optimization study of a surface mine and grade monitoring...
TRANSCRIPT
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Optimization study of a Surface Mine and Grade
Monitoring using SURPAC
Dr. H.K.Naik1
Dept. of Mining Engg., NIT
Rourkela, India
Pritish Das2
M.Tech. (Dual Degree), CCL
Ranchi, India
Abstract — As the world is developing, the raw materials
demand has been increasing day by day. To fulfill both supply and
demand, a more technologically advanced and automated method
of production is required. Since the raw materials are non-
renewable and have taken million years to form, so these resources
should be used rationally, and maximum level of extraction should
be acquired with least mining waste side by side maintaining all
safety and regulations judiciously. This paper aims at estimating
the reserve of a typical iron ore mine using different techniques,
such as solid modeling and block modeling techniques. Different
optimization methods are used for monitoring the grade of the ore
body by using SURPAC software. Moreover, the ultimate pit limit
has also been determined with the help of which the shape of the
pit has been optimized using different slice plans through this
software so that the pit does not cross the lease boundary of the
mine. Besides this an attempt has been made to mine the blocks of
the ore body graphically followed by generation of a work order in
which the required tonnage of ore production ordered by the mine
management can be fulfilled at any point of time during the
development of the pit.
Keywords— SURPAC, Solid modeling; Block modeling; Ultimate
pit limit; Slice plans
I. INTRODUCTION
Minerals and metals have been essential components for the growth of a country. The tremendous growth and fast increasing demand of finished products have put considerable pressure on the parent industry (mining) to continue the supply of raw materials continuously and quickly. Ore deposits can be categorized into three types: massive deposits which are very large deposits; vein deposits; lode type deposits; and horizontal stratified reserves of sedimentary origin with a thin/thick covering of overburden.
Mine planning is done by determining the total ore reserve and the average grade of the deposit. Time to time mine scheduling is done to know the place of extraction at a particular point in time. The mine has to be ready to supply any grade of ore required by the management through ore blending. Opencast mine planning is conducted by first generating a representative model of the ore body and then dividing it into several blocks and sub-blocks known as block modeling with the help of which slice plans are
generated. Using these slice plans the ultimate pit limit is decided, and the pit is designed. While designing the pit, it should be kept in mind that the stripping ratio should be economical in order to minimize losses.
The geological blocks generated through block modeling are used to determine the grade of each block through different grade estimation techniques. By referring the grade of each block the average grade of the ore body is calculated, and the total ore reserve can be determined as:
Total ore reserve = Volume of the ore body * Tonnage factor * Average Grade of the ore body
Problems in optimization
Opencast mine planning is a multi-parameter optimization problem where more than one parameters are involved in open pit production. These parameters are inter related where any change in one parameter affects all other related parameters. Therefore without the correct value of one parameter, the determination of next parameter is not possible. Mine life is decided by the time taken to extract all the resources present in the ultimate pit limit design. For this, a cut-off grade is fixed based on various commercial and industrial factors. Before cut-off grade is decided, an average grade of the ore body is calculated from the reserve estimated through modeling techniques. Finally, an ultimate pit is designed so that maximum ore is extracted within the minimum time period and all these should be done abiding proper legislation norms. Grade monitoring is a crucial part of planning of an open cast mine as this is the most variable factor.
SCOPE OF WORK
With steady technological development in mining industry automation of machinery and fast computation techniques with the use of various softwares to meet the demand of the society has proved to be much safe as well as time-saving. This paper provides an insight of software's capability in reserve determination which can be proved beneficial in real time mine planning. The introduction of this software in the mining industry has made calculations easy for determination of various parameters such as
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• Grade estimation
• Reserve Estimation
• The life of the mine
• Long term and short term mine planning, etc.
This can be helpful to top management people as
resources can be easily modeled and are easy to view and
analyze and hence steps can be taken for ensuring steady
production.
AREA OF STUDY
The studied area for this project is an opencast iron ore mine.
The geological data of a limited area has been provided for
this project work.
Objectives
• To generate a graphical representation of the ore deposit from borehole data and estimate its reserve and grade.
• To compare among the two applied grade estimation techniques, i.e. Inverse Distance, Nearest Neighbor and Ordinary Kriging, and analyze the estimation technique that is more effective
• Optimization of an open pit through Block Modeling Technique.
In order to fulfill these two aspects, ample amount of data has been collected in the form of raw data, grades and assay values, mine plans, etc.
METHODOLOGY
In order to fulfill the above-said objectives, the following methodology has been adopted –
i) Literature review – Collection of all the past research works done by various academicians/researchers/scientists both national and international.
ii) Data collection and preparation – Mine Survey data has been collected to import to the software (SURPAC) for the preparation of geological database.
iii) Experimentation – The experimentation was carried out in different stages:
• Preparation of geological database.
• Displaying of drill holes from the imported data.
• Sectioning of the drill holes.
• Formation of an ore body based on the position of drill holes.
• Estimation of the reserve of the ore body.
• Mathematical and Statistical analysis.
• Grade estimation through various methods.
• Determination of cut-off grade of the ore.
iv) Designing and analysis –
• 3-D Block modeling of the ore body and applying cut-off grade for the identification of ore.
• An open pit for the extraction of the ore body.
• Mining blocks graphically.
Results and Discussions
Generation of Geological Database :
In Surpac uses the following data which has to be
imported: Assay, Survey, Collar, Geology. The whole
project has been carried out using these data only. These data
are in the form of excel files which are imported into
SURPAC. Out of these four files, Collar and Survey are
known as Mandatory tables, and Assay and Geology are
known as Optional tables.
The data of borehole exploration has been imported from
excel files to the software and a geological database has been
created. Once the whole data has been inputted in the
software, the drill holes can be viewed as shown in the
figure. Once the drill holes have been displayed, the geology
patterns and the lithology are distinguished by using color
variants. The mineral concentrations down the borehole are
distinguished with different colors. These values have come
from the assay table. As the ore body has a lithology of
hematite ore, the major mineral is iron. Once the borehole
has been displayed, the surface condition has to be known,
and the ore body has to be created to know the volume of ore
which is also known as reserve estimation after compositing
has been done. The surface conditions cannot be known from
the boreholes.
Surface Modeling
The string file has been created from the collar data excel
file which consists of X- Easting, Y- Northing, Z- Reduced
level. The string that is created is saved in the string file e.g.
filename.str. While saving a string, it has to be noted that
every string has a unique string number.
Once the string has been generated, the Digital
Triangulated Model (DTM) is developed using that file. This
normally shows the elevation and surface conditions of the
area where the boreholes have been drilled. Thus it gives a
somewhat as rough image on the type of surface to be
encountered when mining has to be done. Once DTM has
been created, contouring may be developed to know the
elevation intervals on the surface. The surface has been
created as DTM which only takes string file (.str) to create
the surface model. Thus a string file has been created from
the drill holes, and then a DTM is created. The above process
is known as Surface Modelling.
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Generation of Geological Database
Figure 1: Creation of geological database (Assay)
Generation of Geological Database:
Figure 2: Image displaying boreholes
Surface Modeling
Figure 3. Image displaying the generated surface model
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Solid modeling :
This process has implemented the development of the ore body. The ore body has been developed from the boreholes through repeated sectioning and digitizing of the boreholes. To prepare an ore body, a number of sections are developed, and all the sections are joined together using a triangulated method to create an ore body. Before the development of the ore body, it should be known that all the boreholes have not been useful in the determination of ore body as they contain less percentage of mineral concentration that has to be mined. The determination of ore body is totally dependent on the user of the software. This decides the amount of dilution and the extent of the pit. During sectioning, initially a section has been defined and then a row of boreholes has been set for digitizing. Through digitizing the volume of ore to be mined has been determined. Some boreholes have been exempted of sectioning. This means that the grade of the mineral which will give profit, is very less or absent. Thus it could increase the cost of extraction adding to the overall cost of mining. After sectioning a row of borehole the section has been saved, and then the sectioning of next row is carried out. All the section files have been saved in the same file overwriting it each time. After sectioning of all the boreholes has been done and saved which is in the form of string file. These are the segments which have been developed by the sectioning and digitizing of the boreholes. The next work is the development of the required ore body by joining the segments, but before this, the inside of the hollow segment has been triangulated and then between the segments has been triangulated to create the final ore body. But once the triangulation job has been done it requires validation so that it does not have any error in triangulation. Sometimes triangulation gives an error due to the creation of open segments. The triangulation inside the segment has ensured that the segment is closed. If the validation becomes false, the area and the volume of ore cannot be determined. Thus the ore body has to be validated. Figure 5 shows the process of triangulation and development of final ore body. A 2D or 3D grid system can also be implemented to know the layer extents of the ore body where Max Z value- 978m and Min Z value- 1260m. Once the ore body has been developed and validated, the calculation of area covered by the solid ore body and the volume of ore can be determined, and the report has been saved in ‘.pdf.' format or any other text format that the software provides.
Solid modelling :
Figure 5. Image showing solid model of the ore body
Table 1: Showing area and volume of the solid model
Analysis of drill holes intersecting the ore body:
After the solid modeling has been done, the required ore body has been developed. But this ore body does not cover every drill hole and its full extension. Thus another field has to be added to our database where the part of the drill hole where the ore body has intersected is marked only. This will be ore zone, and it has been saved as a string file. For the creation of the ore zone, only ‘assay’ table or file is required. After the string file has been created, it will show white line as shown in the figure. The assay table where the new field has been created as ore zone can be viewed, and only those borehole ids has been marked as ‘ore’ which has intersected the ore body. A report file has also been created where it has shown all the hole id and its extents which have intersected the ore body.
Figure 7: Image showing sections of boreholes intersecting the ore body
Table 2: Showing ore zone extension
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Block Modeling
Block model has been generated to take care of the influence of the surrounding boreholes to an unknown point. Specifically, it has helped in grade and reserve estimation of the ore body. After the block model has been created, the size of the block is an important criterion which has to be decided. It is advised that block size should be around 1/3rd to 1/4th of the borehole spacing. In this model the borehole spacing is 100m. The size of the block model to be created or its dimension depends on the layer extent of the ore body that has been developed. Its extent can be inquired from the ‘Inquire’ option in the main menu or the string file of the ore section that was generated before can be used and imported. The block size has been taken in meters as Y-20, X-20, and Z-10.
The dimension of Z has been given keeping in mind the height of the bench. The sub-blocks dimensions have also been given the half of the original block dimension. A block model has been created with file name ‘block.mdl’.
Figure 9: Image showing the parent block model
The model in Figure 9 is a block model with no constraints added in it. It only contains the extent of the ore body. To create a block model of the ore body, constraints must be added to it which is the solid model itself. After the constraint has been added a block model of the ore body is created. A full body volume analysis has been done of the created block model to compare between the volume of the ore body which has been determined earlier and the volume of the block model of the ore body. It has been strictly advised that the difference in the volume of block model and the solid model should not exceed 1%. The above block model is also known as parent block model. Here to see the ore body block model, the constraints must be added every time. If saved also it cannot be saved as the constraints have not been inputted in the database of the block model. Therefore a constrained block model has been created taking the input from the solid ore body model and saved to get the block model in the shape of the ore body. The block model has been saved with name ‘iron.mdl’.
Figure 10: Image showing constrained block model of the ore body
Figure 11: Image showing the volume of block model
Statistical Analysis
Figure 12: Image showing statistical analysis of iron
Compositing
For grade value estimation the block model should be inputted with the assay values of the mineral, but they are in the different database which is Geological Database. So the data has to be extracted from the database in a string file, and this file should be used in the 1st model of estimation. Here the samples at equal interval should be normalized. One block will take samples at an equal interval of different samples from different boreholes by using the string file generated after compositing has been done. While inputting attributes in the table while compositing the description field number assigned to each attribute should be remembered as it will be needed for future use. Once the string file has been generated it is used for the grade estimation of the block model. Once the process has been completed, the attributes for each block can be viewed by using the option in the drop-down menu.
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Figure 13: Image showing down the hole composite of the ore body
Variogram Modeling
Using variogram modeling as a second model of ore body grade estimation, the block model is estimated for the grade. The input file is the composite file whose variogram is to be created. The variogram is saved and is used for grade estimation creating new attribute fields and storing the grade value in that field. This method of estimation is known as ordinary kriging method. After the block model has been estimated different constraints as per our choice can be viewed and inputted, and the output image has been shown in the Block model.
Figure 14: Image showing variogram model of the ore body
Block model summary and report
Once estimation of the ore body has finished the report of the ore body has been generated which shows the volume, tonnage, average grade of the minerals of the ore body. Summary reports have also been generated as per attributes inputted which include determining reserve as per depth and different mineral grades.
Table 3: Ore Reserve estimated through three methods
Slice plans or slicing
Slicing refers to cutting the ore horizontally at a definite interval. String files have been generated containing slice
plans of each reduced level. Slice plans have been generated to be used during pit designing where the slice plan of the bottom of the ore body or block ore body will be the ultimate pit limit. According to it the location of the box cut should be decided.
Slices can be given different colors depending on the grades. Figures 15 and 16 shows the slices generated for an iron percentage. As the ore body is of limestone ore, the major mineral that has been needed to determine and extent is iron. Similarly, the block model can also be distinguished by inputting numeric color codes for different grades.
Figure 15: Image showing slice plans generated for the reduced level 1120
Figure 16: Image showing slice plans generated for the whole ore body
Pit Design
The attributes to be inputted after proper calculation for pit designing includes:-
• Bench height:- 10 m,
• Bench slope angle- 65ο,
• Overall slope angle- 46.58ο,
• Berm width- 5 m.
Pit designing has started from the lower slice and
continuing upwards. Digitizing has been done along the
slices for each slice, and then another slice imported. The
digitizing has produced a string file which has to be saved in
a single file. From this string file, a Digital Triangulated
model of the pit has formed. After the pit formation, the
volume of the ore inside the ore body has been calculated,
and the model has been saved, and a report of it has been
generated.
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Figure 17: Image showing angular section of the string file generated for pit design
Figure 18: Image showing angular section of the open pit generated
Table 4: Ore reserve estimated for the ore body inside pit boundary
Mining blocks graphically:
This is a separate feature which has been used to develop a work order for the blocks required to be mined to meet a target tonnage. The ore body is simulated to mine blocks graphically, after the completion of the grade estimation by the three methods. The target volume and the target tonnage are pre-set by the user for mining blocks graphically, and the graphics then asks the users to choose the blocks graphically for mining. The blocks are then chosen based on the requisite grade, and once the tonnage or target volume is met, the wizard in Figure 20 shows the result of how much tonnage or volume of ore was mined. Further, it asks the user if he/she is satisfied with the production report or wish to start a new phase of mining blocks graphically.
Figure 19: Image showing inputted attributes for mining blocks graphically
Figure 20: Image showing output results for desired tonnage input
CONCLUSIONS
The efficiency of reserve estimation using Nearest Neighbor and Inverse Square Distance method was compared with Ordinary Kriging method assuming it to be the best linear unbiased method. From the obtained estimation results it was concluded that both Nearest Neighbor method and Inverse Distance method overestimates the iron percentage.
Pit designing has been done after perfectly considering all the parameters such as the overall slope angle, bench angle, berm width and bench height to get the ultimate pit limit. However designing should be done keeping in mind that the boundary of the pit does not crosses the lease boundary of the mine throughout the process. After the completion of pit design, the amount of ore lost due to part of ore falling outside the pit and its effect on the grade of ore body has also been calculated.
REFERENCES
1. H. Agarwal, “Modeling of Opencast Mines using Surpac and its Optimization” E-Thesis, National Institute of Technology, Rourkela, 2012.
2. S.K. Haldar, “Mineral Exploration- Principles and Practices” Elsevier Publications. Pages: 157-182, 2013.
3. H. Sevim, and D.D. Lei, “Problem of production planning in open pit mines” INFOR J. vol. 36, 1–12, 1998.
4. H. L. Hartman, “Introductory mining engineering” John Wiley & Sons, Inc. , Pages: 149-150, 1987.
5. M.C. Moharaj, and Y. Wangmo, “Ore Body Modeling and Comparison of Different Reserve Estimation Techniques. E-Thesis, National Institute of Technology, Rourkela, 2014.