scholarly journals Pore Structure and Interconnectivity of CdS Aerogels and Xerogels by Hyperpolarized Xenon NMR

2010 ◽  
Vol 114 (31) ◽  
pp. 13187-13195 ◽  
Author(s):  
Shane Pawsey ◽  
Kennedy K. Kalebaila ◽  
Igor Moudrakovski ◽  
John A. Ripmeester ◽  
Stephanie L. Brock
Keyword(s):  
Pore Structure ◽  
Hyperpolarized Xenon ◽  
Xenon Nmr

Synthesis and dissolved hyperpolarized xenon NMR studies of sucrose octaoleate-F104

2004 ◽  
Vol 125 (10) ◽  
pp. 1457-1460 ◽  
Author(s):  
Gerald W. Buchanan ◽  
Rufus Smits ◽  
Elena Munteanu ◽  
Giles Santyr ◽  
Julia Wallace ◽  
...  
Keyword(s):  
Nmr Studies ◽  
Hyperpolarized Xenon ◽  
Xenon Nmr

Rational design of hyperpolarized xenon NMR molecular sensor for the selective and sensitive determination of zinc ions

Talanta ◽  
2014 ◽  
Vol 122 ◽  
pp. 101-105 ◽  
Author(s):  
Ji Zhang ◽  
Weiping Jiang ◽  
Qing Luo ◽  
Xiaoxiao Zhang ◽  
Qianni Guo ◽  
...  
Keyword(s):  
Rational Design ◽  
Zinc Ions ◽  
Hyperpolarized Xenon ◽  
Molecular Sensor ◽  
Sensitive Determination ◽  
Xenon Nmr

ChemInform Abstract: Molecular Sensing Using Hyperpolarized Xenon NMR Spectroscopy

ChemInform ◽  
2014 ◽  
Vol 45 (20) ◽  
pp. no-no
Author(s):  
Krishnan K. Palaniappan ◽  
Matthew B. Francis ◽  
Alexander Pines ◽  
David E. Wemmer
Keyword(s):  
Nmr Spectroscopy ◽  
Molecular Sensing ◽  
Hyperpolarized Xenon ◽  
Xenon Nmr

Molecular Sensing Using Hyperpolarized Xenon NMR Spectroscopy

2014 ◽  
Vol 54 (1-2) ◽  
pp. 104-112 ◽  
Author(s):  
Krishnan K. Palaniappan ◽  
Matthew B. Francis ◽  
Alexander Pines ◽  
David E. Wemmer
Keyword(s):  
Nmr Spectroscopy ◽  
Molecular Sensing ◽  
Hyperpolarized Xenon ◽  
Xenon Nmr

Correlation of Pore Structure and Permeability by SEM-Image Analysis

1990 ◽  
Vol 48 (1) ◽  
pp. 428-429
Author(s):  
C. A. Callender ◽  
Wm. C. Dawson ◽  
J. J. Funk
Keyword(s):  
Image Analysis ◽  
Pore Structure ◽  
Imaging System ◽  
Pore Space ◽  
Simulation Models ◽  
Image Analyzer ◽  
Imaging Data ◽  
Sem Images ◽  
Thin Sections ◽  
Rock Types

The geometric structure of pore space in some carbonate rocks can be correlated with petrophysical measurements by quantitatively analyzing binaries generated from SEM images. Reservoirs with similar porosities can have markedly different permeabilities. Image analysis identifies which characteristics of a rock are responsible for the permeability differences. Imaging data can explain unusual fluid flow patterns which, in turn, can improve production simulation models.Analytical SchemeOur sample suite consists of 30 Middle East carbonates having porosities ranging from 21 to 28% and permeabilities from 92 to 2153 md. Engineering tests reveal the lack of a consistent (predictable) relationship between porosity and permeability (Fig. 1). Finely polished thin sections were studied petrographically to determine rock texture. The studied thin sections represent four petrographically distinct carbonate rock types ranging from compacted, poorly-sorted, dolomitized, intraclastic grainstones to well-sorted, foraminiferal,ooid, peloidal grainstones. The samples were analyzed for pore structure by a Tracor Northern 5500 IPP 5B/80 image analyzer and a 80386 microprocessor-based imaging system. Between 30 and 50 SEM-generated backscattered electron images (frames) were collected per thin section. Binaries were created from the gray level that represents the pore space. Calculated values were averaged and the data analyzed to determine which geological pore structure characteristics actually affect permeability.

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