scale. At larger scales, we represent the reservoir as a network of nodes connected by links. For each node-to-node transition, we compute an upscaled psi(t) from a simulation of transport at the smaller scale. We account for small-scale uncertainty by interpreting psi(t) probabilistically and running simulations for different possible realizations of the reservoir model. To make the number of computations manageable, psi(t) is parameterized in terms of sub-scale heterogeneity and Peclet number, meaning that only a few representative simulations are required. We demonstrate the methodology by finding psi(t) for pore- scale flow and using it in a million-cell reservoir model. We sh ow that the macroscopic behavior can be very different from that predicted by assuming that the advection-dispersion equation operates at the small scale. Small-scale structure does impact macroscopic transport; increasing the pore-level heterogeneity delays breakthrough and leads to longer late- time tails of the production since the solute spends more time in slow-flowing regions of the domain. We discuss extensions to multiphase flow and the development of a novel network- based probabilistic reservoir simulation approach.
机译:我们展示了孔隙储层模拟方法,并将其应用于单相流。传统的数值方法基于具有已知的空间依赖系数的部分微分方程的离散化,例如孔隙率和渗透性。然而,在多孔介质流中,我们不知道一个先验的控制传输方程是 - 例如,不能通过平流分散方程式精确描述单相传输 - 我们也不知道到处都知道水库属性。我们提出了一种不同的方法,该方法不预先假设升高的传输方程的功能形式,并且在储层描述中自动考虑不确定性。单相传输被建模为连续时间随机步行。粒子在具有概率psi(t)dt的节点之间进行一系列转换,该概率psi(t)dt在时间t至t + dt中首先将粒子从最近邻居到达节点。自上而下的多尺度方法用于找到流场。在微米尺度下,从地质代表性网络模型中的建模和分子扩散中发现了从孔隙到孔隙到孔隙的PSI(T)。此PSI(t)用于计算MM到CM比例的传输。在更大的尺度上,我们将库作为通过链接连接的节点网络。对于每个节点到节点转换,我们从较小的刻度模拟传输的模拟计算Upscaled PSI(t)。我们通过解释PSI(T)概率和运行模拟来占小规模的不确定性,以获取水库模型的不同可能的实现。为了使计算数量可管理,PSI(t)在子级异质性和PEClet号方面参数化,这意味着只需要几个代表性模拟。我们通过在百万单元储层模型中找到PSI(T)来展示方法学通过找到PSI(t)并使用它。我们通过假设平流分散方程在小规模运行的情况下,宏观行为可以非常不同。小规模结构会影响宏观运输;增加孔径的异质性延迟突破并导致生产的延长时间延长,因为溶质在域的慢速流动区域中花费更多时间。我们讨论了对多相流的扩展以及新型基于网络的概率储层模拟方法的开发。

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