pit optimisation

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Product

GEOVIA Minex 6.3

Last modified: Wednesday, 4 September 2013

Pit Optimisation tutorial

Table of Contents

About this document ......................................................................................................................... 4

Document conventions ...................................................................................................................... 5

Typographical conventions .................................................................................................................... 5

Keyboard conventions ........................................................................................................................... 5

Menu conventions ................................................................................................................................. 5

Mouse conventions ............................................................................................................................... 5

Form elements ....................................................................................................................................... 6

Concepts ........................................................................................................................................... 8

Setup for this tutorial ...................................................................................................................... 15

Activity: Install the data set ................................................................................................................. 15

Activity: Back up the data set .............................................................................................................. 15

Activity: Create a Minex project .......................................................................................................... 16

Start the Pit Optimiser ..................................................................................................................... 18

Activity: Start the Pit Optimiser ........................................................................................................... 18

Activity: Save and view the input parameters ..................................................................................... 21

Activity: Run the Pit Optimiser ............................................................................................................ 23

Fault Block Geological Models .......................................................................................................... 25

Coal or Ore Value ............................................................................................................................ 26

Washing Costs and Yield .................................................................................................................. 28

Output Grids ................................................................................................................................... 31

Reporting Points .............................................................................................................................. 32

Activity: Report on grids and costs ...................................................................................................... 32

Advanced costs using SQLs ............................................................................................................... 34

Steep Dip Deposits .......................................................................................................................... 36

Advanced Wall Slope Control ........................................................................................................... 37

System information ......................................................................................................................... 39

Summary ......................................................................................................................................... 40

Appendix A ...................................................................................................................................... 41

Activity: Edit MNX files ........................................................................................................................ 42

About this document

GEOVIA Minex 6.3 Page 4 of 60 Pit Optimisation tutorial

About this document

Overview

This document describes the operation of the Minex Pit Optimiser. This Optimiser uses a Minex gridded seam model as its input and creates a gridded surface representing the optimum pit. Both the Minex and Whittle Optimisers are based on the Lerchs Grossmann algorithms.

This tutorial uses a data set that is copied to your computer when Minex is installed.

When the software has been installed, more detailed information is available in the Minex Help, which you can open from the Help menu. You can also contact your local GEOVIA support office for training.

Requirements

Before proceeding with the tutorial, you will need:

a good understanding of basic Minex concepts

Minex 6.3 or later installed

the Ashes data set

a licence for the Open Pit module

Objectives After working through this tutorial, you will be able to:

determine how coal is valued

determine washing costs and yields

create a set of nested pits

create output reports

determine advanced mining costs using SQL commands

use the Optimiser in steep dip deposits

Document conventions Typographical conventions


Document conventions

Typographical conventions

Some text in this guide has special formatting to help you identify it as part of a particular element of information. The following table describes the different text formats and their meanings.

Text format Meaning

Text or data that varies with each input is shown in bold italic font and enclosed in angle brackets. Some examples are installation directories, dates, names, and passwords. When you substitute the text for the variable, do not include the brackets. For example: requires you to substitute a password in place of .

Italics A word or phrase to which the author wants to give emphasis. For example: you must

select an item from the list to continue.

Bold This typeface indicates one of the following:

A file name, path, or URL.

Strongly emphasized text. For example, It is very important to save the data [].

Text that a procedure has instructed you to type.

A menu option, tab, button, check box, list, option button, text box, or icon.

For example: Save the file as pit1.str.

Keyboard conventions

Key combination Meaning

+ Press and hold the first key, then press the second key. For example: CTRL+Z means press and hold the CTRL key, then press Z.

Menu conventions

When you click, or move the pointer over, some menu commands, a subordinate menu appears. To indicate that you should select a command on a subordinate menu, this documentation uses a greater than (>) sign to separate the main menu command from the subordinate menu command. For example, File > Project > Project Manager means choose the File menu, move the mouse pointer over the Project command, and then select Project Manager on the secondary menu.

Mouse conventions

Action Description

Click Press and release the left mouse button without moving the mouse.

Right-click Press and release the right mouse button without moving the mouse.

Double-click Rapidly click the left mouse button twice without moving the mouse.

Drag With the mouse pointer over the object, press and hold the left mouse button to select the object. Move the pointer until the object is in the position you want, and then release the mouse button.

Rotate Use your finger to make the wheel button roll. Move it forward, that is in a clockwise direction, or backward, that is in an anticlockwise direction.

Document conventions Form elements


Form elements

Forms, or dialog boxes, can contain a variety of elements that enable users to carry out operations. Here is an example form.

Forms can contain the following elements

Element Description Example

Title Title of the form.

Tab Labelled group of options used for many similar kinds of settings.

Text box or field

Rectangular box in which you can type text. If the box already contains text, you can select that text and edit it.

Drop-down combo box

Closed version of a list box with an arrow next to it. Clicking the arrow opens the list.

Option button

Round button you can use to select one of a group of mutually exclusive options.

Label Text attached to any option, box, button, or to any other element of a window or dialog box.

Check box

Square box that you select or clear to turn an option on or off.

Button Rectangular or square button that runs a command. Buttons have text labels to indicate their purpose.

Icon A graphical button that you can click to run a command.

List box Any type of box containing a selectable list of items in table format.

Document conventions Form elements


Element Description Example

Menu A set of options or commands that you can run.

Spin box A text box with up and down arrows that you can click to move through a set of fixed values. You can also type a valid value in the box.

Tree A graphical representation of a hierarchical structure. A plus sign next to an item on the tree indicates that you can expand the item to show subordinate items; a minus sign indicates that you can collapse the item.

Concepts Form elements


Concepts

Overview

The concepts presented in this tutorial are concepts from the mining domain or concepts specific to Minex.

Pit Optimisation

Optimisation is a process in which something is made as effective, perfect or useful as possible. The term can be used in a general sense to mean a process where an outcome is optimised by the adjustment of inputs or methods.

Optimisation also has a mathematical definition: which means to find the optimal value of a function, often subject to constraints. Optimal in mathematical terms means one of the following:

Minimal: The lowest possible value. If you were to optimise total cost, you would be seeking to minimize it.

Maximal: The highest possible value. If you were to optimise total profit, you would be seeking to maximize it.

Example ore body

ore

waste

air

ore

waste

air

For any ore body model there are many feasible pit outlines. The number of technically feasible outlines is usually very large. In this context feasible means that it obeys safe slope requirements.

In the current context, an optimum pit is the pit with the maximum dollar value where Dollar Value is defined as:

Dollar Value = Revenues - Costs

You can calculate revenues from coal tonnages, energy, pit and wash plant recoveries or yields and product price. Price is often the main unknown factor however, in order to calculate revenue at all, a price must be assumed.

For simplicity we will assume that the costs of mining and processing are known.

You can calculate the dollar value of any feasible outline by totalling revenues and deducting costs for every cubic metre, or every block, within the outline. The optimal outline is the one with the highest dollar value.



Nothing can be added to an optimal outline which will increase the value without breaking the slope constraints. Nothing can be removed from an optimal outline which will increase the value without breaking the slope constraints. In other words, we mine everything which is worth mining.

The optimal value for a given ore body can be affected by:

Prices and costs: In general if the product price goes up, the optimal pit gets bigger and conversely if costs go up, the optimal pit gets smaller.

Slopes: In general if we use steeper slopes, the optimal pit gets deeper.

In summary the Minex Optimiser, like any Optimiser, generates a pit shape (a Minex grid) that is of maximum value.

A typical analysis methodology in Pit Optimisation is to vary sale price and study the effect on the pit. As sale price is increased, the pit will grow because more material becomes economic. This growth of pits, often termed nested pits, helps us understand the pit limits and the best path or schedule to that limit.

How Pit Optimiser works

The example given here is simplistic but illustrates the main calculations involved in setting up the costs. The following premises or assumptions apply:

A set of 3D blocks can be superimposed on the geology.

The blocks can be filled with dollar value = (revenue costs).

A mining cost of $3/block is used for coal and waste.

Revenue of $20/block is used.

Blocks are for simplicity assumed to be coal or waste. This assumption is not correct but serves the purpose at this stage. A more detailed discussion on this point is given later in this document.

Coal blocks will have a value of $20 - $3 or $17/block.

For simplicity waste mining and coal mining costs are the same.

The following image shows a simple cross section and discusses optimisation as a 2D section. This is simplistic as optimisation works in 3D, however 2D is adequate for this discussion.

The first stage of optimisation is to determine the individual block values. In the following example we assume blocks are 100% coal or 100% waste. The dollar values are thus $17 and -$3 for coal and waste respectively.

$0 $0 $0 $0 $0 $0 $0 $0 $0

-$3 -$3 -$3 -$3 -$3 -$3 -$3 -$3 -$3

-$3 -$3 $17 -$3 -$3 -$3 -$3 -$3 -$3

-$3 -$3 -$3 $17 -$3 -$3 -$3 -$3 -$3

-$3 -$3 -$3 -$3 $17 -$3 -$3 -$3 -$3

-$3 -$3 -$3 -$3 -$3 $17 -$3 -$3 -$3

-$3 -$3 -$3 -$3 -$3 -$3 $17 -$3 -$3

-$3 -$3 -$3 -$3 -$3 -$3 -$3 $17 -$3

-$3 -$3 -$3 -$3 -$3 -$3 -$3 -$3 $17

Cost $3/block

Revenue $20/block

GeologyBlock costs

$0 $0 $0 $0 $0 $0 $0 $0 $0

-$3 -$3 -$3 -$3 -$3 -$3 -$3 -$3 -$3

-$3 -$3 $17 -$3 -$3 -$3 -$3 -$3 -$3

-$3 -$3 -$3 $17 -$3 -$3 -$3 -$3 -$3

-$3 -$3 -$3 -$3 $17 -$3 -$3 -$3 -$3

-$3 -$3 -$3 -$3 -$3 $17 -$3 -$3 -$3

-$3 -$3 -$3 -$3 -$3 -$3 $17 -$3 -$3

-$3 -$3 -$3 -$3 -$3 -$3 -$3 $17 -$3

-$3 -$3 -$3 -$3 -$3 -$3 -$3 -$3 $17

Cost $3/block

Revenue $20/block

Cost $3/block

Revenue $20/block

GeologyBlock costs

The Optimiser algorithm sums the block values vertically downwards. Mining a lower block implies the bocks above are removed. Thus to mine a coal block, all the blocks above must be mined as shown in the following table.



An optimum pit:

Has the maximum value

Is break even at its limits

A larger or a smaller pit will have a smaller value compared to the optimum.

Lerches and Grossman (CIM 1966) developed the optimum pit algorithm to determine the pit of maximum value. The detail of their approach is not discussed here. The final result is a pit outline with maximum value for that set of costs and revenue. The following image shows a table for each pit where we assume the slopes are at 45

o.

The LHS pit table has a cumulative value of $13. This is the sum of the seven columns. From left to right the columns are 0, -3, 14, 11, -6, -3, 0 = $13.

The RHS pit table has a cumulative value of $12. This is the sum of its columns. From left to right the columns are 0, -3, 14, 11, 8, -9,-6,-3= $12.

The $13 dollar pit is optimum as it has the maximum value for the cost and revenue assumptions. A smaller pit is sub optimum and a larger pit is sub optimum.

The following image shows a table for a smaller pit which would have a value of $8 (-3,14,-3)..



The term nested pits is used frequently in optimisation. If the coal sale price increases, the optimum pit will be larger. The extra revenue makes a deeper pit economic. Using different sales prices will generate a set of optimum pits, one pit for each sale price. The following image shows nested pits 1, 2, 3 and 4.

1 2 3 41 2 3 4

This sequence of pits or outlines forms a set of nested pits. Nested pits are important in strategic mine planning. Assume that the actual sale price equates to pit 4. Then mining in the sequence 1, 2, 3, 4 maximizes cash flow and maximizes NPV. This occurs because the smallest pit (pit 1) is optimum at the smallest sale price. If the market price of $100/tonne equates to pit 4 and pit 1 is profitable at say $40, then this pit makes $60 profit per tonne. Mining pit 1 first maximizes early cash flow and maximizes NPV.

In conclusion the optimum pit gives planners:

The final economic pit for a set of costs and revenues.

A sequence of nested pits, which show the best mining sequence.

Minex is a seam or layered modelling system. The basis of the Minex system is a 2D grid or surface model. The following image shows the 2D grids for topography and for one coal seam floor. Typically in Minex a set of floor, roof, thickness, density, energy and ash grids etc exist for each seam. These grids in combination make up a 3D geological model.

The optimisation process uses a 3D block model. The Minex Optimiser firstly converts the 2D gridded seam model into a block model. This block model is not a resource model with waste volume, coal tonnes and grade. It is a block model of block value, where value = (revenue cost).

To build this block model, the Minex Optimiser defines the extent of the block model in X Y and Z. The X, Y extents are based on the input topography surface. The vertical or Z extent is based on the maximum Z of topography and the minimum Z of the deposit or a base grid. The block size of the 3D block model is based on the grid cell size of the topography grid. Thus if the topography grid used is 100 x 100 metres in size then the optimiser blocks will be 100m x 100m x 100m in XYZ. Sub blocking in the vertical or Z dimension provides better Z accuracy and thus allows better resolution of coal seams.

The Z extent of the Optimiser model is taken from the topography and base grid. It can for speed reasons be useful to reduce the model size by limiting the base grid. Similarly if the economic area (in XY) is limited, then reducing the input topography will reduce the block model size and may reduce compute times. The following image shows these concepts.

The topography defines the block model X, Y dimension. The Z dimension comes from the topography and base seam.



Z extent

X extent

Y e

xtent

Z extentZ extent

X extent

Y e

xtent

The block model stores dollar values as an integer which is equal to:

Value = (Volume x revenue) (Volume x costs)

The example used below assumes the following:

Waste mining costs is a constant of $2.6/bcm

Coal mining costs are $5/bcm

The coal sale price is $45/tonne

Therefore a 100% waste block with dimensions of 100 x 100 x 100 metres would be valued at negative $2,600,000. The value for a block is based on a scan through the centroid of each block. In section the block value calculation is defined as shown in the following image.

W1 =60m

W2= 35m

A B

C1=5W4=60

W5=25

W3=5

C2=5

C

C3=10

W6=10

W7=80

W1 =60m

W2= 35m

A B

C1=5W4=60

W5=25

W3=5

C2=5

C

C3=10

W6=10

W7=80

Here block A is assigned a value based on:

The cost of the waste between the topography and the seam (W1)

= volume x waste mining cost

= (60 x 100 x 100) x $2.6

= $1,560,000

The value of the coal seam (C2)

= (volume x density x sale price) (volume x coal mining cost)

= (5 x 100 x 100 x 1.4 x $45) (5 x 100 x 100 x $5)

= $2,900,000

The cost of the waste below the seam (W2)




= (35 x 100 x 100) x $2.6

= $910,000

The value of the block

= - W1 cost + C2 value W2 cost

= - $1,560,000 + $2,900,000 - $910,000

= $430,000

Block B can be calculated as:

The cost of the waste above the upper coal seam (W3)


= (5 x 100 x 100) x $2.6

= $130,000

The value of the upper coal seam (C1)


= (5 x 100 x 100 x 1.4 x $45) (5 x 100 x 100 x $5)

= $2,900,000

The cost of the waste between the two coal seams (W4)


= (60 x 100 x 100) x $2.6

= $1,560,000

The value of the lower coal seam (C2)


= (5 x 100 x 100 x 1.4 x $45) (5 x 100 x 100 x $5)

= $2,900,000

The cost of the waste below the lower coal seam (W5)


= (25 x 100 x 100) x $2.6

= $650,000


= - W3 cost + C1 value W4 cost + C2 value W5 cost

= - $130,000 + $2,900,000 - $1,560,000 + $2,900,000 - $650,000

= $3,460,000

Now consider the base block, block C. Assuming the stratigraphy stops at the lowest seam then this block is assigned a value of:

The cost of the waste above the coal seam (W6)


= (10 x 100 x 100) x $2.6

= $260,000

The value of the coal seam (C3)


= (10 x 100 x 100 x 1.4 x $45) (10 x 100 x 100 x $5)

= $5,800,000


= - W6 cost + C3 value

= - $260,000 + $5,800,000

= $5,540,000



The underburden of 80 metres (W7) below the basal seam is not included in the block value as it will not be mined. In Minex, this cost is excluded as it is below the stratigraphy.

Underburden W2 and W5 is however used to determine the value of blocks A and B respectively as these blocks are above the basal seam. In some cases this extra underburden cost can be misleading. To minimize this error the Minex Optimiser uses Z sub blocking. Basically the Z block is subdivided by an integer value between 1 and 8. So if the primary block size is 100x100x100 and the Z blocking is 4 then the Optimiser runs at 100x100x25.

Sub-blocking gives advantages in:

accuracy

slope definition

Dividing blocks A, B or C into four 25m high blocks increases the resolution. These thinner blocks are more clearly either waste or coal, or more correctly are either economic or uneconomic.

Sub-blocking is not always an exact division of the primary block size. For the Optimiser to achieve the required side slope sufficient block detail must exist.

In the following example a 45o slope can be achieved with 40 x 40 x 10 metres blocks. However a side

slope of 30o can only be achieved with 23.09 metres of vertical rise. As the Optimiser side slope falls the

Z sub block size falls to accommodate the flatter slope angle. The following example shows 4 x 5.77 metre blocks (shown bottom left) up and one 40m block across equates to a 30

o slope (RHS).

45o 30o45o 30o

In the following table the Z-sub block size is a function of the wall slope and the Z-sub blocking. The Minex Optimiser will automatically calculate the appropriate Z block size based on the user input Z blocking and the user input slopes.

Relationship between block size in Z and slope angle

WALL BLOCK OPT Z TAN SIZE Z Z BLKS

SLOPE X SIZE BLOCK WALL REQD REQD

DEGREES MET MET MET

45 40 10 1.00 40.00 4.00

40 40 8.39 0.84 33.56 4.00

35 40 7 0.70 28.01 4.00

30 40 5.77 0.58 23.09 4.00

Setup for this tutorial Activity: Install the data set


Setup for this tutorial

Tutorial data

When you install Minex and accept the default installation settings, the tutorial data is installed on your machine. If you choose not to install the tutorial data sets when installing Minex, you can install them separately.

Activity: Install the data set 1. Double-click the MinexInstallation.msi file on the installation CD.

2. At the Welcome message, click Next.

3. Select Modify, and click Next.

Minex displays the Custom Setup options.

4. Click the icon next to the Tutorial Data Sets option and select This feature will be installed on local hard drive.

5. Click Next, and follow the remaining installation messages.

Data set location

The data set is installed to the following location by default:

Operating system Location

Windows 7 or Windows 8

C:\Users\Public\GEOVIA\GEOVIA Minex\6x\shared\tutorialData\Datasets\Ashes\

Windows XP C:\Documents and Settings\All Users\GEOVIA\GEOVIA Minex\6x\shared\tutorialData\Datasets\Ashes\

Activity: Back up the data set

It is a good idea to keep a backup copy of the data in case you want to restart the tutorial with a fresh set of data later.

1. Start Windows Explorer.

2. Browse to the data set.

3. Right-click the Ashes folder, and choose Send To > Compressed (zipped) folder.

4. In Windows Explorer, make a new folder for backups, for example C:\minexBackups, and copy the zip file to that folder.

Setup for this tutorial Activity: Create a Minex project


Create a Minex project

To make it easy to work with your data, you will create a Minex project and set the working directory to the location of the tutorial data (Ashes).

Activity: Create a Minex project

1. Start Minex.

2. Select File > Project > Project Manager.

3. Click New.

4. In the Project Name field, type PitOptimisationTutorial.

5. Browse to the Ashes folder.

Tip: When you are browsing to this folder you can click the Jump to My Documents icon to select a folder that is close to the folder of the data set.

6. Click Finish.

7. The project is set up and the Minex Explorer displays the Ashes folder and subfolders.

Setup for this tutorial Activity: Create a Minex project


Note: If you use Hub to manage your files, Hub status icons are displayed beside the files in the Minex Explorer. For this tutorial, Hub status icons are not shown. For more information on Hub, refer to the Help, or the Hub training guide available with the Minex tutorials.

Tip: In the Minex Explorer you can select the top level folder, which is Ashes for this project, look at the Properties pane, and see the full path of the project. This is useful if you forget, or want to verify, where the data is.

Start the Pit Optimiser Activity: Start the Pit Optimiser


Start the Pit Optimiser

Activity: Start the Pit Optimiser 1. Select OP Design > Pit Optimiser.

The Pit Optimiser form opens.

Fields on the Pit Optimiser form

Field Description

New Parameter File Name

The name of the file to store the parameters

Log File Name The name of the output file created when the Optimiser runs. This file will contain errors and results information.

Structural Model The model name containing seam floor and seam thickness grids. Roof grids are not required. The Model Must contain topography, weathering and a base grid. The output Optimiser grids are also stored in this file.

Quality Model The Model containing density and energy grids.

Note: The grade quality variable on which the sale price is based Must increase with increasing quality value. For example, higher values of BTU/lb or MJ/kg have higher sale values. Ash cannot be used to value coal. Higher ash coal has less value than a low ash coal. If BTU/lb or MJ/kg is unavailable you can use a proxy such as (100- Ash%). See also section 4.

Cost Model Waste mining and coal mining costs can be based on grids having suffixes such as WM and CM respectively. If these grids exist they will be stored in this file. See Section 6 SQL Costs.



Field Description

Topography Grid Project topography.

Note: As the Optimiser block model is based on the topography grid, it is often advisable to run on a coarser topography for optimisation. Optimisation may be run on a 50 x 50 mesh grid, while the original topography may be 5 x 5. If a weathering grid is unavailable then use topography.

Weathering Grid Use topography if weathering is unavailable. Any coal above weathering is set to be waste.

Note: As the Optimiser block model is based on the topography grid, it is often advisable to run on a coarser topography for optimisation. Optimisation may be run on a 50 x 50 mesh grid, while the original topography may be 5 x 5. If a weathering grid is unavailable then use topography

Base Grid Usually the basal seam floor or a maximum depth grid. For example the user may create a grid as TOPS 200 as the base for the pit. Coal below this base would not be considered.

Seam List (.B35) Seam B35 file used to list seams in stratigraphic order.

Density Grid Suffix Usually RD

Density Grid Default Usually 1.3 or 1.4. This value is used if the density grids don't exist

Washery Yield Grid Suffix

A grid suffix such as YD. These grids will contain wash plant yield or recovery expressed as a percentage. See Section 5.

Washery Yield Default (%)

A default value used when the YD grid doesnt exist. Yield is expressed in percent.

Grade Grid Suffix Usually SE or CV or BTU or in coal an energy value grid. The value of the coal must increase as the grid increases. Ash can't be used as a value.


Sale Value/Grade Unit ($/unit)

Price of a SE unit. For example if SE varies from 28 to 33 and this value is 1, then sale price will be $28 to $33/tonne.


Grade Grid Default Energy value used if grid values dont exist.

Grade Grid Cutoff Coal with less SE will be wasted.

Note: All optimisers will waste coal or ore that is uneconomical. However coal below a cut-off or market specification may have no market value. Setting a cut-off will ensure coal below cut-off is wasted. Setting the cut-off to a low value say 0, will allow the Optimiser to set its own cut-off.

Minimum Seam Thickness (m)

Coal less than this thickness will be wasted.

Pit Recovery (%) Allows for wastage of some coal. The lost coal is not treated as waste.

Pit Slope (degrees) Average slope for optimisation.

Z Sub-Blocks (max=8)

An integer between 1 and 8 usually set at 4 or 5. The primary block size say 50x50x50 is divided to 50x50x10 for an input of 5. The Optimiser may modify the Z value to meet slope inputs. So the block could be 50x50x11 or 50x50x12.7 where this combination better meets an input wall slope.

Minimum Mining Width (m)

Allows trivial spotty pits to be removed.

Note: This option eliminates trivial pits which are less than this width in



Field Description

diameter. These pits are usually uneconomical by the time a practical ramp is constructed. Using this option is not however optimal, these trivial pits are economic under the criteria given.

Waste Mining Cost ($/bcm)

The operating cost of mining waste. Should include drill and blast, loading and haulage.

Waste Lift Cost ($/bcm/m)

Extra haulage cost can be added for depth.

Waste Exit Elevation (m)

Point at which waste is deemed to leave the pit rim. Depth costs are incremented to this elevation.

Waste Mining Cost Grid Suffix

Grids with the seam name and a WM suffix can be created using tools such as SQL. Refer Section 7. The Optimiser will if they exist use these grids for costs.

Coal Mining Cost ($/bcm)

The coal mining costs expressed in $/bcm not $/tonne.

Coal Lift Cost ($/bcm/m)

The coal lift cost expressed in $ per bcm of coal per metre of lift to the exit elevation.

Coal Exit Elevation (m)

Elevation at which coal exits pit.

Coal Mining Cost Grid Suffix

Usually CM for coal Mining. These grids are expressed in $/bcm and typically are used where costs need to vary with depth or location or seam. See Section 7.

Coal Wash Cost ($/feed tonne)

The cost of washing coal in $/input or feed tonne.

Note: As the wash cost is measured in $/tonne it is often used to cover many other costs. For example, pit services (lighting, roads, pumps, supervision, rehabilitation etc) could be added to this figure.

Start Discount Factor

The first Optimiser run will be run at this price.

End Discount Factor The last Optimiser run will be run at this price.

Note: This value can exceed 1. For example if the value is 1.10, the coal is valued at 110% of sale price.

Discount Step Increments will be run between the above prices.

Output Grid Prefix All output grids will be prefixed with this name.

Note: To create nested pits, the first pit at say 30% of sale price is the input topography for the second run at say 35% of sale price. To facilitate this cascading system the output optimum pit grids must be written to the input structure file.

.

Start the Pit Optimiser Activity: Save and view the input parameters


Activity: Save and view the input parameters

1. Fill in the Pit Optimiser form as shown.

2. Click the Save button.

3. Click OK on the Initial Breakeven Strip Ratio form.

4. Click OK on the Save Parameter File form.

Start the Pit Optimiser Activity: Save and view the input parameters


Save will write two files in the project directory:

.MNX commands which will be used by the Pit Optimiser

a .bat file called Run_.bat that will run the .mnx file

The files are visible in the Filesystem tab of the Minex Explorer.

Start the Pit Optimiser Activity: Run the Pit Optimiser


Activity: Run the Pit Optimiser

1. On the Pit Optimiser form, click Save & Run.

2. Click Yes on the Parameter File Exists form.

3. Click OK on the Initial Breakeven Strip Ratio form.

4. Click Yes to run the Pit Optimiser.

Note: You can click No to modify the input parameters.

Start the Pit Optimiser Activity: Run the Pit Optimiser


5. Click OK on the Running the Pit Optimiser form to run the Pit Optimiser.

6. Click Exit to exit the Pit Optimiser form and discard all entered values.

7. To confirm exiting, click OK.

Fault Block Geological Models Activity: Run the Pit Optimiser


Fault Block Geological Models

For Fault Block Models there are no additional commands required.

mrcopn will detect if the input model is a faulted model and builds the 3D block model Fault Block by Fault Block. In stratigraphic mode, STRAT=YES, the interburden created between overthrusted seams (see below) is handled by setting the costs values to the default values. This includes setting these regions to any polygonal defined haulage costs that fall in this zone.

The optimised floor below was generated using STRAT=NO.

Coal or Ore Value Activity: Run the Pit Optimiser


Coal or Ore Value

The Pit Optimiser uses a grade value like energy to determine the value of the coal. For example, if 28kcal/kg coal is sold at $30FOB/tonne then the value could be expressed as $1.07/kcal. Then 20kcal/kg coal would be valued at $21.42/tonne.

Unmarketable coal, say coal below 18kcal/kg, should be wasted using the cut-off grade switch.

Typical questions in optimisation are:

Should I optimise at the mine or at the port?

How do I optimise for extra elements?

What to do with bauxite and alumina?

What about multiple coal products?

Optimise at the mine or port

It is generally best to optimise at the mine and remove the downstream costs from the optimisation process. Using the above figures and downstream costs as shown in the following table, coal can be considered sold at $20/tonne ($30FOB less $10 for downstream costs).

FOB Free on board means the coal is sold free of any costs loaded on the ship. The supplier pays all costs to get it into the ship. The buyer pays unloading and shipping costs.

FIS free in store means the seller pays shipping and unloading. The coal is delivered to the buyers store.

Downstream costs

RAIL HAULAGE $ 5.00

PORT CHARGES $ 2.00

ROYALTIES $ 2.00

DEMURRAGE $ 1.00

TOTAL $ 10.00

In this case the Optimiser would use a sale value of 20/28 = $0.71/kcal. Optimising at the mine makes sense as the downstream costs, while real, are not controllable by the mine. The mine can change mining costs using contractors or larger equipment etc, however it cant rapidly change rail port or royalty costs.

Optimise bauxite and alumina

In cases such as bauxite the process of refining bauxite into alumina adds value and the process of converting alumina to aluminium adds value. The average Australian 2006 export commodity values illustrate this value add:

Bauxite averaged $22/tonne,

Alumina averaged $362/tonne and

Aluminum averaged $2974/tonne

What is measured in the ground and in the model is the bauxite or %Al or %Al2O3 and this is what needs to be optimised.

In bauxite processing, the cost of caustic soda is critical and the elements that consume caustic such as silica or iron can be as critical in determining the value of the alumina content. As with the gold/copper example, local logic is required to determine the value based on these chemical components.

Coal or Ore Value Activity: Run the Pit Optimiser


Optimise multiple coal products

For example a coal deposit creates three products.

Coking sold at $80/tonne,

Blending or middlings sold at approximately $30/tonne and

Thermal sold at $50/tonne.

The coking coal is washed at a low SG and produces a coking coal of say 8% ash. The yield is approximately 50%. The coal rejected from the washing process is rewashed and produces a secondary product (middlings) with an ash of 25% and a yield of approximately 15%. The thermal coal has an ash of 13% and a yield of 70%. Thermal coal is washed only once. Grid suffixes are as follows:

PY Primary yield of coking coal

SY Secondary yield of coking coal

PA Primary ash of coking coal

SA Secondary ash of coking coal

TY Yield of thermal coal

TA Ash of thermal coal

From an SQL point of view it is easier to have PY SY and TY for all seams with TY = 0 on the coking coals and PY and SY = 0 on the thermal coals.

You can use this formula to calculate the coal sale value (SV):

SV = 80 x RD x PY/100 + 50 x RD x TY/100 + 50 x 0.60 x RD x SY/100

Note: As the yields are in percentages they must be divided by 100.

As RD is used in creating the SV it must NOT be double counted. When the Optimiser is run, a density default of 1.0 and a dummy RD suffix such as XX would be used.

Washing Costs and Yield Activity: Run the Pit Optimiser


Washing Costs and Yield

You can use the .mnx file to manipulate washability data to reflect practical plant recovery. The menu will not allow this flexibility as it assumes perfect plant efficiency.

You can edit the .mnx file using the information given below. The first example assumes all coal is washed with 100% recovery and a cost of $10/tonne.

WASH FEED_STOCK=0,WASH_REC=100,WASH_COST=10.000

WASH FEED_STOCK=100.00,WASH_REC=100,WASH_COST=10.000

The expression WASH_FEED_STOCK refers to the value of the yield grid for the seam of that block. For example, a yield grid suffix YD has a value of 70% then the actual yield used is raised to 100% as defined by the WASH_REC entries.

Essentially the two entries define yield and cost can be plotted as shown in the following image. Here the implication is that all coal is bypassed (100% yield) and processing costs are constant at $10/tonne.

0

20

40

60

80

100

120

0 20 40 60 80 100 120

GRID INPUT YIELD

CO

ST

& A

CT

UA

L Y

IEL

D

ACTUAL YIELD

WASH COST/FEED TONNE

0

20

40

60

80

100

120

0 20 40 60 80 100 120

GRID INPUT YIELD

CO

ST

& A

CT

UA

L Y

IEL

D

ACTUAL YIELD




In the next example, wash yield has been downgraded 5% to compensate for the slim core yield overstating true or practical yield. Costs are allowed to fall as the yield increases. This could reflect lower reject disposal costs as shown in the following example.

WASH FEED_STOCK=0,WASH_REC=0,WASH_COST=10




0

10

20

30

40

50

60

70

80

90

100

0 20 40 60 80 100 120

SLIM CORE MODELLED YIELD

YIE

LD


ACTU

AL Y

IELD

0

10

20

30

40

50

60

70

80

90

100

0 20 40 60 80 100 120

SLIM CORE MODELLED YIELD

YIE

LD


ACTU

AL Y

IELD



The next example uses ASH as the feed stock (bolded below). Here the assumption is that low ash coal (below 12%) can be bypassed at 100% yield with a low cost of $3/tonne to cover crushing. Above 12.1% the recovery falls and the costs increase. Here ASH is a proxy for yield but in the syntax of the Optimiser ASH is WASH_FEED_STOCK a shown in the following example.

- GRADE_PARAMS GRADE_CUT=0,SALE_PRICE=1,

- GRADE_SUFF=SE,YIELD_SUFF=AS,DENSITY_SUFF=RD,

- DILUTION_THICK=0.0,QUALITY_DILUTION=0.0,

- YIELD_DILUTION=0,MINIMUM_THICK=0.3



WASH FEED_STOCK=12.1,WASH_REC=80,WASH_COST=9


0

20

40

60

80

100

120

0 20 40 60 80 100 120

ROM ASH

YIE

LD

ACTUAL YIELD


0

20

40

60

80

100

120

0 20 40 60 80 100 120

ROM ASH

YIE

LD

ACTUAL YIELD


The washability definition must cover the range of input feed stock. So if you are using ash as the Feed stock and ash varies from 1 to 50% then this range must be defined. If you are using BTU as the feed stock and BTU varies from 5000 to 13000, then the definition must cover this range. The lines below will cover a BTU case:




Output Grids Activity: Run the Pit Optimiser


Output Grids

The output from the Pit Optimiser is a set of nested pits as shown in the following image. The naming convention used is a prefix and a suffix. The suffix 30, 40 110 etc represents the sale value. Therefore, the grid OPT080 represents an Optimiser run at 80% of the sale price.

You can plot each grid in plan 3D or section. Each grid is assigned a surface number that will show the nested sequence. The colours indicate the incremental size of each nested pit.

This following example shows the sequence in white, green blue as sale price increases.

When you run nested pits some pits may not be economical. For example, a sale price of 10% may not generate an economic pit. Similarly if using a 30% pit as the topography for a 32% pit, it is possible that there will be no additional economic material in this 2% increment. Obviously the generation of an optimum pit depends on the deposit characteristics and the costs applied.

In both cases the Pit Optimiser will output the incremental grid as OPT10 or OPT32 as these grids are used as topography for the next increment.

Reporting Points Activity: Report on grids and costs


Reporting Points

You can output a report on the grids and costs for X Y coordinates. The report point can be useful when validating a model and the costs used. The menu will not allow you to define a report point. It simply assigns a dummy coordinate of (1000, 120000). You can edit this coordinate to be a coordinate inside your deposit.

When the Optimiser program runs the report, point output is placed in a .txt file with a similar name PitOptim_PointReportxxx12May02123519.txt. Where xxx is the user id followed by the date.

Activity: Report on grids and costs

1. In the Minex Explorer, double-click the Run_MRCOPN.bat file, located in the Ashes project folder.

The Windows command pane will open while the batch file runs.

The txt file similar to PitOptim_PointReport12May02123519.txt is added to the project folder.

2. Double click the text file.

Reporting Points Activity: Report on grids and costs


The contents of this file is shown below (left) and explained on the right.

Processing Seam:TT23 **** Waste Layer **** Roof : 132.61 Floor: 127.94 Waste Extraction Cost: 4.62 Waste haulage Cost: 0.00 Waste haul time : 0.00 Waste to Plant : 0.00 Waste Haulage Factor : 1.00 Waste Mining Costs : -4.62 Insitu Value : -4.62 **** ORE Layer **** Roof : 127.94 Floor: 127.30 Waste Extraction Cost: 4.62 Waste haulage Cost: 0.00 Waste haul time : 0.00 Waste to Plant : 0.00 Waste Haulage Factor : 1.00 Waste Mining Costs : -4.62 Ore Density : 1.56 Ore Grade Var : 35.36 Ore Yield Var : 81.57 Ore Extraction Cost: 29.61 Ore haulage Cost: 0.00 Ore haulage time : 0.00 Ore to Plant : 0.00 Ore Haulage Factor : 1.00 Ore Mining Costs : -29.61 Tonnage of Ore : 1.56 Unit Sale Price : 35.3584 Product yield : 81.57 Sale Price : 44.87 Cost Milling : 0.00 Cost Mining : -29.61 Net Value Ore : 60.14 Insitu Value : 60.14

The next is ORE Layer or coal, note same cost $4.62 is reported. MRCOPN will only use this cost if the coal is wasted.

Coal goes from 127.94 to 127.30 so its 0.64 metres thick.

Density is 1.56 yield is 81.57 sale price is 35.36 so sale price per cubic metre is $44.87.

The actual sale price is 2 x 44.87 = 89.74/bcm (as FF =2 in this example)

Coal cost is 29.61 (recall this cost is expressed as $/bcm)

The final ore value has a difference $89.74 - 29.61) = $60.14/bcm

As $60.14 is greater than 4.62 so it is treated as ore.

If the value was less than 4.62 then we would treat it as waste (EG low yield low price)

At this point TTIB has a cost of $4.62 so entry is minus (-4.62).

Advanced costs using SQLs Activity: Report on grids and costs


Advanced costs using SQLs

Listed below are some examples of using grid SQL commands to set costs for the Pit Optimiser.

Note: This is not a training exercise in using SQLs.

Waste costs typically increase with depth. However a more complex case could involve:

Surface costs as waste is transported out of the pit.

Waste at depth is cheaper as it is back-filled and

Thin waste is more expensive than thick waste. Larger equipment can be used to mine thick waste.

In this case a grid with a suffix such as WM is created for each seam using an SQL. Assumptions are:

The top 100 metres of waste material is transported out of the pit at $2.50/bcm, lower waste material is transported into the pit at $1.50/bcm.

Equipment is used to rip thin waste less than 2 metres in thickness at $1.50/bcm. This material is loaded by equipment at $0.75/bcm.

Thicker waste is drilled and blasted at $1.00/bcm and loaded by equipment at $0.50/bcm.

An SQL to create the WM grids can use the seam floor (SF) and seam interburden grids (IB) as input grids. The grid should be created as TOPS minus 100 (TOPS-100) and saved as TOPSm100. The IB and SF grids should exist in a merged grid so they exist everywhere.

An SQL command using these assumptions would read as follows:

EXTERNAL TOPSm100, SF, IB, WM

! X THIN AND DEEP

SELECT X

WHERE SF # NULL

AND SF < TOPSm100

AND IB < 2

IF SELECT X

WM = 1.50 + 1.50

WM = WM + 0.75

ENDIF

! Y THICK AND DEEP

SELECT Y

WHERE SF # NULL

AND SF < TOPSm100

AND IB >= 2

IF SELECT Y

WM = 1.50 + 1.00

WM = WM + 0.50

ENDIF

! Z THICK AND SHALLOW

SELECT Z

WHERE SF # NULL

AND SF >= TOPSm100

AND IB >= 2

IF SELECT Z

WM = 1.50 + 1.00

Advanced costs using SQLs Activity: Report on grids and costs


WM = WM + 0.50

ENDIF

! A THIN AND SHALLOW

SELECT A

WHERE SF # NULL

AND SF >= TOPSm100

AND IB < 2

IF SELECT A

WM = 1.50 + 1.50

WM = WM + 0.75

ENDIF

Steep Dip Deposits Activity: Report on grids and costs


Steep Dip Deposits

The Pit Optimiser uses a set of seams in stratigraphic order to generate the cost and revenue model. Waste below the base seam is not assigned a cost as the base seam is the logical pit floor.

A problem can be caused when the pit wall slope is flatter than the seam. In the following example the stratigraphy is A B C and the waste mining cost is $3/cubic metre.

0

3

3

0

3

A

B

C

0

3

3

0

3

A

B

C

In the Optimiser the waste above A, above B, and above C are all assigned $3 costs. However, the waste below C is not in the stratigraphic definition and is assigned a cost of $0. This can cause the pit to grow artificially in the area below the base seam. In this case you can introduce a new base seam below the C seam using grid manipulation. The new seam should be given a thickness of zero so there is no revenue introduced. This will correct the problem as shown in the following image.

3

3

3

3

3

A

B

C

D

3

3

3

3

3

A

B

C

3

3

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B

C

D

Advanced Wall Slope Control Activity: Report on grids and costs


Advanced Wall Slope Control

Optimiser slopes

The optimiser by default defines wall lopes in 8 directions or octants. Users can by editing the command file also define slopes using specific seams or interburdens or by using polygons. The three methods of slope definition are discussed below.

Octants

The Pit Optimiser defines slope angles in eight octants. These are defined in the MNX file as

PIT_PARAM SLOPE_ANGLE=(15,20,25,30,35,40,45,50),Z_SUB=4,

The first octant is North with the zones then moving in a clockwise direction. This is shown in the following image.

15o

20o

25o

north

30o

35o40o

45o

50o15o

20o

25o

north

30o

35o40o

45o

50o

Seams

Each seam or waste (interburden) can be defined as a rock type with a maximum of 16 rock types allowed. In the following script, lower seams are defined as rock type 1 and assigned a slope of 16

o. All

other seams are assigned a slope of 32o. The result is shown in following image. Only the seams with

rock type 1 are listed, the undefined seams (and waste) are assigned the default value in this case 32o

PIT_PARAM SLOPE_ANGLE=32.0,Z_SUB=5

DEFAULTS SEAM=113C,ORE_ROCK_TYPE=1,WASTE_ROCK_TYPE=1

DEFAULTS SEAM=114C,ORE_ROCK_TYPE=1,WASTE_ROCK_TYPE=1

DEFAULTS SEAM=067N,ORE_ROCK_TYPE=1,WASTE_ROCK_TYPE=1

DEFAULTS SEAM=070N,ORE_ROCK_TYPE=1,WASTE_ROCK_TYPE=1

SLOPE_ANGLES ROCK_TYPE=1,SLOPE_ANGLE=16

Advanced Wall Slope Control Activity: Report on grids and costs


The following image shows 32o wall slopes assigned to upper seams. 16

o for lower seams.

Slope 16o for lower seams

Slope 32o

for upper seams

Slope 16o for lower seams

Slope 32o

for upper seams

Polygons

Polygons or masks can be used to define rock types. Rock types can then be assigned a slope angle. Up to 16 rock types can be defined. A rock type is defined using a polygon and an elevation range. In the following example the default slope is 55

o. Three polygons define the slopes as 45, 35 and 40 between

the elevations -1000Z and 1000Z

PIT_PARAM SLOPE_ANGLE=(45),

-Z_SUB=4,MINIMUM_MINING=0

ROCK_TYPES DEPTH=(-1000,1000),ROCK_TYPE=1,POLY_IDENT=45






When using slope polygons the geometry file must be listed at the top of the MNX file.

//TER

//DD GRDFILE DSN=MODEL.GRD,DISP=OLD,UNIT=PACKA

//DD OPTPIT DSN=MODEL.GRD,DISP=OLD,UNIT=PACKA

//DD QUALITY DSN=QUALITY.GRD,DISP=OLD,UNIT=PACKA

//DD MAPIN DSN=UNSW.GM3,DISP=OLD,UNIT=PACKA

//DD SYSIN *

System information Activity: Report on grids and costs


System information

The Pit Optimiser is limited to input grids with less than 4,000,000 mesh points or a grid of 2000 x 2000 points.

Summary Activity: Report on grids and costs


Summary

Congratulations on completing this tutorial. You should now have a greater understanding of the Minex pit optimising functions. You have learnt a number of concepts and topics including how to:

determine how coal is valued

determine washing costs and yields

create a set of nested pits

create output reports

determine advanced mining costs using SQL commands

use the Optimiser in steep dip deposits

Appendix A Activity: Report on grids and costs


Appendix A

MNX Files

The .MNX file is a Job Control Language file or JCL which is created using the input parameters. You can edit the .MNX file if required. An example file is shown below.

//TER //DD SYSPRINT DSN=TRAINING.LOG,DIS=NEW,UNIT=PACKA //DD GRDFILE DSN=MODEL.grd,DISP=OLD,UNIT=PACKA //DD QUALITY DSN=MODEL.grd,DISP=SHR,UNIT=PACKA //DD COST DSN=cost.grd,DISP=OLD,UNIT=PACKA //DD SYSIN * //* INIT SEAMS=(SW1,SW2,AB,ST,DL,UGB,MGB1,MGB2, - ULGB,LLGB,UDB,UDBS,LDBS,LDB,WGG1,WGG2, - ,) - DENSITY_DEFAULT=(1.4), - GRADE_QUALITY=(28), - YIELD_QUALITY=(80), - STRUCTURE_DDNAME=GRDFILE, - QUALITY_DDNAME=QUALITY - COST_MODEL_DDNAME=COST GRADE_PARAMS GRADE_CUT=18, - SALE_PRICE=1.0, - GRADE_SUFF=SE, - DENSITY_SUFF=RD, - YIELD_SUFFIX=YD, - DILUTION_THICK=0.0, - QUALITY_DILUTION=0.0, - YIELD_DILUTION=0.0, - MINIMUM_THICK=0.3 WASH FEED_STOCK=0,WASH_REC=0,WASH_COST=5 WASH FEED_STOCK=1.00,WASH_REC=1,WASH_COST=5 WASH FEED_STOCK=100.00,WASH_REC=100,WASH_COST=5 ORE_COSTS COST_OF_EXT=(5), - COST_TO_PLANT=0.0, - REFERENCE_RL=100, - COST_OF_LIFT=0.001, - ORE_MINING_REC=100, - COST_GRID_SUFFIX=CM WASTE_COSTS COST_OF_EXT=2, - REFERENCE_RL=100, - COST_OF_LIFT=0.001, - COST_GRID_SUFFIX=WM PIT_PARAM SLOPE_ANGLE=(45,45,45,45,45,45,45,45),Z_SUB=4, - MINIMUM_MINING_WIDTH=(0) COMPUTE TOPO=TOPS_OPT, - BASE=WGG2SF, - WEATHER=BOW, - OUTPUT_DDNAME=GRDFILE, - OPT=OPT030, - DESC=('Optimum pit discount 0.3','Surface 3'), - FORCING_PAR=0.0,REPORT_POINT=(10000,120000), - LERCH=YES, - FLOATING_CONE=YES, - CONE_CONV=2, - OPTIMUM_PIT=YES, - MAJOR_CYCLES=50, - SURFACE_NUMBER_RESET=YES, - SET_SURFACE_NUMBER=3 EXIT

THE LOG FILE CONTAINS OUTPUT REPORTS SEAMS LISTED IN STRATIGRAPHIC ORDER. WASHING COSTS ARE FIXED AT $5/FEED TONNE THE WASH TABLE LINES ARE DISCUSSED IN SECTION 6. SLOPES ARE DEFINED IN 8 DIRECTIONS CLOCKWISE FROM NORTH. THE REPORT POINT OPTION WILL CREATE A LIST OF DATA AND COSTS AT THE XY COORDINATE ENTERED.

Appendix A Activity: Edit MNX files


Activity: Edit MNX files

Caution: If you edit the MNX file and then run the Pit Optimiser again, you will overwrite the MNX file. To avoid overwriting the MNX file, use the batch file (Run_.bat) to run the MNX

file externally.

1. In the Minex Explorer, right-click MRCOPN.mnx, and choose Treat as Text.

2. Click OK on the Question form

The file MRCOPN.mnx is shown with the icon . You can edit this file with Source Editor.

3. In the Minex Explorer, right-click MRCOPN.mnx, and select Open.



The Source Editor opens.

Note: When editing or adding statements to the .mnx file, a missing or incorrectly placed comma will cause an error and prevent Pit Optimiser from running.

Tip: To save any changes you make to a text file, click the icon.

File usage

The following are standard ddnames used by the Optimiser. However you can, via commands, declare additional ddnames which must be defined.

Input files

SYSIN Input data set

MODEL Grid file containing topography and other 2D structure grids.

QUALITY Grid file containing quality

MAPIN Optional input map file for haul polygons.

COSTMOD Optional input cost model.

Output files

SYSPRINT Message data set

GRDFILE Same grid file as above, but now contains 2D grid of optimum pit

COSTMOD Optional input cost model.

Input commands

Input consists of the following statements:

Initialise Selects layers and default grades



Grade_Params Selects grade variables and dilution parameters.

Washing_Params Defines washing yields and costs

Ore_Costs Defines ore mining costs and in-pit haulage cost method 1.

Waste_Costs Defines waste mining costs and in-pit haulage cost method 1.

Defaults Defines defaults on a seam basis

Haulage_Elevations Defines parameters for haulage cost method 2.

Haulage_Areas Defines parameters for haulage cost method 2.

Truck_Factors Defines parameters for haulage cost method 3.

Truck_Areas Defines parameters for haulage cost method 3.

Rock_Types Defines rock types on the basis of depth or elevation.

Slope_Angles Defines maximum wall slopes for various rock types.

Pit_Parameter Defines side slopes

Compute Computes optimum pit

Exit Exit from program



INITIALIZE Statement

Initialise Seams=(s1,s2........sn),[ Density_Defaults=(d1[,d2...dn])],

[Grade_Quality_Defaults=(g1[,g2...gn])],

[Yield_Quality_Defaults=(yg1[,yg2...ygn])],

[Structure_DDname=dsname],

[Quality_DDname=dqname],[Cost_Model_DDname=dcname]

Seams=(s1,s2........sn)

Seam names to be considered. Any seams not in this list are considered as waste.

Density_Defaults=(d1[,d2...dn])

Density default value. This may be defined on a seam basis by the DEFAULTS command verb.

If there were 10 seams you could nominate.

Density_Defaults = (1.35, 1.41, 1.65, 1.45)

RD Seam 1 = 1.35, Seam 2 = 1.41, Seam 3 = 1.65 and Seam 4 - 10 = 1.45

Grade_Quality_Defaults=(g1[,g2...gn])

Grade quality default value.

If the grade value in the grid is null or the grid does not exist. This is the quality variable used to assess the quality of the coal and on which the sale price is based.

It MUST be used to determine coal sale value and MUST increase in sale value with increasing quality value. For example, BTU/1b or MJ/kg.

Note: ASH can NOT be used since a higher ash is NOT worth more. If BTU/1b or MJ/kg is unavailable you can create a convenient alternative by subtracting the %Ash from 100 and using this alternative variable. Each seam can have its own defaults via the DEFAULTS command verb.

Yield_Quality_Defaults=(yg1[,yg2...ygn])

Yield quality default value if the grade value in the grid is null or the grid does not exist.

This is the quality variable used to compute washing yield (see Washing_Params).

Structure_DDname=dsname

The grid file ddname for accessing structure grids.

Quality_DDname=dqname

The grid file ddname for accessing quality grids.

Cost_Model_DDname=dcname

The grid file ddname for accessing input and output of 2D grid cost models.



GRADE_PARAMS Statement

Grade_Params Grade_Cut_Off=gcut,[Sale_Price=sprice],[Grade_Suff=gsuff],

[Yield_Suff=ysuff],[ Density_Suff=dusff],

[Dilution_Thickness=thkdil],[ Quality_Dilution_Grade=gdil],

[Yield_Dilution_Grade=ydil],

[Minimum_Thickness=thkmin]

Grade_Cut_Off=gcut

Cut off grade for quality.

Coal with lower quality is wasted. Normally set to 0, by setting this cut off to 0 the Optimiser decides what is coal and what is waste. If the coal is of poor grade or very thin, then the Optimiser may treat it as waste.

Sale_Price=sprice

Sale price expressed in $ per unit of quality per unit of mass. That is, $/BTU/ton or $/MJ/tonne.

For example, if the grade specification calls for coal with a calorific value of 6000 BTU/1b and the price is $30 per ton, the sale price would be $0.005/BTU/ton.

Grade_Suff=gsuff

The suffix applied to the seam name to obtain the grid name used to define the quality grade. For example, CV might be the suffix for calorific value.

Yield_Suff=ysuff

The suffix applied to the seam name to obtain the grid name used to define the yield variable. For example, AS might be the suffix for ASH which is later related to washery recovery. Normally use YD - i.e. washery yield suffix.

Density_Suff=dusff

The suffix applied to the seam name to obtain the grid name used to define the density. This is usually RD.

Dilution_Thickness=thkdil

The thickness of dilution to be applied to each seam in computing the recoverable quality. This dilution is only in the computation of cost/benefit and is NOT applied permanently to the seam grids. If a diluted model is being used, then do NOT apply dilutions here.

Quality_Dilution_Grade=gdil

The quality of the waste dilutant. For example, calorific value or Specific Energy, etc.

For example CV Rock = 50 BTU/lb

Yield_Dilution_Grade=ydil

The yield quality of the waste dilutant, e.g. Yield Rock = 50 (% ASH)



Minimum_Thickness=thkmin

The minimum mining thickness (metres or feet). Coal less than this is wasted. Say 0.3m or 1 foot.

WASHING_PARAMS Statement

This command is repeated to set up a table of recoveries and costs for each feedstock grade. A minimum of 2 commands must be given at the top and bottom limits of wash yield.

Washing_Params Feed_Stock_Grade=ygrade,Wash_Recovery=orerec,Wash_Cost=wcost

Feed_Stock_Grade=ygrade

The input yield grade. This usually relates to a quality variable such as ASH or YIELD.

Wash_Recovery=orerec

The washing recovery (yield) at the specified feed stock grade in percent.

Wash_Cost=wcost

The cost of processing the coal per unit mass of feedstock.

For example, $ per ton.



ORE_COSTS Statement

Ore_Costs {Cost_of_Extraction=(oexc1[,oexc2...oexcn])|

Cost_Grid_Suffix=ocgsuff},

[Cost_to_Plant=hcplant,] [Reference_RL=orelev,Cost_of_Lift=orehc,]

[Ore_Mine_Recovery=minrec]

Cost_of_Extraction=(oexc1[,oexc2...oexcn])

Excavation cost for coal, by seam (i.e. loaded into truck) $ per unit volume.

Cost_Grid_Suffix=ocgsuff

Ore cost grid suffix. The grid value must be in $ per unit volume.

Cost_to_Plant=hcplant

Cost of haulage of coal from pit crest to washery. ($ per unit volume). Default=0.0.

Reference_RL=orelev

Reference level at pit crest to which coal must be lifted by trucking. ($ per unit volume).

Note: Only used with Dump Method 1.

Cost_of_Lift=orehc

Cost of lifting coal from pit floor to pit crest ($ per unit volume per unit lift, e.g., $/cubic metre/metre lift or $/cubic yard/foot lift. Default=0.0.


Ore_Mine_Recovery=minrec

Pit recovery for coal, usually 90-95%. Default value=100.0



WASTE_COSTS Statement

Waste_Costs {Cost_Grid_Suffix=wcgsuff|

Cost_of_Extraction=(wexc1[,wexc2...wex cn])},

[Cost_of_Dump=hcdump],

[Reference_RL=wastelev,Cost_of_Lift=wastehc]

[,Default_Cost_of_Extraction=dwexc]

Cost_of_Extraction=(wexc1[,wexc2...wexcn)

Excavation cost for waste (i.e., loaded into truck) ($ per unit volume).

Cost_Grid_Suffix=wcgsuff

The grid suffix for accessing the waste cost grid.

Cost_of_Dump=hcdump

Cost of haulage of waste from pit crest to dump. ($ per unit volume). Default=0.0.

Reference_RL=wastelev

Reference level at pit crest to which waste must be lifted by trucking.


Cost_of_Lift=wastehc

Cost of lifting waste from pit floor to pit crest ($ per unit volume per unit lift, e.g., $/cubic metre/metre lift or $/cubic yard/foot lift). Default=0.0.


Default costs of extraction where waste is not defined as interburden.

Default_Cost_of_Extraction=dwexc

Default excavation cost for undefined waste (i.e., loaded into truck) ($ per unit volume). Default value for dwesc = wexc1, ie costs for first/overburden layer.



DEFAULTS Statements

You can use this statement to override any predefined defaults for nominated seams.

Defaults Seam=sname,

Ore_Cost_of_Extraction=oexcost],[Ore_Haulage_Factor=ohfact],

[Waste_Cost_of_Extraction=wexcost],Waste_Haulage_Factor=whfact],

[Density_Defaults=dens], [Grade_Quality_Defaults=grade],

[Yield_Quality_Defaults=yield],

[Ore_Rock_Type=ortype],[Waste_Rock_Type=wrtype]

Seam=sname

The name of the seam to override the following defaults.

Ore_Cost_of_Extraction=oexcost

Excavation cost for coal (i.e., loaded into truck) $ per unit volume.

Ore_Haulage_Factor=ohfact

Factor to be applied to cost of ore haulage, Default = 1.0

Waste_Cost_of_Extraction=wexcost

Excavation cost for waste (i.e., loaded into truck) $ per unit volume.

Waste_Haulage_Factor=whfact

Factor to be applied to cost of waste haulage, Default = 1.0

Density_Defaults=dens

Density default value. This can be defined on a seam basis by the DEFAULTS command.

Grade_Quality_Defaults=grade

Grade quality default.

You use this quality variable to assess the quality of the coal and on which the sale price is based. It MUST be a variable to determine coal sale value and MUST increase in sale value which increases with quality value, e.g., BTU//1b or MJ/kg.

Note: ASH can NOT be used since a higher value ash is NOT worth more. If BTU/1b or MJ/kg is unavailable, you can create a convenient alternative by subtracting the %ASH from 100 and using this alternative variable. You can define this on a seam basis by the DEFAULTS command.

Yield_Quality_Defaults=yield

Yield quality default.

You use this quality variable to assess the yield of the coal in the processing plant, e.g., recovery may be a function of ash. If this is correct, then this is the default ash content and can be defined on a seam basis by using the DEFAULTS command.



Ore_Rock_Type=ortype

Default ore rock type. Rock types are used to control wall side slope.

Waste_Rock_Type=wrtype

Default waste rock type. You can use rock types to control wall side slope.

Dump Method 2

Dump Method 2 allows the user to define haulage cost tables on the basis of:

Nominating elevation ranges for each table, and within elevation ranges specifying costs associated with a number of elevation ranges.

Optionally using polygons with the same attributes to override the general definition for specific pit zones.

Note: The nominated elevation ranges should not overlap.

Haulage_Elevations Range=(elvmin,elvmax),

Elevations=(elv1,elv2[,...elvn]),

Waste_Costs=(wc1,wc2[,....wcn]),

Ore_Costs=(oc1,oc2[,...ocn])

You can use this statement to define a number of general elevation ranges within which you define haulage costs at a number of specific elevations. The maximum number of elevations in a table is 10.

Range=(elvmin,elvmax)

You use this statement to define the current elevation range.

Elevations=(elv1,elv2[,...elvn])

You use this statement to specify the elevations at which costs are to be nominated. The elevations would normally be within the elevations defined by the elevation range.

Waste_Costs=(wc1,wc2[,....wcn])

You use this statement to specify the waste haulage costs at each of the elevation elv1,elv2elvn.


You use this statement to specify the waste haulage costs at each of the elevation elv1,elv2elvn

Haulage_Area Ident=polyid,

Range=(elvmin,elvmax),

Elevations=(elv1,elv2[,...elvn]),

Waste_Costs=(wc1,wc2[,....wcn]),


You use this statement to specify a number of specific zones using polygons and thus override the haulage costs defined in the prior general definition. The maximum number of haulage areas is 300.

Ident=polyid



You use this statement to specify a polygon identifier (8 characters) which exists in the selected Geometry File. All points within this polygon and within the following elevation ranges will be assigned the associated haulage costs.



Dump Method 3

Dump Method 3 allows the user to define haulage cost tables on the basis of:

Nominating elevation ranges for each table and within pit elevation ranges specifying horizontal distances and dump elevations for both waste and ore truck out-of-pit haulage.

Optionally using polygons with the same attributes to override the general definition for specific pit zones.

Truck_Factors In_Pit_Mode=(y/n),

{Percent_Out_of_Pit=op_per,

Grades=(g1,g2,,,,gn),

Full_Truck_Speeds=(ft1,ft2,,,,ftn),

Empty_Truck_Speeds=(et1,et2,,,,etn),

Panel_Length=pan_len,

Floor_Space=floor_sp,

Fixed_Times=(load_t,dump_t),

Wall_Slopes=(high_wall_slope,spoil_slope)|

Timing_Constants=(c1,c2,c3)}

Waste_Truck_Cost=wtc,

Ore_Truck_Cost=otc,

Waste_Truck_Load_BCM=wtvol,

Ore_Truck_Load_Tonnes=otton,

Truck_Utilisation=truck_util,

Range_Elevation_Metres=(elvmin,elvmax),

Horizontal_Distance_Kilometres=(hd1,kd2,hd3,hd4),

Dump_Elevation_Metres=(de1,de2,de3,de4)

Note: The nominated elevation ranges should not overlap.

Range_Elevation_Metres=(elvmin,elvmax)

You use this statement to define the current elevation range.

Horizontal_Distance_Kilometres=(wdmin,wdmax,odmin,odmax),

Dump_Elevation_Metres=(wemin,wemax,oemin,oemax)

You use this statement to specify the waste haulage costs at each of the elevation elv1,elv2elvn

Truck_Areas Ident=polyid,

Range_Elevation_Metres=(elvmin,elvmax),

Horizontal_Distance_Kilometres=(hd1,kd2,hd3,hd4),

Dump_Elevation_Metres=(de1,de2,de3,de4)

You use this statement to specify a number of specific zones using polygons and thus override the haulage costs defined in the previous definition. The maximum number of haulage areas is 300.

Ident=polyid

You use this statement to specify a polygon identifier (8 characters) which exists in the select Geometry File. All points within this polygon and within the following elevation ranges will be assigned the associated haulage costs.



Rock_Types

You can define a rock type that is either a constant depth from the topographic surface or a constant elevation within the deposit.

In the other rock type definition listed under DEFAULTS it relates to either a seam or the overburden immediately above it. The option Rock _Types allows the input of a rock type that may not necessarily be adjacent to a seam. For example A sill.

Tip: Only enter a rock type for a particular rock that will affect the pit slope. For example, very weak mudstone between quartz-arenitic sandstone which cannot hold the same angle of cut compared to the sandstone.

Rock_Types {Depth=(d1,d2)| Elevation=(e1,e2)},

Rock_Type=rtype

Depth=(d1,d2) [,Poly_Ident=ident]

The rock type is defined as being a constant depth below the topographic surface. Essentially this rock type will follow the topographic surface at depth x away from topography. This requires the input of the rock roof and floor as a depth from topography.

The rock type may also be optionally constrained in this area by defining a polygon.

For example:

Depth = (100,105)

In this example the rock roof and floor is 100m and 105m below topography respectively.

Elevation=(e1,e2)

You can use this for a completely flat rock structure. This requires the input of the rock roof and floor as an elevation from sea level.

For example:

Elevation = (100,95)

In this example the rock roof is at an RL of 100m and the floor is at an RL of 95m.

Poly_Ident=ident

Nominate a polygon identification name that will define the rock type by area. In combination with Depth or Elevation this will constrain the rock type both vertically and horizontally. If not given then the rock type is not constrained horizontally.

Rock_Type=rtype

Nominate the rock type (number) here, which corresponds to either, the rock defined by Elevation or Depth above.

Maximum rock type number is xx.



Slope_Angles

Slope_Angles Rock_Type=rt,

{Slope_Angle=(s1[,s2...sn])|Side_Slope=(a1[,a2,a3...an]) }

You use this statement to define the maximum wall slopes for a particular rock type.

If a layer or seam does not have a unique rock type, it will use the default slope angle defined in Pit_Parameters.

Rock_Type=rtype

Enter in the rock type either defined in the DEFAULT menu or Rock_Types menu you wish to define a slope angle for.

Slope_Angle=(s1[,s2...sn])

You can define the slope angle (in degrees from horizontal) for the rock for eight different directions within the pit. Enter in the angles required according to the following table:

Side_Slope=(a1[,a2,a3...an])

You use this statement to define up to 8 slopes in the form of vertical/horizontal ratio.

The directions inside a pit are divided into 8 segments pointing in the 8 cardinal direction, clockwise from North.



PIT_PARAMETERS Statement

Pit_Parameters

{Slope_Angle=(a1[,a2,a3...a8])|Side_Slope=(s1[,s2,s3...s8])},

[Z_Block_Size=zbsize],[Z_Datum=zdatum],

[Z_Sub_Intervals=zsubint],

[Minimum_Mining_Width=minwidth]

Slope_Angle=(a1[,a2,a3...a8])

The required sidewall slope expressed as degrees from horizontal.

Side_Slope=(s1[,s2,s3...s8])

The required sidewall slope expressed as horizontal run divided by vertical climb. That is, 0.5 is equivalent to 63 degrees from the horizontal.

Z_Block_Size=zbsize

The required primary thickness (or depth) of each block.

Z_Datum=zdatum

The elevation of the block model base. The default is the minimum of the base limit grid. This value is not normally defined unless there a specific reason for the datum (eg for direct comparison with another model).

Z_Sub_Intervals=zsubint

The number of height sub-interval for each block. default =1. The value is used to obtain a better approximation of wall slope.

Minimum_Mining_Width=minwidt

The minimum floor mining width default = block size.



COMPUTE Statement

Compute

Topo_Grid_Name=tgrid,[Base_Grid_Name=bgrid],Weather_Grid_Name=wgrid],

Optimum_Grid_Name=ogname,[Output_DDname=odname],

[Forcing_Parameter=fparam],[Stratigraphic_Sequence={YES|NO}],

[Report_Point=(PX,PY)],

[{2D_Grid_Cost_Model=NO|2D_Grid_Cost_Model=YES,

Output_Cost_Model_DDname=ocname,

Waste_Cost_Grid_Suffix=wcsuff,

Ore_Cost_Grid_Suffix=ocsuff,Ore_Value_Grid_Suffix=ovsuf}]

[Optimum_Pit={YES|NO},]

{Floating_Cone=NO| Floating_Cone=YES,[Cone_Convergence=cconvg]},

{Lerch_Grossman =YES,[Major_Cycles=[mcycles]],

[Convergence_Cycles=cycleno1,lgconv1,]|Lerch_Grossman=NO}

[Search_to_Top={NO|YES}], [Input_File={No|YES}],[Output_File={NO|YES}],

[Datamine_Format={NO|YES},Genesis_Format={NO|YES}]

[,Surface_Number_Reset (YES/NO)][, Set_Surface_Number=surfno]

Topo_Grid_Name=tgrid

The name of the top grid. This is usually TOPS (the topography).

Base_Grid_Name=bgrid

The name of the base grid. This is usually the basal seam. However, you can modify in the following circumstances:

Where the base seam is not continuous over the entire area of interest and other seams still exit, it may be advisable to create a base grid by taking the logical OR of the structure floor of the lowest seams.

Where surface features, lease boundaries, and obstructions would prevent a pit form existing in certain areas, these can be removed from consideration by masking the base grid and using that logical OR function with the top grid to produce a base grid which will act as an envelope for the optimisation.

Weather_Grid_Name=wgrid

The name of the optional weathering surface grid. If specified all ore above this surface is wasted.

Optimum_Grid_Name=ogname

The name of the output optimum pit limit grid, which will be computed and stored.

Output_DDname=odname

The name of the output file ddname in which optimum pit limit grid will be stored. The default is GRDFILE.

Forcing_Parameter=fparam

The forcing factor is a discount on the sale price and is used to create nested optimum pits. The default = 0.0.

Effective_Sale_price = (1.0 fparam) x Sale_price

Stratigraphic_Sequence={YES|NO}



A response of NO assumes the structural model need not maintain a correct stratigraphic sequence. This may result from extreme faulting and reversal of the geology. In such cases it is not possible to differentiate the cost of mining of each waste layer. The default response is YES.

Report_Point=(PX,PY)

If specified the program shall report all cost data for each seam at this (x,y) location.

2D_Grid_Cost_Model={NO|YES}

A response of YES shall output a 2D grid cost model. The default is NO. The cost grids will be written to the file defined by the ddname ocname, the default for ocname is odname.

If the response is YES three 2D grids are written:

Waste cost model.

Ore Cost model.

Ore Sale Value model.

The grid names are constructed from the seam name plus a suffix.

All models are in $/unit volume.

Output_Cost_Model_DDname=ocname

This is the name for the file to contain the output cost model grids. Default = odname.

Waste_Cost_Grid_Suffix=wcsuff

The suffix for the 2D waste cost grid model.

Ore_Cost_Grid_Suffix=ocsuff

The suffix for the 2D ore cost grid model.

Ore_Value_Grid_Suffix=ovsuf

The suffix for the 2D ore value grid model.

Optimum_Pit={YES|NO}

A response of NO shall not compute an optimum pit however, requests to output a 2D grid cost model or 3D block cost model will be performed.

Floating_Cone={NO|YES}

A response of YES will first run a floating cone pass effectively lowering topography prior to running the Lerch_Grossman optimum pit algorithm.



Note: the floating cone is sub-optimal and may on rare occasions over-mine the deposit. However, the use of floating cone pre

pit optimisation

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