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Well Test Analysis of Naturally Fractured Vuggy Reservoirs with an Analytical Triple Porosity – Double Permeability Model and a Global Optimization Method

机译:具有三重孔隙率-双渗透率模型和整体优化方法的天然裂缝性储层试井分析

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The aim of this work is to study the automatic characterization of Naturally Fractured Vuggy Reservoirs via well test analysis, using a triple porosity-dual permeability model. The inter-porosity flow parameters, the storativity ratios, as well as the permeability ratio, the wellbore storage effect, the skin and the total permeability will be identified as parameters of the model. In this work, we will perform the well test interpretation in Laplace space, using numerical algorithms to transfer the discrete real data given in fully dimensional time to Laplace space. The well test interpretation problem in Laplace space has been posed as a nonlinear least squares optimization problem with box constraints and a linear inequality constraint, which is usually solved using local Newton type methods with a trust region. However, local methods as the one used in our work called TRON or the well-known Levenberg-Marquardt method, are often not able to find an optimal solution with a good fit of the data. Also well test analysis with the triple porosity-double permeability model, like most inverse problems, can yield multiple solutions with good match to the data. To deal with these specific characteristics, we will use a global optimization algorithm called the Tunneling Method (TM). In the design of the algorithm, we take into account issues of the problem like the fact that the parameter estimation has to be done with high precision, the presence of noise in the measurements and the need to solve the problem computationally fast. We demonstrate that the use of the TM in this study, showed to be an efficient and robust alternative to solve the well test characterization, as several optimal solutions, with very good match to the data were obtained.
机译:这项工作的目的是使用三重孔隙度-双重渗透率模型,通过试井分析研究天然裂缝性松散油藏的自动表征。孔隙度之间的流动参数,孔隙度比,渗透率,井筒储存效果,表皮和总渗透率将被确定为模型的参数。在这项工作中,我们将使用数值算法将在全维时间内给出的离散真实数据传输到拉普拉斯空间中,在拉普拉斯空间中进行试井解释。拉普拉斯空间中的试井解释问题已被提出为具有箱形约束和线性不等式约束的非线性最小二乘优化问题,通常使用带有信任区域的局部牛顿型方法来解决。但是,在我们的工作中使用的称为TRON的局部方法或著名的Levenberg-Marquardt方法通常无法找到具有良好数据拟合度的最佳解决方案。像大多数反问题一样,使用三重孔隙度-双渗透率模型进行的良好试验分析也可以得出与数据良好匹配的多种解决方案。为了处理这些特定的特征,我们将使用一种称为隧道方法(TM)的全局优化算法。在算法的设计中,我们考虑了问题的问题,例如必须以高精度完成参数估计,测量中存在噪声以及需要快速计算解决问题的事实。我们证明,在这项研究中使用TM表现出是解决井测试特征的有效且鲁棒的替代方案,因为获得了几种与数据非常匹配的最佳解决方案。

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