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本文针对储集层表征提出了一种经济、定量的方法,储集层表征可改进渗透率和一次采油及强化开采期注采动态的预测。该方法根本上是以岩石类型(有独特孔隙几何形态的岩石层段)的识别为基础。它应用岩心图像分析定量识别各种孔隙几何形态。当综合使用孔隙度、渗透率和毛细管压力等常规岩石物理测量值时,可以从非取心井或非取心层段的常规测井资料中识别具有不同孔隙几何形态(岩石类型)的岩石层段。这可用于岩石类型分析和改进对渗透率、饱和度的估算。基于地质输入,储集层可被划分为流动单元(流体动力学上的连续层)和模拟网格块。本文给出对一低孔隙度碳酸盐岩储集层和一高孔隙度砂岩储集层两个截然不同的复杂岩性储集层的详细研究结果。使用该独特技术获得的改进的储集层表征和动态预测结果与生产数据结合,就为我们确定最佳开发井位、改善井网设计、快速识别波及和地层损害问题、判别未波及生产层段及改善目前和将来价值评估提供了一种方法。
In this paper, an economic and quantitative method for reservoir characterization is proposed. Reservoir characterization can improve permeability and prediction of oil and gas production in primary recovery and enhanced recovery. The method is fundamentally based on the identification of rock types (lithosphere with unique pore geometry). It uses core image analysis to quantitatively identify various pore geometries. When conventional petrophysical measurements such as porosity, permeability, and capillary pressure are used in combination, it is possible to identify rock layers with different pore geometry (rock types) from conventional well log data from non-coring or non-coring intervals segment. This can be used for rock type analysis and to improve estimates of permeability and saturation. Based on the geological input, the reservoir can be divided into flow cells (hydrodynamically continuous layers) and simulated grid blocks. This paper presents detailed results of two distinctly complex lithologic reservoirs of a low-porosity carbonate reservoir and a high-porosity sandstone reservoir. The combination of improved reservoir characterization and dynamic prediction using this unique technology with production data helped us to identify the best development wellbore, improve well design, identify rapid wave propagation and formation damage problems, and identify areas that did not affect production And to improve the current and future value assessment.