流场压缩感知渗透率计算  

Application of Compressive Sensing of CFD in Permeability Calculation

作　　者：郭龙 姚树新[1] 郑法威 GUO Long;YAO Shuxin;ZHENG Fawei(CNOOC Information Technology Co.,Ltd.,Shenzhen 518000,China;Shenzhen Institute of Advance Technology,Chinese Academy of Sciences,Shenzhen 518000,China)

机构地区：[1]中海油信息科技有限公司,广东深圳518000 [2]中国科学院深圳先进技术研究院,广东深圳518000

出　　处：《电子科技》2021年第5期1-6,共6页Electronic Science and Technology

基　　金：国家自然科学基金青年项目(41801223)。

摘　　要：石油工业需要通过CT扫描得到多孔材料模型的渗透率,但计算模型的网格数量通常非常巨大,一般大于2000×2000×2000体素,使用微型计算机难以在短时间内求解流体力学问题。采用低密度的网格降低模拟所需要的计算量,再使用一种数学上的拟合恢复算法将模拟结果恢复到高精度网格上,可以实现使用低性能设备短时间完成流体模拟任务。文中将压缩感知引入欧拉网格计算,恢复低精度采样的网格的流场数据。随机选取3块砂岩岩心,将压缩恢复结果和高精度网格计算的结果对比,误差在4%以内,证明该方法在岩石孔隙的流体模拟渗透率计算中可优化计算效率。The petroleum industry needs to obtain the permeability of porous material model by CT scanning,but the number of meshes in the calculation model is usually very large,which is usually larger than 2000×2000×2000 voxels,Therefore,it is impossible to solve the hydrodynamic problems by a microcomputer in a short time.If the low-density grid can be reduced with the amount of simulation decreased accordingly,and then a mathematical fitting recovery algorithm can be implied to restore the simulation results to the high-precision grid,the low-performance equipment may complete the fluid simulation task in a short time.In this study,compressed sensing is introduced into the Euler grid computation to recover the flow field data of the grid with low precision sampling meshes.Three sandstone cores are randomly selected and compared with the results of high-precision grid calculation,and the error is less than 4%.Therefore,this method can optimize the calculation efficiency in the permeability calculation of fluid simulation of porous rock.

关 键 词：算法优化 CT扫描 数字岩心 网格优化 计算流体动力学 压缩感知 格子玻尔兹曼方法 稀疏重构 

分 类 号：TP311.1[自动化与计算机技术—计算机软件与理论]