Accurate Reconstruction of Porous Materials via Stochastic Fusion of Limited Bimodal Microstructural Data

Hechao Li, Pei En Chen, Yang Jiao

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

Porous materials such as sandstones have important applications in petroleum engineering and geosciences. An accurate knowledge of the porous microstructure of such materials is crucial for the understanding of their physical properties and performance. Here, we present a procedure for accurate reconstruction of porous materials by stochastically fusing limited bimodal microstructural data including limited-angle X-ray tomographic radiographs and 2D optical micrographs. The key microstructural information contained in the micrographs is statistically extracted and represented using certain lower-order spatial correlation functions associated with the pore phase, and a probabilistic interpretation of the attenuated intensity in the tomographic radiographs is developed. A stochastic procedure based on simulated annealing that generalizes the widely used Yeong–Torquato framework is devised to efficiently incorporate and fuse the complementary bimodal imaging data for accurate microstructure reconstruction. The information content of the complementary microstructural data is systematically investigated using a 2D model system. Our procedure is subsequently applied to accurately reconstruct a variety of 3D sandstone microstructures with a wide range of porosities from limited X-ray tomographic radiographs and 2D optical micrographs. The accuracy of the reconstructions is quantitatively ascertained by directly comparing the original and reconstructed microstructures and their corresponding clustering statistics.

Original languageEnglish (US)
Pages (from-to)1-18
Number of pages18
JournalTransport in Porous Media
DOIs
StateAccepted/In press - Jun 29 2017

Fingerprint

Porous materials
Fusion reactions
Microstructure
Sandstone
Petroleum engineering
X rays
Electric fuses
Simulated annealing
Physical properties
Porosity
Statistics
Imaging techniques

Keywords

  • Limited bimodal microstructural data
  • Microstructure reconstruction
  • Porous materials
  • Stochastic data fusion

ASJC Scopus subject areas

  • Catalysis
  • Chemical Engineering(all)

Cite this

Accurate Reconstruction of Porous Materials via Stochastic Fusion of Limited Bimodal Microstructural Data. / Li, Hechao; Chen, Pei En; Jiao, Yang.

In: Transport in Porous Media, 29.06.2017, p. 1-18.

Research output: Contribution to journalArticle

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