Estimation of optimum fine-scale permeability with image logs and core photographs

准确预测原位采收率对优化油藏开发和资源管理具有重要意义。渗透率建模控制着稠油开采过程中流体流动和蒸汽/溶剂效率，是构建储层预测地质模型的关键因素。然而，获得具有代表性的岩石样品用于油砂储层的渗透率测试是困难和昂贵的。此外，现场温度和压力条件与岩心塞渗透率测量条件不同。研究方案解决的关键问题是如何在高分辨率流动模拟网格单元尺度下可靠地估计渗透率。

Accurate prediction of in-situ recovery performance is important to optimize reservoir development and resource management. Permeability modeling is a key element in construction of geological model for reservoir forecast, as it controls fluid flow and steam/solvent efficiency in most heavy oil recovery processes. However, obtaining representative rock samples for permeability testing in oil sands deposits is difficult and expensive. Furthermore, in-situ temperature and pressure conditions are different from those under which core plug permeability is measured. The key problem addressed by this research proposal is to make reliable estimations of permeability at the scale of high-resolution flow simulation grid cells.