DocumentCode :
2429681
Title :
A hybrid reconstruction method of sandstone from 2D section image
Author :
Tang, Tang ; Qi-Zhi Teng ; Xiao-Hai He
Author_Institution :
Sch. of Electron. & Inf. Eng., Sichuan Univ., Chengdu
fYear :
2008
fDate :
7-11 June 2008
Firstpage :
342
Lastpage :
347
Abstract :
We present a hybrid algorithm to reconstruct 3D microstructure from 2D section image of sandstone. Utilizing porosity and autocorrelation function of 2D image, truncated Gaussian method based on fast Fourier transformation is used to reconstruct an initial structure rapidly with less accuracy. The initial structure is evolved by simulated annealing method to reconstruct a microstructure with the same statistic characteristics of 2D section image. Permeability of reconstructed microstructure estimated by Kozeny-Carman formula is close to that of tomographic images of sandstone. Experiments and comparisons show that the hybrid reconstruction method is more efficient and effective than simulated annealing algorithm alone.
Keywords :
Gaussian processes; correlation methods; fast Fourier transforms; image reconstruction; permeability; porosity; simulated annealing; statistical analysis; tomography; 2D section image; 3D microstructure reconstruction; Kozeny-Carman formula; autocorrelation function; fast Fourier transformation; porosity; reconstructed microstructure permeability estimation; sandstone; simulated annealing method; statistic characteristics; tomographic images; truncated Gaussian method; Autocorrelation; Computational modeling; Image reconstruction; Iterative algorithms; Microstructure; Permeability; Reconstruction algorithms; Signal processing algorithms; Simulated annealing; Statistics; Fourier Tranforms; Reconstruction; Simulated Annealing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks and Signal Processing, 2008 International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-2310-1
Electronic_ISBN :
978-1-4244-2311-8
Type :
conf
DOI :
10.1109/ICNNSP.2008.4590369
Filename :
4590369
Link To Document :
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