May 05, 2024

Study on Block Prediction and Control Technology of Natural Caving Method in Yechangping Molybdenum Mine

The Yechangping molybdenum deposit consists of two parts: the upper ore body and the lower ore body. The scale and reserves are large. The ore body is 800m long from east to west, 600m wide from north to south, and 6.39~236.04m thick. It is a large-scale fine vein disseminated molybdenum deposit. .
Mine was founded in April 1996, in the second half of 2010 by the China Gold Group Holdings acquisition, it plans to mine the recent construction of a large scale is 20000t / d, long-term construction scale of 60000t / d of non-ferrous metal underground mines. Currently, the deposit is operated by China National Gold Group Zhongyuan Mining Co., Ltd. The deposit is jointly developed by the main flat raft + blind inclined well. The main mining methods are natural caving mining method and segmented medium-deep hole forced caving mining method.
The molybdenum ore body is jointly controlled by two groups of fractures, and two main ore bodies are symbiotic, which are the upper I ore body and the lower II ore body. The upper ore body is located above the granite porphyry and has a round cake shape. The shape is relatively regular. The center of the ore body is high, and it is inclined at 10° to the surrounding. The ore body is 820m long, 590m wide and 6-230m thick. There are two layers of ore bodies; the lower ore body is located under the granite porphyry, the thickness is 6 ~ 300m, the top of the ore body is dolomite , and the bottom is dolomite or potassium long granite porphyry. The ore rock is hard, compact and brittle. Due to the late structure and weathering, the rock is broken and the stability is poor. It is difficult to manage the top and bottom plates, and it is prone to bad engineering geological phenomena such as roof collapse and slump.
1 block control technology research 1.1 Factors affecting the rock mass degree With the deep research on the natural caving law, it is clearly recognized that the factors affecting the rock mass are mainly as follows:
(1) The distribution and quantity relationship of joints.
(2) Ground stress state. Includes raw ground stress and secondary stress conditions.
(3) Grinding action. The collapse of ore occurs during the process of ore discharge, causing secondary or non-human crushing of the ore that has collapsed.
1.2 Block prediction theory The methods for predicting the rock mass can be divided into the following three categories: rock quality index method, image method and joint network simulation method. The rock quality index method is a method for qualitative evaluation of the collapse and collapse rock mass according to the rock mass characteristic parameters. It is a relatively close-to-experience forecasting method, mainly for the preliminary qualitative evaluation of the caving rock mass. The basic idea of ​​the image analysis method is to obtain the two-dimensional projection contour of the rock mass on the photographic plane after segmentation of the explosion image, and then realize the expansion from two-dimensional to three-dimensional through a certain reconstruction technique to obtain the three-dimensional block. The blockiness distribution. The joint network simulation method is a statistical analysis result based on the joint state of the joint space and the condition of the joint surface. Monte Carlo simulation technology is used to simulate the cutting of the rock mass in the joint, and the mechanical knowledge of the caving and ore-out process is used to predict the caving. The block distribution of the ore.
2 The ore body natural block degree prediction uses the Makeblock ore block prediction software to predict the ore block size, according to the ore body, the upper and lower plate partition, the different collapsibility category division and the overall evaluation area of ​​the oxidized ore body to the mine in the night Changping molybdenum ore area. The rock performs the original block prediction. When the block prediction is performed using the Makeblock software, the number of samples for each joint plane is set to 30000, and the number of block samples is set to 10000. After several sampling experiments, it was found that when the number of blocks was set to 10000, the volume percentage of extra large blocks was below 3%, and the sampling results were relatively stable. When the number of sampling blocks is set to 10000, the average six faces of each block is calculated, then 60,000 joint faces are required, and each joint face can serve as the face of two blocks, so the number of blocks of the joint face is set. More than 30,000 can be.
According to the statistical analysis of the block prediction results, the percentage of large blocks on the grid with a block size greater than 0.91m is 29%, and the large blocks with a block size greater than 1.4m account for 16%, with a partial second The amount of crushing, but the probability of blockage of the ore discharge is not large. The equivalent size distribution curve, the shape coefficient distribution curve, and the volume distribution curve are shown in Figures 1 to 3, respectively.
Tu 1
Tu 2
Tu 3

From Fig. 1, the bulk rate of the lower part of the ore body is relatively large, while the large block rate of the upper plate is the smallest, and the large block size varies between 2.0 and 2.28 m, which is relatively close. The statistics on the equivalent size sieve show that the block size of the original ore rock is larger than 0.91m, accounting for 59% of the ore body, 49% of the upper plate, and 59.8% of the lower plate; Blocks with a block size greater than 1.2 m accounted for 37% of the ore body, 26.1% of the upper plate, and 35.9% of the lower plate.
From Fig. 2, the shape coefficient distribution of the three is not much different, and the main distribution is concentrated between 0.018 and 0.19. According to the comparison standard of the relevant parameters, the majority is in the shape of a disk and a block. The block size of the lower plate is slightly larger than that of the ore body and the upper plate, which is consistent with the research results of the qualitative evaluation block of the RMR value. The lower part of the lower plate is larger, the rock is stable, which is conducive to the construction safety of the project. However, if the upper part of the plate is small, it is easy to fall and fall off, which is more likely to cause the original depletion in the stope. Therefore, it should be strengthened. Mine management, strict control of depletion.

From Fig. 3, the block size of the lower plate is large, the block size of the upper plate is small, the blockiness of the ore body and the block degree of the lower plate are relatively close, and the whole is smaller than the upper plate, and from the volume of the block, the mine The maximum volume of the bulk of the body is slightly smaller than that of the upper ore body, and the maximum volume of the upper and lower plates is 1.0~.
Change between 3.5m3.
3 block control process After the ore body damage is affected by external force, it first expands along the original fracture surface, and the ore collapse degree is closely related to its joint development. Therefore, by controlling the size of the bottom area of ​​the stope and the amount of voids in the caving area, the natural caving range and speed can be controlled. By controlling the caving speed, the stress time and the caving block in the rock mass can be controlled. .
In summary, the size of the caving ore block is affected by the natural blockiness factor of the joint crack cutting, prolonging the caving time, promoting the crack extension and developing new secondary cracks, and secondary cutting the rock mass will control the caving ore block. The most effective method. At the same time, control the mining volume and the mining speed of the stope, adjust the space height between the surface of the heap in the caving area and the exposed surface of the roof, and if necessary, apply the towing force to the exposed roof to delay the time for the rock to leave the ore body, Indirectly control the rate of collapse and improve the degree of collapse.
4 Conclusions (1) Based on the spatial distribution law of the structural plane and the mutual cutting relationship, the cutting structure of the rock mass and the distribution of the size and shape of the rock mass formed by the cutting are simulated according to the statistical principle. The spatial geometric parameters, the geostress state and the motion process grinding effect of the joint system are based on the block prediction model established by the Monte Carlo method and the W.Glivenko's large number theorem. The BorlandDelphi5.0 software is used for analysis and calculation. An effective prediction method and means for rock mass.
(2) Analysis of the natural collapse block prediction model shows that the cumulative percentage on the block sieve with the equivalent size greater than 0.91m is 29.8%, and the cumulative percentage on the block sieve greater than 1.4m is 16.1%. The ore body and the lower plate have larger block sizes, and the upper plate has the smallest block size. The maximum equivalent size of the three is varied between 2.0 and 2.28 m. Among the original ore blocks, the equivalent size is greater than 0.91m, accounting for 59% of the ore body, 49% of the upper plate, 59.8% of the lower plate, and the equivalent size of the block larger than 1.2m. Body, mineral body accounted for 37%, accounting for 26.1% in the upper plate, and 35.9% in the lower plate. These data are advantageous for equipment selection and production planning.
(3) The prediction and control process of natural caving block is a theoretically strong and involved work. Its variability and uncertainty determine the complexity of the problem, so that the theoretical analysis is better in line with reality. In the future production practice, we must constantly explore and innovate and constantly improve.


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Article source: Mining Technology; 2017.17(3)

Author: Chen Jiangchuan, Era; China National Gold Group Zhongyuan Mining Co., Ltd., Sanmenxia City, Henan Province 472000 Li Weiming; Changsha Institute of Mining Research Co., Ltd., Changsha 410012

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