油藏油水两相流低阶模型算法

目前,油藏数值模拟主要采用的方法如有限元方法、有限容积法等在油藏数值计算时均需要较长的计算时间,很大程度上限制了油藏注采的实时预测与快速动态模拟.该文以一种高效的数据处理方法(最佳正交分解(POD)方法)为基础,对油藏油、水两相流抽取特征函数,并对油藏两相流模型进行Galerkin投影得到新的低阶计算模型.数值计算表明...

A Low-Order Model Method for 2-Phase Oil Reservoir Simulation

At present, the main methods used in reservoir numerical simulation, such as the finite element method and the finite volume method, require long calculation times, which limit their implementation in the real-time prediction and the reservoir production. An efficient data-processing method that based on the POD (proper orthogonal decomposition) was proposed to obtain the empirical coefficients and eigenfunctions of the oil-water 2-phase flow in the reservoir, and build a new low-order Galerkin calculation model. The numerical calculation indicates that, with the POD, the calculated eigenvector energy has proper features. Only a small number of eigenvalues can capture most of the energy, completely describe the reservoir characteristics (pressure, saturation), and help reduce the order of the partial differential equations. The calculation results of the low-order model are in good agreement with those from the IMPES, with much time saved. The proposed method applies well to history matching in numerical simulation of reservoir injection and production.