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分形是一种几何物体,以不同的尺度来观察,它们似乎具有类似的形状。例如,储集层中的天然裂缝、渗透率数据,孔隙数据以及由不稳定混相驱动而导致的粘性指进,均显示出这种分形特征。特科特(Turcotte)引入了重正规化群(renormalization group)概念,并导出了一个立方体单元碎裂成体积逐渐减小的各单元的分维数。这一概念已成功地应用于依据采矿生产数据分析产量与等级的关系上。在本文中,重正规化群概念已推广用来预测油气藏的发现率,这种预测是以某一地区中探井成功率为基础的。作为次要目标,本文中还提出了一个预测含油区最终储量的模型。
Fractals are geometric objects that are observed on different scales and appear to have similar shapes. For example, natural fractures in the reservoir, permeability data, pore data, and viscous fingerprinting caused by unsteady mixed-phase drives all show this fractal character. Turcotte introduced the concept of a renormalization group and derived the fractal dimension of a cube where the cube was fractured into decreasing volumes. This concept has been successfully applied to the analysis of the relationship between output and level based on mining production data. In this paper, the concept of regularization groups has been extended to predict the discovery rates of reservoirs, based on the success rate of exploration wells in a particular area. As a secondary goal, a model for predicting the final reserves of oil-bearing regions has also been proposed in this paper.