Characterization of pore size distribution in porous silicon by NMR cryoporosimetry and adsorption methods

2008 ◽  
Vol 70 (4) ◽  
pp. 507-514 ◽  
Author(s):  
A. G. Khokhlov ◽  
R. R. Valiullin ◽  
M. A. Stepovich ◽  
J. Kärger
Keyword(s):  
Porous Silicon ◽  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution

Characterization of Shale Pore Size Distribution by NMR Considering the Influence of Shale Skeleton Signals

2019 ◽  
Vol 33 (7) ◽  
pp. 6361-6372 ◽  
Author(s):  
Jinbu Li ◽  
Shuangfang Lu ◽  
Chunqing Jiang ◽  
Min Wang ◽  
Zhuoheng Chen ◽  
...  
Keyword(s):  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution

Characterization of Silica-Based Monoliths with Bimodal Pore Size Distribution

2002 ◽  
Vol 74 (11) ◽  
pp. 2470-2477 ◽  
Author(s):  
Felix C. Leinweber ◽  
Dieter Lubda ◽  
Karin Cabrera ◽  
Ulrich Tallarek
Keyword(s):  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Bimodal Pore Size Distribution

On the characterization of pore size distribution of building materials

2017 ◽  
Vol 41 (3) ◽  
pp. 247-263 ◽  
Author(s):  
LF Dutra ◽  
N Mendes ◽  
PC Philippi
Keyword(s):  
Relative Humidity ◽  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Building Materials ◽  
Mercury Porosimetry ◽  
Energy Performance ◽  
Volume Distribution ◽  
Wide Range

Moisture affects significantly the energy performance of air conditioning systems, the durability of materials, and the health of occupants. One way of reducing those effects, without increasing the energy costs, is by means of using porous material ability of absorbing and releasing moisture from/to the adjacent environment, which attenuates the indoor relative humidity variation. This natural ability is intrinsically related to the porous microstructure. Therefore, the characterization of the pore space is an important research theme in the building physics area. This article aims to present a method for obtaining the pore size distribution based on adsorption isotherms and mercury porosimetry data. First, the theoretical formulation based on the Gibbs free energy for a two-phase (liquid–vapor) system, using the De Boer and Zwikker model, is presented, allowing the calculation of the critical adsorbed thickness for pore filling, critical radius, adsorbed moisture content, capillary condensation content, available surface for adsorption, and the distribution of micropores for a wide range of radius. The adsorption isotherm curve is estimated for high relative humidity values through mercury porosimetry, along with the adsorption curve obtained from the experiment. The pore volume distribution calculated by this method can be used to estimate transport coefficients for liquid and vapor phases.

scholarly journals Integration of NMR, Conventional Logs and Core Data to Improve Formation Evaluation of a Gas Reservoir in Kangan and Dalan Formation, Iran

2014 ◽  
Vol 5 (1) ◽  
pp. 154-168
Author(s):  
Ali Mohammad Bagheri ◽  
Mohammad Mohammadnia ◽  
Ghafor Karimi
Keyword(s):  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Well Logs ◽  
Logarithmic Mean ◽  
Reservoir Properties ◽  
Gas Reservoir ◽  
Technical Problems ◽  
Conventional Logs

Conventional log based reservoir characterization of a gas reservoir in the Kangan and Dalan formations have recently been improved by application of the nuclear magnetic resonance log (NMR).    Important reservoir properties such as permeability, pore size distribution and capillary pressure curves can be estimated from NMR. These parameters are simulated directly in the laboratory on core samples recovered from the reservoir. Due to high cost associated with coring and some technical problems, few wells in any given field are cored.    The only problem of NMR measurements in gas reservoirs is that in gas-bearing zones, total NMR porosity read much less than actual porosity due to low hydrogen index of the gas. This problem was solved by integration of NMR porosity with conventional well logs such as density and sonic and compared with core porosity. Improved porosity calculation lead to better core independent permeability estimation on the wells logged with NMR.     NMR T2 distribution was calibrated with laboratory derived pore size distribution in 7 samples and a constant scaling factor was derived for each rock type to predict a pseudo pore size distribution from NMR. Logarithmic mean of pore size distribution in 4 wells with NMR was integrated with conventional logs in an artificial neural network to predict a pseudo pore size distribution logarithmic mean (PPSDLM) in the wells without NMR.    PPSDLM and conventional well logs were involved to an electrofacies modeling to predict electrofacies in the reservoir for characterization of heterogeneity of the reservoir in 3D geological model. NMR permeability was also imported to the model as an associated log to predict facies base permeability.    To test the permeability prediction, estimated permeability was compared with core derived permeability on 2 cored wells to see how well, estimated permeability fitted the actual core permeability.

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