Download Pore Structure Characterization of Ten Typical Rocks in China

Pore Structure Characterization of Ten
Typical Rocks in China
Zechen Yan
State Key Laboratory of Disaster Prevention and Mitigation of Explosion and Impact, PLA
University of Science and Technology, Nanjing, Jiangsu 210007, China
Canshou Chen
College of Defence Engineering, PLA University of Science and Technology, Nanjing,
Jiangsu 210007, China
Pengxian Fan
1. State Key Laboratory of Disaster Prevention and Mitigation of Explosion and Impact,
PLA University of Science and Technology, Nanjing, Jiangsu 210007, China
2. Collage of Field Engineering, PLA University of Science and Technology，Nanjing,
Jiangsu 210007, China
Corresponding Author: fan-px@139.com*
Mingyang Wang
State Key Laboratory of Disaster Prevention and Mitigation of Explosion and Impact, PLA
University of Science and Technology, Nanjing, Jiangsu 210007, China; wmyrf@163.com
Xiang Fang
College of Field Engineering, PLA University of Science and Technology，Nanjing,
Jiangsu 210007, China; gygzr@sina.com
ABSTRACT
The characterization of rock pore structure is of great importance for many engineering fields. In
this paper, the test methods for pore structure characterization were reviewed and the mercury
intrusion method was recommended. Ten rock samples with different lithology were tested by
mercury intrusion method. The results of total porosity, average pore diameter and breakthrough
radius were given. The pore size distributions of samples were demonstrated by frequency
distribution diagrams and analyzed in detail. According to the test results, igneous rock samples
have small effective porosity and wide pore-size distribution range. The volume of meso-pore with
size between 10 and 1000 nm accounts for a large proportion of the total pore volume of
sedimentary rock. Pore size distribution curves of the tested samples are single peak except sample
B2 and B5.The test results imply that the pore structure of rocks with different lithology has little
similarity. Relative researches on pore structure of rock and their characteristic method are also
discussed.
KEYWORDS: rock; pore classification; test methods; pore-size distribution.
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INTRODUCTION
Rock is a natural porous material, and many engineering problems in rock mechanics and
engineering geology are closely related to rock pore structure. For example, the evaluation of rock
reservoir productivity in oil and gas exploration, some major disasters such as gas and water inrush
in coal mining, and the propagation of stress wave caused by earthquake or explosion in rock and
soil medium. As a material with hierarchic structure, the microstructure of rock greatly influences
engineering properties like permeability, strength and durability. Recent research (1-4) also reveal
that, the stress fluctuation and concentration induced by the meso-structure and internal defects
play an important role in the deformation and failure process of rocks. Understanding and
quantitatively describing the influence of pore structure on rock properties have a great
significance in petroleum geology, mining, civil engineering and water conservancy projects.
However, the published data of pore structure of engineer rocks is relatively less in spite of its
importance, except for petroleum industry.
C. De Las Cuevas5 characterized the pore structure of rock salt from the Lower Salt Unit of
the Cardona Saline Fm. (Spain) by using three independent methods: mercury injection
porosimetry, saturation in a low viscosity isoparaffin and gas adsorption. He found that the
effective porosity obtained by saturation in a low viscosity isoparaffin is significantly less than that
obtained by mercury injection porosimetry. V. Cnuddeand et al. (6) studied microstructure of
concrete and natural building stones by X-ray computed micro-tomography (micro-CT), water
absorption under vacuum and mercury intrusion porosimetry (MIP). Their test results showed that
not only the total porosities varied greatly, but also porosities measured by different methods in the
certain range of pore diameter were also significantly different due to the material properties and
pore structure characteristics. Test results indicate that different test methods may have a
significant or even decisive influence on test result.
In this paper, we first reviewed the test methods for pore structure characterization of rocks.
The advantages, disadvantages and the scope of application of different test methods were
analyzed. By mercury intrusion method, we tested 10 rock samples with different lithology to
study the pore structure of rocks. Test results were analyzed with the statistics of the distribution
of the pore with different size.
TEST METHODS FOR CHARACTERIZATION OF ROCK
PORE STRUCTURE
Pore structure refers to the geometry, size, distribution and interconnected relationship of rock
pore, etc. Characterization parameters of pore structure mainly include the porosity, pore-size
distribution and characteristics of rock pore. In the past decades, several methods are developed to
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characterize the pore structure of rock or other porous materials. Because different test methods
may have a significant or even decisive influence on test result, we first review the test methods.
Scanning electron microscope (SEM)
Scanning electron microscope (SEM) (7) is a type of electron microscope that produces
images of a sample by scanning it with a focused beam of electrons. The electrons interact with
atoms in the sample, producing various signals that can be detected and that contain information
about the sample's surface topography and composition. An SEM image of mineral has
characteristics of stereo image, high resolution and great depth of field, which can analyze the
three-dimensional shape and connectivity of pore-throat system, pore throat configuration
relationship, the type of clay minerals and their chemical speciation in samples. In recent years, the
innovative of electron microscope technology has led to the development of focused ion beam
polishing technology (FIB), field emission SEM with higher magnification and transmission
electron microscopy, providing tool s to observe small pores.
SEM method can qualitative characteristics the pore images of materials and unable to obtain
the quantitative data of the pore-size distribution. In addition, SEM needs to process rock samples,
which to some extent destroys the internal structure and external morphology of the pores in the
rock samples, also causes a distortion of observations. At the same time, because the greater the
magnification, the smaller the field of view, it is easy to over generalize the observation and miss
important information.
Nuclear magnetic resonance (NMR)
NMR (Nuclear magnetic resonance)8 technology is a physical phenomenon in which nuclei in
a magnetic field absorb and re-emit electromagnetic radiation. It is the response signal of fluid
hydrogen nuclei in the rock pore that being measured when the water (oil) saturated rock is given a
nuclear magnetic resonance imaging (NMRI) scan. Because the rock usually consists of pores of
different sizes, the pin echo trains measured in water (oil) saturated rock by NMR are actually a
result of the superposition of variety of transverse relaxation components. After the spin-echo
sequence is obtained, transversal relaxation time spectrum can be gotten by using mathematical
inversion. According to the principle of NMR, signal with longer relaxation time corresponds to
the larger pore space. Meanwhile, the signal strength of water (oil) saturated rock is proportional to
the amount of fluid that rock contained. The more fluid that rock contained, the stronger the
magnetic resonance signal is.
At present, NMR is applied more in normal sedimentary rocks such as sandstone, carbonate
rock; other types of rock have more magnetic mineral composition which has a great influence on
pore fluid signal. In addition, for rock sample with large pores, due to fluid polarization is not
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complete, NMR method also can cause large error. In principle, this method only measures the
open pores in the rock. Open pores refer to those which are connected to the outside. As a result,
the porosity is also divided into open porosity and close porosity. Because close pore is not
connected to the outside, it is difficult to determine the close porosity.
Mercury intrusion porosimetry (MIP)
MIP9 method is based on the fact that mercury, as a non-wetting liquid, will enter pore spaces
when pressure exceeds capillary pressure. The pore size invaded by the mercury is related to the
applied pressure by the Washburn equation:
P= −
2γ cos θ
r
(1)
where P is applied pressure; γ is the surface tension of the mercury; θ is the contact angle;ｒis the
pore radius.
Because γ is 0.480 N/m for mercury, Eq.1 can be simplified to:
r=
750
P
(2)
where the unit of the pressure is MPa, the unit of the pore radius is nm.
It can be seen that each capillary pressure corresponds to a pore radius, and the amount of the
mercury invaded under a certain pressure represents the volume of the pore with the corresponding
radius. Additional information can be obtained from the mercury ejection curves after reduction of
the pressure. According to the Young-Duper equation, work done on mercury by applied pressure
should be equal to the work that submerging the powder surface need, then the specific surface
area can be determined. The average pore radius can be estimated by the pore volume and specific
surface area. The minimum pore diameter that MIP method can test depends on its maximum
working pressure.
The actual rock mass may have pores of different scales, and open pores are mutually
communicated through the throat. When pressure increasing, mercury is pushed from large pore to
the throat then into the adjacent pore. Adjacent pore size may be larger than the throat size, but the
corresponding injected mercury volume is included in the volume of smaller pore, leading to
misjudgment.
In order to overcome the shortcomings of the conventional MIP, rate controlled MIP method is
developed10. The principle of rate controlled MIP is maintaining a quasi static(准静态) mercury
intrusion process at a very low injection speed. The main throat radius is determined by the
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pressure of breaking point, the size of the pore is determined by the injected mercury volume, as a
result, size and number of throat can be clearly reflected in the mercury intrusion pressure curve.
MIP method has many advantages and becomes the most commonly used method for pore
structure characterization. The advantages include: 1) Fast determination speed, usually every 1-2
hours for a sample；2) High measuring pressure, so it is suitable for cores with high, medium or
low permeability, and complete capillary pressure curve can be obtained for further analysis；3)
Even irregularly shaped rock samples can be tested；4) Measuring range for pore diameter is
relatively wide. Meanwhile, the MIP method has two disadvantages:1) mercury is toxic, harmful
to the human body; 2) only the features of the open pore can be reflected.
Gas adsorption method
For the pore range that cannot be measured by MIP, in particular the pores of nanometer, gas
adsorption method can be used. The procedure is: use nitrogen (N2) or carbon dioxide (CO2) as
adsorbate, gradually increase gas pressure at a constant temperature and measure the amount of the
gas that sample adsorbed, in turn gradually reduce the partial pressure and measure the
corresponding desorption amount. The pore volume is calculated by the amount of adsorbate at the
boiling temperature. Under low temperature and pressure（<-196℃,<0.127MPa) N2 isothermal
adsorption can reflect pore-size distribution of 2 ~ 50 nm. CO2 isothermal adsorption method is
used to calculate the pore-size distribution of 0.35 ~ 2 nm. Gas adsorption method is an effective
means for characterization of pore with size less than 50nm, and the application is restricted by the
narrow test range.
Micro-CT analysis
CT scan method is also known as tomographic imaging method11, and the digital geometry
processing is used to generate a three-dimensional image of the inside of the rock core from a large
series of two-dimensional radiographic images taken around a single axis of rotation. Through
integrating the projection data and iterative arithmetic, section profile of the X-ray attenuation
coefficient can be obtained, and this is the foundation of the reconstructing the CT images of core
section. CT scanning can provide pore structure, filling distribution, the particle surface structure,
and physical property parameters of rock core etc.
CT analysis is the only semi-quantitative method that capable of non-destructive imaging the
open and close pore inside the rock samples. But CT analysis has its obvious disadvantages.
Firstly, the cost of Micro-CT analysis is very high, whose price is about 20 times as high as the
MIP；Secondly, the detection range of CT analysis method is limited by the poor resolution.
Presently, the best resolution of CT instrument can only reach micron grade, and the maximum
horizon is about 1000~2000 times larger than the resolution, which implies that only pores within
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2~3 orders of magnitude can be detected. Thirdly, artificial image processing is needed after CT
imaging, and artificial threshold will affect the results to some extent because it is difficult to tell
the boundaries between porosity and entities. Fourth, high resolution requires small sample, which
is easy to cause the secondary cracks in the process of machining and then cause a deviation in test
results.
Comparison of pore structure characterize methods
In order to select a suitable method, we compare the available methods for rock pore structure
characterization. The comparison is listed in Table 1. From Table 1, we can see that the MIP
method is the only one which can obtain message of pores with size from nm to hundreds of μm.
Table 1: The experimental methods and measurements for testing the porosity
Method
Test range
SEM
>1nm
NMR
>4μm
MIP
0.003~400μm
Gas
adsorption
Micro-CT
Sample Conditions
Solid rock after
Advantages
Disadvantages
High resolution
No quantitative data
Standard cylinder rock
Direct observation and
Not suitable for samples with
sample
display
large porosity
Core block or Core
Quick, wide measuring
sheet
range
conducting treatment
Good for measuring the
0.35 ~50nm
Rock powder
>0.5μm
Standard rock sample
small pore size
Mercury is toxic
Narrow measuring range
Capable of measuring the
High cost
close pore
complex image processing
PORE STRUCTURE CHARACTERIZATION BY MIP
METHOD
Sample preparation
In order to obtain first-hand information and gain an intuitive understanding of pore structure
of rock with different lithology, we collected 10 typical types of rock samples and conducted MIP
tests in key laboratory of coalbed methane resources and accumulation process, ministry of
education, China Mining University. Samples are shown in Figure 1.
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A1
B1
A2
B2
485
A3
B3
A4
B4
Figure 1: Ten tested rock samples
Test results summary
The main test results are shown in Table 2.
A5
B5
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Table 2: MIP data of ten studied samples
No.
Lithology
Porosity
Average pore
Breakthrough radius
Density
（%)
diameter（nm)
（μm)
（g/cm3)
Location
A1
basalt
1.7908
28.5
34.4
2.2221
Nanjing
A2
granite 1
0.8127
260.8
162.9
2.2676
Nanjing
A3
granite 2
0.6686
480.1
75.1
2.1509
Nanjing
A4
metamorphic rock 1
1.1222
200.1
144.4
2.1157
Nanjing
A5
metamorphic rock 2
1.5921
129.7
37.6
2.1355
Nanjing
B1
mudstone
3.1820
20.3
41.3
2.1333
Chongqing
B2
sandstone
5.9269
63.2
45.9
2.0729
Chongqing
B3
siltstone 1
10.1074
123.3
6.46
1.9222
Nanjing
B4
siltstone 2
4.4547
37.6
28.3
2.1017
Nanjing
B5
red sandstone
8.9043
38.9
8.34
1.9384
Linyi
Remark: Breakthrough radius refers to the radius of the largest throat intruded by mercury in first
stage
The total porosity (open porosity) of samples in group A (igneous or metamorphic rock) are
relatively small, ranges from 0.67% to 1.79%, the average pore diameter and the breakthrough
radius are relatively large. The average pore diameters within the group differ considerably, the
smallest average pore diameter of basalt is only 28.5 nm, but the average pore size of A3 granite is
480.1 nm, a difference of more than ten times. Five types of tested sedimentary rocks show
different regularity. First is the relatively large porosities, the maximum of them exceeds 10%.
Second is small average pore size, ranging between 20~125nm.
At the same time, breakthrough radii of all the samples are above micron level, among which
two kinds of sedimentary rocks (B3 silty sandstone and B5 fine red sandstone) are less than 10μm,
six kinds of rock are between 10μm and 100μm, one igneous rocks (A2 granite) and one
metamorphic rocks (A4) are larger than 100μm.
Pore size distribution
In order to investigate the pore size distribution, frequency distribution diagrams were made.
The main results are shown in figure 2. The figures give the information about the volume
percentages of pores with different sizes and the scale range of the dominant pores. Assume that
the total mercury quantity is 100, the height of the histogram represents the proportion of the pore
volume within certain pore diameter range.
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Figure 2: Pore-size distribution frequency histogram of ten rock samples
Rock sample A1 is black basalt, hard and fine texture, with uniform grains and no visible
particles or pores. The initial amount of intruded mercury is large, the pores whose diameters are
larger than breakthrough radius account for 15% of total pores. After breaking through the first
stage throat, the volumes of pores with diameters between 151~36258nm show a uniform
distribution. The dominant pores concentrate between 5~50nm, whose volume accounts for about
50% of the total. Rock sample A2 is cyan granite, hard and fine texture, with visible grains. The
initial amount of intruded mercury is large too. The volume of the pores with size ranging from
523 to 25926nm changed little. When pore diameter came to about 500nm, the corresponding
proportion of pore volume increased and reached its peaking at the range of 90.7~151nm. Pores
with size less than 22.7nm were not detected. Rock sample A3 is pink granite, hard and fine
texture, with visible grains. Its effective porosity is least among the ten samples. But its
breakthrough radius and average pore diameter are relatively large, reaching at 75.1μm and 480.1
nm respectively, ranking third and first of the ten samples. The dominant pore size concentrate in
the range of 303~2119 nm, whose volume accounts for more than 40% of the total. Pores with
diameter less than 40.4nm were not detected. Rock sample A4 is a kind of metamorphic rock
evolved from granite, hard texture and coarse grains. The sample A4 has a small effective
porosity. But the breakthrough radius and average pore diameter are relatively large, reaching at
144.4μm and 200.1 nm respectively, ranking second and third of the ten samples. The dominant
pore size concentrate in range of 40.4~2119 nm, whose volume accounts for about 56% of the
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total. The pore-size distribution is widespread and without obvious peak. The smallest detected
pore diameter is about 10 nm. Rock sample A5 is a kind of metamorphic rock evolved from
sandstone, hard texture and with visible small grains. The dominant pore size concentrates in range
of 90.7~1164 nm, whose volume accounts for about 60% of the total. Pores with diameter between
303~523 nm represent the largest volume proportion, at 22%. Size distribution curve has a
significant peak. The smallest size of detected pores is about 10 nm.
The initial amounts of intruded mercury from A1 to A4 are relatively large. This phenomenon
is probably caused by the pockmarks-effect. Pockmarks-effect refers to the increase of the initial
amount of intruded mercury caused by mercury (non-wetting phase) pasting to the rough surface
of the rock pit. With the increasing pressure, the mercury will intrude into the rock pore after the
surface pits are filled. This effect causes interference on test results, but due to lack of sufficient
statistical data to quantify the interference, it is difficult to be excluded.
Rock sample B1 is a kind of brown mudstone, with small skeleton particles, muddy cement
and soft texture. The dominant pore size concentrates in range of 9.1~90.7 nm, whose volume
accounts for more than 50% of the total. Pores with the diameter of 22.7~40.4 nm represent the
largest volume proportion, at 19%. Rock sample B2 is a kind of bluish gray sandstone, with
medium skeleton particles and hard texture. The pore size distribution curve has two significant
peaks, located at the range of 303~1164nm and 22.7~151nm. Pores with the diameter of 303~523
nm represent the largest volume proportion, at 20%. Rock sample B3 is a kind of yellow porous
sandstone, with very fine skeleton particles and soft texture. The dominant pore size concentrates
in range of 303~12960 nm, whose volume accounts for about 70% of the total. The pore size
distribution curve has a significant peak in the range of 5065~7544nm. Rock sample B4 is a kind
of grey siltstone, with very fine skeleton particles and soft texture. The pore size distribution curve
has a significant peak, and the pore distribution is concentrated in the range of 22.7~90.7 nm,
whose volume accounts for over 70% of the total. Rock sample B5 is a kind of red sandstone, with
very fine skeleton particles and hard texture. The pore size distribution curve has a significant peak
in the range of 5065 ~ 7544 nm, but the pore size is widely distributed.
Subsection statistics of pore
One of the most commonly used classification standards for rock micro-pore is by pore size.
According to the classification standard proposed by IUPAC12 (International Union of Pure and
Applied Chemistry),rock pore is divided into three categories, they are micro-pore whose pore
diameter is less than 2nm, meso-pore whose diameter is between 2~50nm and macro-pore whose
diameter is larger than 50nm. Ходот presented a Decimal Classification system13 in 1961, he
classified the pore with the diameter less than 10nm as micro-pore, 10 nm~100nm as transition
pore, 100nm~1000nm as meso-pore, greater than 1000nm as macro-pore.
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Referring to the classification standards in literature, we regard the pore with diameter less
than 10nm as micro-pore, 10~1000 nm as meso-pore, greater than 1000nm as macro-pore. We
calculate the proportion of pores with different size of ten rock samples (by volume), the results
are listed in table 3.
Table 3: Pore volume percentage of ten tested rock samples
No.
Total volume (ml/g)
Volume percentage
Micro-pore
Meso-pore
Macro-pore
Micro-pore
Meso-pore
Macro-pore
A1
0.0009
0.0042
0.0030
11.00%
52.00%
37.00%
A2
0.0005
0.0012
0.0019
13.89%
33.33%
52.78%
A3
0.0000
0.0013
0.0018
0.00%
41.94%
58.06%
A4
0.0000
0.0028
0.0025
0.00%
52.83%
47.17%
A5
0.0001
0.0056
0.0018
1.33%
74.67%
24.00%
B1
0.0027
0.0107
0.0015
18.12%
71.81%
10.07%
B2
0.0008
0.0235
0.0043
2.80%
82.17%
15.03%
B3
0.0011
0.0205
0.0310
2.09%
38.97%
58.94%
B4
0.0030
0.0198
0.0010
12.61%
83.19%
4.20%
B5
0.0040
0.0200
0.0219
8.71%
43.57%
47.71%
According to Table 3, although igneous rocks (A1, A2, A3) have quiet small effective
porosities, they have wide pore-size distributions, pores with the diameter larger than 1μm account
a large proportion. The pore conditions of sedimentary rock are related to a variety of factors, such
as the skeleton diameter, the deposition conditions etc. In most cases, the meso-pore with diameter
of 10 nm~1000 nm account for a large proportion in pore volume. But when the deposition is not
sufficient, (such as sample B3 whose texture is soft and not being full compacted), or skeleton
particles is relatively large (such as sample B5), the macro-pore account for a larger proportion in
pore volume. The pore distribution of metamorphic rock is more complex, not only depending on
the rock characteristics before modification, but also being affected by metamorphism process
pressure, temperature, and recrystallization conditions.
DISCUSSIONS
Pore structure of other rocks
C. De Las Cuevas5 tested the pore structure in rock salt and found that, there was good
agreement between the porosity measured by gas adsorption and mercury injection porosimetry.
Gas adsorption confirmed that the results obtained at very high pressures using mercury injection
porosimetry are valid. Furthermore, the porosity measured on isoparaffin saturated samples
reflects the absence of very large macro-pores, which could not be detected with low pressure
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porosimetry. The pore structure in rock salt is very complex, exhibiting a multiple peaks
distribution. Macro-pore, micro-pore and infraporosity were represented by pores varying between
60 and 7 μm, pores with sizes between 800 and 300 nm, and pores of around10nm size
respectively. Moreover, macro and micro-pores exhibited a fractal pore-surface structure, whereas
infrapores had a non-fractal structure. Among the 10 tested samples presented in this paper,
sample B2 and sample B5 demonstrate double peaks distribution, and the pore-size distribution
frequency histograms of the other eight samples are single peak curves. The comparison implies
that the pore structure of rocks with different lithology has little similarity and one should confirm
the rationality when using the method of analogy.
V. Cnuddeand et al6 studied microstructure of concrete and natural building stones (quartz
sandstone and bioclastic limestone). They found that, in most cases, the MIP systematically
generates higher total porosity values. The main reasons for these different results can be
explained by the different measurable pore-size range. Test range of MIP basically covers all of
the pore size inside specimens. The water absorption determines pores larger than 100 nm, while
micro-CT visualizes pores larger than 10μm. The specific difference depends on the specific pore
size distribution. Surprisingly, the HPC (high performance concrete) breaks the rule. Its porosity
measured by water absorption was larger than that measured by MIP. Analysis showed that, not
only the total porosity varied greatly, but also the porosity in the overlapping pore-size range are
significantly influenced by material properties and pore structure characteristics. For artificial
material like HPC, porosity with the pore size ranging from 10 to 60μm measured by MIP is much
less than that measured by water absorption. It is speculated that there are many closed pores and
pores with size greater than 60μm in casting type manmade material, resulting in MIP failed to
measure the complete data. Similar deviations happen to porous rock with many close pores, such
as volcanic gas reservoir and volcano bubbles rock14.
Discussion on Micro-CT analysis
Micro-CT is widely used method for pore structure characterization after mercury intrusion
porosimetry. JuYang15 et al. (2008) studied pore scale and space distribution characteristics of red
sandstone with porosity between 22.9% and 23.8% using CT scanning method. They reconstructed
the three-dimensional porous structural model of sandstone. Since the limit of device resolution,
they studied the pore with the diameter no less than 50μm. Li Jiansheng16 et al. (2010) scanned
clay rock in coal stratum non-destructively by micro-CT. They came to a conclusion that with the
increase of the pore diameter, the porosity of clay rock in coal stratum is reduced by the negative
exponent rule.
However, the study based on Micro-CT analysis remains some arguable aspects. According to
the theoretical basis of CT scan, CT image is the reflection of the attenuation of radiation passed
through the sample. It is impossible to distinguish pores and base material directly. When
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processing the obtained image, the selection of gray threshold determines the test results of pore
structure directly.
Ju Yang et al15. (2008) compared the porosity calculated by CT image that processed by
different thresholds with the porosity obtained by helium porosity analyzer, and chose the
thresholds which made two porosities equal for binary processing. The process confuses two
important concepts. First, the porosity calculated by CT image that processed by different
thresholds is the total porosity (including open and close pores), but the porosity obtained by
helium porosity analyzer is the effective porosity. The thresholds which make two porosities equal
cannot represent the actual pore boundary. Second, the resolution of the CT scan can only identify
the porosity of the micron magnitude, and many test data show that the volume of the rock pore
with the diameter above micron level only accounts for a small part of the total pore volume.
Based on the above understanding, pore data obtain by Micro-CT should be considered with care.
Relationship between pore structure and engineering
properties
The engineering properties of rocks are influenced by the pore structures. Many experiments
have been conducted to investigate the intrinsic relationship between the meso structure and macro
properties. A. A. Al-Harthiet al17 (1999) investigated the influence of the porosity on the
engineering properties of vesicular basalt in Saudi Arabia, and established a statistical quantitative
relation. N. Hudyma et al18 (2004) reported that the compressive strength and elastic modulus of
lithophysae-rich Topopah Spring tuff specimens decrease as the porosity increase. Yang
Yongming et al19 (2010) reconstructed the three-dimensional porous structural models of
sandstone and numerically studied the relation between the pore distribution characters parameters
and the failure process of Brazil disk. The results indicated that porosity affected the failure states
of disk models greatly. Lin Zhihong et al. 20 (2010) experimental studied the influences of physical
indices and microstructure parameters on strength properties of red stone from Western Hunan,
and their results indicated that the UCS showed a negative exponential relationship with porosity.
Ju Yang et al. 21 (2010) established 3D finite element models of rocks with varied porosities and
investigated the dynamic behaviour of porous rock samples by numerical experimentation. The
results showed that the dominant deformations are the failure of matrix around pores and
coalescence of existing micro cracks and the energy dissipation rate increased linearly with the
increasing of porosity for a constant impact velocity.
The existing investigations provide us a preliminary understanding on the relation of
micro structure and macro properties of engineering rock. However, the studies are statistical or
numerical, and the mechanism of the influence of pore structure is still behind the scenes. Zhou
Xiaoping et al22,23 established a non-Euclidean model for the analysis of failure process of deep
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rock mass, with an emphasis on the density and the length of microcracks. But they did not give
the describing method or measureable index of rock. More and more researchers realize the
importance to connect the macro properties with the micro structure of rocks. In view of the above
mentioned facts, the investigative work on the relation between pore structure and engineering
properties should be enhanced.
CONCLUSIONS
Rock is a kind of natural porous material. The pore structure characteristics of rock are very
important in many engineering fields. In this paper, the test methods for pore structure
characterization were reviewed and the application scopes of the methods are presented. Ten rock
samples with different lithology are tested by mercury intrusion method. The results of total
porosity, average pore diameter and breakthrough radius are given, and the pore size distributions
of samples are demonstrated by frequency distribution diagrams and detailed analyzed. Test results
indicate that the igneous rock samples have small effective porosities and wide pore-size
distributions. Compare to igneous rock samples, sedimentary and metamorphic rock samples
showed lager discreteness. Pore size distribution curves of the tested samples are single peak
except sample B2 and B5. The test results imply that the pore structure of rocks with different
lithology has little similarity. Relative researches on pore structure of rock and its characteristic
method are also discussed.
ACKNOWLEDGEMENT
The authors would like to acknowledge the financial support from the National Key Basic
Research Program of China (Grant: 2013CB036005), and the National Natural Science Funds of
China (Grant: 51304219). The authors also thank the financial support of State Key Laboratory for
GeoMechanics and Deep Underground Engineering, China University of Mining & Technology
(Grant: SKLGDUEK1305) and China Postdoctoral Science Foundation, which collectively funded
this project.
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