流场压缩感知渗透率计算

doi:10.16180/j.cnki.issn1007-7820.2021.05.001

摘要/Abstract

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2 000×2 000×2 000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。

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

Abstract:

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 2 000×2 000×2 000 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.

Key words: algorithm optimization, CT scanning, digital core model, grid optimization, computational fluid dynamics, compressive sensing, LBM, sparse reconstruction

中图分类号:

TP311.1

郭龙,姚树新,郑法威. 流场压缩感知渗透率计算[J]. 电子科技, 2021, 34(5): 1-6.

GUO Long,YAO Shuxin,ZHENG Fawei. Application of Compressive Sensing of CFD in Permeability Calculation[J]. Electronic Science and Technology, 2021, 34(5): 1-6.

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小波基	分层数	稀疏度
Haar	2	0.099
Haar	3	0.061
Daubechies	2	0.081
Daubechies	3	0.052
Symlets Biorthogonal	2	0.076
Symlets Biorthogonal	3	0.051

稀疏变换方法	分层数	稀疏度
小波变换	3	0.051
曲波变换	3	0.042

稀疏优化方法	渗透率/md	MSE
SPGL1	16.2	0.004 92
GPSR	16.1	0.005 26
FISTA	16.2	0.004 21
POCS	16.3	0.004 85

稀疏优化方法	切片重构时间 /ms	节约流场计算时间/ms
SPGL1	122	1 743
GPSR	35	1 830
FISTA	152	1 713
POCS	58	1 807