快速多点地质统计三维重建算法

A fast 3D reconstruction algorithm of multiple point statistics

摘要:

在SNESIM算法的基础上，提出了一种快速多点地质统计三维重建算法. 首先利用红黑树构建模式集，降低树结构高度，快速检索匹配数据事件. 其次综合概率融合与连续逐层采样方法，分别利用半模板与全模板进行点模拟，提高模板中条件数据的比例，缩小模式检索范围. 对二维河道图像、三维多孔介质图像和三维储集层岩心图像进行了多组重建实验，结果表明该算法能够在不损失精度的同时显著提升时间效率，且对于各向同性、各向异性岩心图像的重建结果都与真实数字岩心具有相似的视觉特征、统计特征和孔喉分布特征，证明了算法的可靠性.

Abstract:

Based on the SNESIM algorithm, a fast three-dimensional(3D) reconstruction algorithm of multiple-point statistics simulation was proposed. First, pattern sets were built by the red-black tree. The height of tree structures was rapidly reduced. CPU time for retrieving matching data events was saved. Then, the algorithm combined the advantages of probability aggregation approach and the sequential two-dimensional(2D) simulations with sample data approach. Half-template and all-template were utilized in nodal simulation. The proportion of informed conditioning nodes in template was increased so that the amount of possible data event was declined. The algorithm was tested on 2D channelized reservoir section, 3D porous medium images and 3D reservoir rock images. The results showed that this algorithm achieved the efficiency without degradation of accuracy. No matter isotropic or anisotropic rocks, the visual characteristics, the statistics characteristics and the pores-throats structures of the reconstructions were similar to the corresponding real 3D digital rock images, which proved that this algorithm was reliability.