Exercise 1 - Optimisation Overview To generate an optimal pit for a ore deposit where the net value of each block in the model must be calculated automatically by the Pit Optimiser from given sale prices and costs. As an additional requirement, the resultant optimal pit must have wall slope angles of no greater than 45 degrees around the entire wall of the pit. Requirements The data files required for this exercise are: gold.mdl, topo1.dtm, topo1.str These files are located in the dem/training/pitopt directory where Surpac Vision has been installed. Getting started Set your current working directory to be the directory containing the files to be used for this exercise. To do this, left click with the mouse on the directory in the navigator and then right click to pop up a menu. Select Set As Work Directory from this menu. Display the block model menu by right clicking with the mouse at the end of the main menu bar (to the right of the Help menu). When discussing any block model functions in this tutorial, they will be referred to from this menu. Open the block model file gold.mdl by selecting this file from the navigator with the left mouse button and while holding down this button, dragging the mouse pointer into the graphics viewport. The block model status item should appear at the bottom of the Surpac window as shown below:
Surpac Minex Group Pit Optimiser in Surpac Vision June 2006 Copyright © 2006 Surpac Minex Group Pty Ltd All rights reserved This software and documentation is proprietary to Surpac Minex Group Pty Ltd Surpac Minex Group Pty Ltd publishes this documentation for the sole use of Surpac licenses Without written permission you may not sell, reproduce, store in a retrieval system, or transmit any part of the documentation For such permission, or to obtain extra copies please contact your local Surpac Minex Group Office Surpac Minex Group Pty Ltd Level 190 St Georges Terrace Perth, Western Australia 6000 Telephone: (08) 94201383 Fax: (08) 94201350 While every precaution has been taken in the preparation of this manual, we assume no responsibility for errors or omissions Neither is any liability assumed for damage resulting from the use of the information contained herein All brand and product names are trademarks or registered trademarks of there respective companies About This Manual This manual has been designed to provide a practical guide to the many uses of the software The applications contained within this manual are by no means exhaustive as the possible uses of the software are only limited by the user’s imagination However, it will give new users a starting point and existing users a good overview by demonstrating how to use may of the functions in Surpac Vision If you have any difficulties or questions while working through this manual feel free to contact your local Surpac Minex Group Office Author Rowdy Bristol Surpac Minex Group Perth, Western Australia Product Surpac Vision v5.1 Table of Contents Introduction Requirements Objectives Workflow Optimisation Theory Data Requirements and Block Model Preparation Exercise - Optimisation Exercise - Ore Discounting Factor 74 Exercise - Assigning Net Values to block model 82 Introduction Pit optimisation allows us to produce a model for pit design based on a block model with real world constraints This document introduces the theory behind the pit optimisation process and provides detailed examples using the pit optimisation functions in Surpac Vision Requirements Prior to proceeding with this tutorial, you will need: • • • • • To have Surpac Vision v5.1 installed The data set accompanying this tutorial Basic knowledge of Surpac string files and editing tools To have completed the Introduction manual To have completed the Block modelling manual Objectives The objective of this tutorial is to allow you to create an optimised pit model by applying real world conditions to an existing block model Workflow The process described in this tutorial is outlined below: • • • • Understand the theory basis of pit optimisation models Perform pit optimisation on an existing block model Apply optimisation using an Ore Discounting factor Apply optimisation by assigning Net Values to the block model Optimisation Theory Overview An optimal pit for a deposit is one that maximises profit and satisfies both cost and slope constraints Designing an optimal pit is a challenging and complex problem that is difficult to solve As a result, several mathematical algorithms have been developed to solve this problem in a reasonable time frame The Pit Optimiser developed by the Surpac Minex Group is based on a variation of the Lerchs Grossman algorithm that was first proposed by Koenigsberg in 1985 The Pit Optimiser works on a block model of the deposit where each block must have a net value that represents the economic value that will be returned if that block is extracted in isolation The Pit Optimiser then considers each of these blocks in turn to work out which combinations of blocks should be mined in order to return the highest possible total value given mining constraints for a particular sale price The result is a 3D surface that represents the base / limit of the pit that maximises the total value of the mine and any further extension of the pit will not increase the total return Requirements Prior to performing the exercises in this chapter, you should: • Be familiar with the basic principles of Surpac Vision • Be familiar with the Block model module and the Geological database module Pit optimisation works on a block model of the deposit to be mined and the surrounding material With any block model, only a subset of blocks will actually contain material of sufficient grade to make them worthwhile to mine once they are exposed at the surface In order to reflect this information, each block must be assigned a value that essentially shows the net cash flow that would result from mining that block in isolation This value must be positive for an ore block and can be calculated as the sale price minus the costs of mining and milling For waste and air blocks, this value will be zero or a negative value representing the cost of mining that block To illustrate this, the diagram below shows a cross section of a deposit For simplicity, all air blocks in the block model for this ore body will be given a value of $0, the mining cost associated with extracting an ore or waste block will be set at $3, while the sale price for each ore block will be $20 The diagram below shows a cross section of the block model for this deposit Each block has been assigned a net value indicating the cost of extracting the block if it were already exposed Once all the blocks have been assigned a net value showing the cost of extracting just that block as if it were already exposed, each block is then considered in turn and all the blocks that are needed to be mined in order to uncover it are identified From these blocks, it is then possible to calculate the total net value of a block in relation to its position in the model This will be the net value of the block in question minus the cost of mining all the blocks that need to be mined before it can be extracted In the above example, we have assumed that in order to mine a block, the block directly above it must be extracted first Therefore, to calculate the total net value of a block, you would take the net value of the block and subtract the net value for all the blocks above it After the total net value for each block is calculated, it is then a matter of finding the combination of blocks to extract that will result in the maximum return for that deposit As shown below, the maximum value for a vertical pit (90 degree slope angle) for this deposit is $40 This is computed by adding up the total net values of the blocks along the base of the pit outline If more blocks were extracted, the total return of the pit would actually decrease as shown below When an extra column of blocks is extracted, the value of the pit is $39 Likewise with a smaller pit, the total return is only $38 This is illustrated below An optimal pit is one which returns maximum revenue A slightly smaller pit will leave revenue on the pit walls, while a slightly bigger pit is unprofitable at its limit In pit optimisation, wall slope angles are an important consideration when calculating the optimum pit because these angles determine which blocks need to be mined before a certain block can be extracted This in turn affects the total net value for each block and will result in different blocks forming the optimal pit The above simplified case assumed a slope angle of 90 degrees which is unrealistic If on the other hand, a slope angle of 45 degrees is assumed, the following results would be achieved The maximum value for a 45 degree slope pit would give a value of $13 and is once again calculated by adding up all the total net values of the blocks along the base of the optimum pit Regardless of the slope angle used, a slightly smaller or larger pit would result in less return as shown in the two diagrams below As can be seen from the above, finding the optimal pit for a deposit is not a simple process There are many different combinations and sizes of pit outlines that need to be assessed before it is possible to determine which pit will return the most profit for a given sale price This process can be repeated by increasing the sale price to calculate more profitable pits closer to the surface that are shorter term (2 to years) In effect, a series of nested pit shells can be produced and used as a rough guide for determining the schedule of the mine or estimating the maximum net present value of the mine The two algorithms that the Surpac Minex Group pit optimiser uses are the Floating Cone and Lerchs Grossman techniques to determine an optimal pit for a deposit These two algorithms are discussed later Data Requirements and Block Model Preparation The minimum data requirements for the Pit Optimiser are: The block model containing quality data and an attribute indicating which blocks are ore and which are waste blocks in the model or alternatively, an attribute representing the net value for a block The net value for a block is the net cash flow generated after the block has been extracted and processed, and can be calculated as follows: Block Net Value = Sale Price – (Mining Costs + Milling Costs) Sale Price is the price of the material that it can be sold at For ore material, this will be a positive value as it can be sold and for waste and air material, this will be zero because they cannot be sold Mining Costs refer to the cost of extracting the block as if it were the only block in the model It does not include the cost of extracting the immediate blocks above it Both ore and waste blocks will have an associated mining cost Air blocks cost nothing to extract and therefore have no mining costs Milling Costs represent the cost of processing ore material through the mill Only ore blocks will have a milling cost component and hence, waste and air blocks have no milling costs From the above calculation, ore blocks will always have a positive net value while waste blocks will have a negative net value and air blocks have a zero net value The net value must be expressed in either dollars per mass unit (eg $/tonne) or dollars per volume unit (eg $/m3) of ore This will be discussed in more detail later Topography DTM surface Once all the necessary attributes have been added to the model and the topography surface has been prepared, the pit optimisation parameters can be entered and the pit optimiser will produce a pit shell or series of nested pit shells representing the base of the optimal pit at given sale price Now that we have a net value attribute stored in the model that takes into account mining costs and sale prices of the blocks in the model, we can start entering the parameters for the optimisation From the Block model menu, select Pit Optimisation, to display the Pit Optimisation form We will create a new parameter file for this exercise Press Apply to display the Pit Optimisation Parameters form We must now fill out the Ore Type tab pane Select $/mass from the Method combo box We are selecting this method because the net_value attribute that we just set up is expressed in $/t ($/mass unit) 90 As with the previous two exercises, we will select the ore_type attribute for the Ore Type field to describe which areas of the model are to be considered as the same material Note that the ore_type attribute has assigned all the blocks in the model to be of the same material For the SG (Optional) field, select the sg attribute in the model 91 Select the net_value attribute that we created during the first exercise for the Net Value Attribute field This attribute tells the Pit Optimiser which blocks are ore blocks (positive net values) and which blocks are waste blocks (negative net values) These are the only fields that need to be filled in this tab because the table on the Ore Type tab pane only needs to be filled in if an attribute for the SG (Optional) field is not chosen Click on the Mining Costs tab pane to display the form below: 92 There is no need to enter any information in the Mining Costs tab pane because the mining costs must already be taken into account in the net value attribute that was chosen on the Ore Type tab pane Now click on the Slopes tab pane so we can define the maximum slope constraints for the resultant optimal pits For this exercise we will select a maximum default slope angle of 30 degrees Enter in a value of 30 in the default row of the Default column in the table 93 This time we will add in an extra criterion that a maximum slope angle of 40 degrees is to be used in the southern region of the pit To enter this information, left click the mouse into the field called South East and change the current value of 30 to 40 Do the same for the field labelled South and South West Once the maximum slope angles of the resultant pit have been established, click on the Vertical Limits tab pane As we are working with the same data set as the previous exercises, the vertical limits will be the same Select topo1.str for the topography location and limit the base by an elevation of 0.0 Click on the Optimisation tab pane to determine how the optimisation will find a solution 94 Once again, select the Lerchs Grossman algorithm to perform the optimisation Check the Lerchs Grossman checkbox and leave the Major Cycles field at so the optimisation runs to completion We will write the results back to the block model and will store the value in a new attribute called pit_number To this, type the new attribute name pit_number into the Pit Attribute field 95 A report name must be entered to save a summary of the resultant optimum pit volume and net value For this exercise, we will save the report to a Surpac note file called pit_$mass_report.not To this, enter the file name pit_$mass_report into the Output Report File Name field and select not from the Output Report File Format combo box Finally, we will save the resultant DTM pit shell that will be created to a file called pit_$mass0.dtm Remember that the Discount % is automatically appended to the Output Pit Location name We also graphically display the result in a layer called pit_$mass and the pit shell will be coloured in cyan 96 There is no need to enter in an attribute name for the Value Attribute field above because we manually calculated the net value for each block at the start of the exercise and so, we already have the net value stored in the model Note: With the $/mass and $/volume methods, you cannot enter in discount percentages to affect the sale price of the ore The reason for this is that the sale price has been incorporated into the net value that we assigned at the beginning of the exercise Therefore the Pit Optimiser does not know the sale price of the ore to be able to apply discount factors Press Apply on the Pit Optimisation Parameters form to run the optimisation The resultant optimal pit shell should appear in graphics as shown below: By displaying the block model and constraining the pit to show only the blocks with a gold grade value of greater than one (only blocks with a grade value of greater than one were given a sale price), we will be able to see which ore blocks should be mined to maximise profit 97 From the Block Model menu, select Display, then Display block model, to display the entire model Apply the drawing defaults shown below: From the Block model menu, select Constraints, then New Graphical Constraints and enter the following to add new constraints 98 The graphical constraint should appear as follows: From the Block model menu, select Block model then Report, and fill in the form to find out the tonnage and average grade for gold in the optimal pit Press Apply on this form to display the Block Model Report form 99 Fill in the form as shown below: Press Apply on this form and constrain the report firstly by only considering all the blocks above the optimum pit shell: 100 Secondly, only report on the ore blocks in the model: After applying the above constraints, the following report should be generated The volume and tonnage is reported by 20 m benches: Z 230.0 -> 250.0 210.0 -> 230.0 190.0 -> 210.0 170.0 -> 190.0 150.0 -> 170.0 130.0 -> 150.0 Grand Total Volume 39500 107375 12000 38750 47500 4000 249125 Tonnes 94800 257700 28800 93000 114000 9600 597900 Gold 2.13 2.72 1.80 1.96 1.86 1.00 2.27 Report The following report will be generated in the window that pops up: Results: Discount 0.00 Volume 552,000.00 Value 6,463,950.00 Output pit_$mass0.dtm This shows the volume of the optimal pit is 552,000 m3 and the net value of the pit is $6,463,950.00 This report is saved to a file called pit_$mass_report.not 101 Alternative way of getting bench reports – available from Surpac version 5.2 onwards Reset Graphics to clear the graphics view port Use the same block model that you have saved the net value attribute that takes into account mining costs and sale prices From the Block model menu, select Pit Optimisation, to display the Pit Optimisation form and use the parameter file gold_$mass.pop that was created for the above exercise Click on the Report tab and fill it in as shown below: 102 Results: Discount 0.00 Bench Elevation 130.00 150.00 150.00 170.00 170.00 190.00 190.00 210.00 210.00 230.00 230.00 250.00 Total pit Volume 552,000.00 Value 6,463,950.00 Waste Mass 0.00 Waste Volume 0.00 Waste Value 0.00 Ore Mass 11,840.00 Ore Volume 4,000.00 104,591.25 44,000.00 162,843.75 58,000.00 135,670.00 56,000.00 135,005.00 48,000.00 36,622.50 16,000.00 34,418.75 12,000.00 111,643.75 46,000.00 367,645.00 130,000.00 200,723.75 88,000.00 138,418.75 50,000.00 589,251.25 250,000.00 451,552.00 637,744.00 143,609.00 503,914.00 875,621.00 2,612,440 00 850,171.25 302,000.00 Output pit_$mass0.dtm Ore Value Gold (1) 130,240.00 1.00 Stripping Ratio 0.00 1,679,368 00 1,457,411 00 405,425.00 1.56 0.76 1.64 1.17 1.61 1.33 2.33 0.35 1.68 1.76 1.92 0.83 4,281,564 00 1,122,382 00 9,076,390 00 Note: Even though you can get a quick bench report, by the optimiser Reports tab, it is not as versatile as the Block Model Reporting For example you can not specify constraints,/or the number of decimal places to use when reporting Pit Attribute From the Block model menu, select Constraints, then Remove all graphical constraints, to view all the blocks in the model that are in the optimal pit The entire model will be redisplayed From the Block model menu, select Constraints, then New Graphical Constraints and enter the following to add new constraints 103 This will show all the blocks within the optimal pit as shown below: Rotated Block Models The pit optimiser is only able to handle rotated models around the Z axis only That is, a model where the bearing has been set to something other than It will not deal with a plunged or dipped model 104 [...]...Exercise 1 - Optimisation Overview To generate an optimal pit for a ore deposit where the net value of each block in the model must be calculated automatically by the Pit Optimiser from given sale prices and costs As an additional requirement, the resultant optimal pit must have wall slope angles of no greater than 45 degrees around the entire wall of the pit Requirements The data files required for this exercise... that were previously entered Modifications can then be made to these parameters and the pit optimiser can be run again All modifications will be saved back to the parameter file The parameter file has a pop extension Enter in gold_$unit for the parameter file name for this example Press Apply to display the Pit Optimiser parameters form As can be seen above, the form is made up of five different tab... given an ore_type value of one This means that all the blocks in the model are ore blocks (not waste) and therefore will be processed by the Pit Optimiser In reality, only a portion of blocks in the model are actually part of the ore deposit and hence the Pit Optimiser will use the Sale Price Curves (discussed later) to determine if a block is really an ore block or is actually waste Select the ore_type... familiarity with the deposit The object of this exercise is to generate the base of the pit for this deposit that will return the most profit at a given sale price Before entering the pit optimisation parameters, we must set the units that will be used when specifying the maximum allowable slope angles for the optimal pit The two options available are decimal degrees or gradients For this exercise, we... ($/percent) It is important to note that using this method to define the sale price, the net value for each block does not have to be calculated and stored in the model before running the pit optimisation The Pit Optimiser will automatically calculate the net value for each block from the sale prices, mining costs and milling costs that have been assigned for each different ore type $/mass To use this... known in order for the Pit Optimiser to work with mass units This method assumes the net value assigned to each block is correct and any blocks with a negative or zero value are waste and air blocks respectively, and any blocks with a positive value are ore blocks Special care must be taken when calculating the net value for each block as any errors will result in an incorrect optimal pit being generated... then press Apply to set these units 13 From the Block model menu, select Pit optimisation The following form will appear prompting you to enter the name of the parameters file The parameters file is a file created to store all the pit optimisation parameters that are entered on the next form so that on subsequent runs of the pit optimisation it is possible to redisplay all the parameter values that... should be entered in the order they appear and are discussed in the following pages: 15 Ore Type This tab pane is used to identify whether a block is an ore block or a waste block It also tells the Pit Optimiser whether it has to calculate the net value for each block or whether the value is already stored in the model If you click on the down arrow button on the Method combo box, you will see there... classifies the different ore materials in the model by an integer value From the information in the block model, it can be seen that there is no attribute containing the net value for each block and so the Pit Optimiser will have to automatically calculate it Press Apply on the form to close it From the Block model menu, select Display, to display the entire block model The following form should appear: 9... Yield combo box on the Ore Type tab pane to indicate the gold grade will be used to model our milling recovery 21 Sale Price Curves To work out the sale price for each ore block in the model so the Pit Optimiser can calculate its net value, mathematical curves can be set up for each ore type For complex pricing structures, several grade cutoffs can be used to define different sale prices for different