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RESERVOIR REGIONS MANAGEMENT WITH UNSTRUCTURED GRID RESERVOIR SIMULATION MODEL

机译:非结构化网格储层模拟模型的储层区域管理

摘要

Reservoir management based on unstructured grid reservoir simulation is improved with machine learning based intelligent automation. Reservoir heterogeneity, geological internal boundary features and well geometry complexity are taken into account to automatically detect well zone and focusing reservoir area by calculating the region-of-interests in the model and defining cell spacing for grid coarsening and refinement in the reservoir. Data points for wells in the reservoir are grouped into reservoir regions according to datasets organized as a convex hull, which is a minimum convex set in spatial geometry which encloses the totality of such data points. The reservoir regions form a basis for grid spacing utilized in the reservoir model.
机译:借助基于机器学习的智能自动化,改进了基于非结构网格储层模拟的储层管理。考虑到储层的非均质性,地质内部边界特征和井几何形状的复杂性,可以通过计算模型中的感兴趣区域并定义单元间距进行储层网格粗化和细化来自动检测井区并聚焦储层面积。根据组织为凸包的数据集将储层中的井的数据点分组到储层区域,该凸包是空间几何中的最小凸集,该最小几何集包围了这些数据点的全部。储层区域构成了储层模型中网格间距的基础。

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