J. Cent. South Univ. Technol. (2007)02-0220-05

DOI: 10.1007/s11771-007-0044-x                                                                                             

Pore structure of ore granular media by

computerized tomography image processing

WU Ai-xiang(吴爱祥)¹, YANG Bao-hua(杨保华)², XI Yong(习 泳)², JIANG Huai-chun(江怀春)²

(1. Civil and Environment Engineering School, University of Science and Technology Beijing,

Beijing 100083, China;

2. School of Resources and Safety Engineering, Central South University, Changsha 410083, China)

Abstract: The pore structure images of ore particles located at different heights of leaching column were scanned with X-ray computerized tomography (CT) scanner, the porosity and pore size distribution were calculated and the geometrical shape and connectivity of pores were analyzed based on image process method, and the three dimensional reconstruction of pore structure images was realized. The results show that the porosity of ore particles bed in leaching column is 42.92%, 41.72%, 39.34% at top, middle and bottom zone, respectively. Obviously it has spatial variability and decreases appreciably along the height of the column. The overall average porosity obtained by image processing is 41.33% while the porosity gotten from general measurement method in laboratory is 42.77% showing the results of both methods are consistent well. The pore structure of ore granular media is characterized as a dynamical space network composed of interconnected pore bodies and pore throats. The ratio of throats with equivalent diameter less than 1.91 mm to the total pores is 29.31%, and that of the large pores with equivalent diameter more than 5.73 mm is 2.90%.

Key words: ore granular media; pore structure; X-ray computerized tomography; image processing                             

1 Introduction

Solution mining technology is researched and applied widely in China, particularly heap leaching, which has become an effective and economical method for treating poor ore, tailings and waste ore containing valuable metals, such as uranium, copper, gold and silver. The efficiency of heap leaching depends on two aspects: one is the dissolving ability of solution to available minerals; the other is the permeability of solution in ore heap. These two aspects determine the recovery and leaching rate of available metals. However, the permeability of solution in ore heap becomes the crucial factor when the dissolving ability of solution to available metals is definite. Lots of experiments and theoretical researches indicate that the porosity of ore heap plays the main control role in the percolation of solution^[1-4]. Porosity is a macro-parameter of the leaching system, which is measured in laboratory with ore samples generally. In order to understand the percolation law of solution in leaching heap deeply, it is necessary to study the spacial distribution of porosity and pore geometry and to realize the visualization of pore structure, so as to provide precondition for studying the visualization of solution flow. In this paper, the images of pores among ore particles at different heights of leaching column were scanned by X-ray computerized tomography (CT). There is no report about the experimental method using X-ray CT to obtain the images of ore granular media in leaching column in our country while it has been done in foreign countries in last several years^[4-5].

2 Experimental

2.1 Principle of X-ray CT

X-ray of CT can penetrate nonmetal materials and the penetrating ability of X-rays with different wavelengths is different. The ability of absorbing the same X-ray to different materials is also different. The higher the density of the material is, the stronger the absorbing ability is. During X-ray penetrating the material, its intensity is attenuated by exponential correlation. The density of material is embodied by the attenuation coefficient of material to X-ray. When X-ray penetrates the detected object, its intensity follows the following equation: where I₀ is the intensity of X-ray before penetrating object, I is the intensity of X-ray after penetrating object, μ_m is the absorbing coefficient of unit mass detected object, ρ is the density of material, and x is the penetrating length of incident X-ray.

CT makes the information of materials with different density at certain lay display as high re- solution digital images through computer images reconstruction^[6-7].

2.2 Experimental equipment

The experimental equipment is composed of an organic glass column for leaching experiment (height is 500 mm; diameter is 50 mm) and the X-ray CT machine, shown in Fig.1, whose type is SIEMENS SOMATOM Balance.

Fig.1 X-ray CT machine used for leaching column scanning

2.3 Experimental procedure

Firstly the leaching column was filled up with ore particles with different size grades. Table 1 shows the ore particle size distribution. Secondly the porosity of ore samples was measured to be 42.77％with general method in laboratory^[8]. Lastly CT machine began to scan the top, middle and bottom zone of leaching column, respectively. The length of each scan zone was 5 cm. The thickness of each scan layer was 2 mm. There were produced three series of cross sectional images; each series included 25 cross sectional two-dimensional images. The scanning sequence number was 1 to 25 respectively from top to bottom.

Table 1 Ore particle size distribution

3 Pore structure analysis

3.1 Pre-processing CT images

Fig.2 shows entirely the pore structure images of corresponding positions at different heights of leaching column.

Fig.2 Overall view of leaching column and two-dimensional tomographic images corresponding to relative position of column

Since the densities of pore space and ore particle are different greatly, the spatial boundary of them can be established easily. In order to analyze the pore geometry, it is necessary to pre-process the obtained CT images^[9-10]. Fig.3 shows the image pre-processing procedure: 1) selecting a rectangle zone with the same size from each original two-dimensional image for analysis; 2) transforming all gray images to binary particle images with the same threshold; 3) inverting the binary particle images to binary pore images.

3.2 Porosity calculation based on image analysis

For the ore granular media in heap leaching, porosity is an important parameter to reflect its property. The porosity of ore granular media means the ratio of pore space volume among ore particles to the total volume of the media^[11]. It can be expressed as the following equation:

              (2)

where  is the porosity of granular media, %; V_g is the total volume of granular media, m³; V_f is the volume of pore space, m³.

The porosity of ore granular media can be measured in laboratory generally, which is a macrocosmic parameter. In order to get the porosities of different zones in leaching column, the image process method was used to calculate them. After image pre-process, the binary pore images of scanning zones located at different heights are obtained, which is shown in Fig.3(c). Apparently, porosity is the ratio of white area to the total area of the image, namely the ratio of pixel number of white area to the total pixel number of the whole image. It is often called surface porosity^[12-13]. Table 2 lists the porosities of ore granular media located at different zones of leaching column and their average values.

Fig.3 CT image pre-processing procedure

(a) Original gray image of selected zone; (b) Binary particle image (pore is black); (c) Binary pore image (pore is white)

 Table 2  Surface porosities at different heights of leaching column  (%)

Fig.4 shows the varying trend of porosity with scanning height. The figure indicates the porosity has spatial variability, which decreases from the top to the bottom. The reasons are as follows: 1) there is natural segregation during filling ore; 2) the smaller particles move in the void space among bigger particles; 3) the density is higher at bottom because of high pressure caused by gravity. The porosity distribution of ore particles in leaching column is similar to that of the actual leaching heap. In addition, the total average value of surface porosity can be obtained to be 41.33%, which is lower than the measured value (42.77%). The reason is that the measured value includes the microporosity inner ore particles, which occupies 1%-3% of the total porosity.

Fig. 4 Variation of porosity with scanning height(a) Top zone; (b) Middle zone; (c) Bottom zone

3.3 Pore geometry and connectivity analysis

The ore granular media is stacked with different sizes of ore particles in heap leaching system, so its pore structure is very complex. It is necessary to process the obtained binary pore images further so as to analyze the pore geometry and connectivity. The brim tracing technology can be used to confirm the brim of pore space so as to confirm the pore geometry. Skeleton extracting technology can be used to get the skeleton of pore space so as to show the topological property of pore space. The image processing results are shown in Fig.5.

Fig.5 Pore brim tracing and pore skeleton extracting(a) Binary pore image; (b) Traced pore brim; (c) Extracted pore skeleton

gig.5(b) indicates that the pore geometry is very complex, the pore shapes are various and its size distribution is large. Fig.5(c) indicates that most of the pores are interconnected and the topological structure is a spatial network with three dimensional pore body and pore throat. Fig.6 shows the two dimensional pore structures schematically^[8]. It indicates that the pore throat plays bottleneck role in the solution flow and its size determines the permeability. In addition, the ratio of pore throat to the total pores and the size distribution of all the pores can be estimated with the erosion and dilation operation of image process. Fig.7 shows the two successive stages of erosion/dilation operation with random layer. The size distribution of pores is shown in Fig.8. If take the pores with equivalent diameter less than 1.91mm as throats, the percentage of throats to the total pores is 29.31%; the percentage of the pores with equivalent diameter less than 3.82 mm is 77.15%; and the percentage of the large pores with equivalent diameter more than 5.73 mm is 2.90%.

erosion/dilation (E/D)Binary pore image; (b) Image after first stage of E/D; (c) Image after second stage of E/D

In order to show the inner structure of ore granular media more clearly, the visualization of inner pore network is realized based on the three dimensional reconstruction of original successive scanned two dimensional CT images, as shown in Fig.9. Research results indicate that the proportion of dead pores volume in lots of porous media is not more than 1%, that is to say, pore connectivity reaches 99%^[14]. Of course the ore granular media stacked loosely follows this property in the same way before bio-leaching.

Fig.8 Pore size distribution of ore granular media

Fig.9 Reconstructed three dimensional image

The ore granular media in heap leaching system is similar to other porous media, which is full of pores. However, it is different from them, because its inner pore network is a dynamic structure. With the continuous effect of gravity and the solution flow, particularly the bio-leaching processing, the ore particles are damaged gradually, so the inner pore network evolves continuously. The pore network evolvement law and its effect on seepage properties of heap leaching system are the focus of further study.

4 Conclusions

1) The porosity of ore granular media with various sizes in leaching column has spatial variety through image processing, which decreases appreciably along the height of the column. The porosity obtained by image processing is little lower than the measured value, which consists with the practical condition. The results indicate that image processing method can effectively analyze the porosity of ore granular media in leaching column and its spatial distribution property.

2) The pore structure of ore granular media is characterized as a dynamical space network model composed of interconnected pore bodies and pore throats, where the size distributions of throats control the solution flow efficiency.  

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Foundation item: Project(2004CB619205) supported by the National Key Fundamental Research and Development Program of China; Project(50325415) supported by the National Science Fund for Distinguished Young Scholars; Project(50574099) supported by the National Natural Science Foundation of China

Received date: 2006-05-21; Accepted date: 2006-07-27

Corresponding author: YANG Bao-hua, Doctoral candidate; Tel: +86-731-8830851; E-mail: yangbaohuar2004@126.com

(Edited by LI Xiang-qun)