PCBC Block Cave Scheduling

7/24/2019 PCBC Block Cave Scheduling

1/17

1

BLOCK CAVE PRODUCTION SCHEDULING USING PCBC

Tony Diering, Gemcom Software International Inc., Vancouver, Canada

Otto Richter, Gemcom Australia, Perth, Australia

Daniel Villa, Gemcom Software International Inc., Vancouver, Canada

Abstract

Gemcom PCBCTMis a software package which

has been developed over the last 22 years for the

planning and scheduling of block cave mines. This

paper presents an update of the various research and

development activities done to PCBC recently. It

also provides an overview of the current capabilities

of the software including tools for both feasibility

type studies as well as tools for operating mines.

PCBC is used extensively by prospective and

operating block cave mines and some of the recent

applications are described.

Introduction

History

PCBC was first developed in 1988 for the

Premier Diamond Mine in South Africa(Diering,

2000). In 1992, the first production scheduler was

added to the system and in 1994 a significant upgradewas done for Northparkes Mine in preparation for

their Lift 1. PCBC was upgraded to Microsoft

Windows operating system in 1996. In 2002, the

Cave Management System (CMS) was developed for

Freeport DOZ mine and this was upgraded to provide

SQL Server database support in 2003 for Finsch

Diamond mine(Diering, 2004). A new algorithm

called Template Mixing (Diering, 2007) was added to

provide better and alternate flow modeling options to

users.

More recently, various enhancements to the

production scheduler and other areas of the program

have been completed some of which are describedhere.

It is worth noting that the block cave market (in

terms of software) is very limited. As such, it is

difficult to fund high quality research and program

development. We at Gemcom Software International

Inc. have been very fortunate to have companies

sponsor custom development activities within PCBC

over the years. These companies are listed in the

acknowledgements section of this paper.

Typical project workflow

A significant number of block cave projects

have been studied using PCBC over its 20 year

history. During that time, a well used work flow has

evolved which is usually used as a guideline for new

projects.

Conceptually, the steps are as follows:

Figure out what is in the ground (geological

model)

Work out where you want to mine (X,Y,Z limits)

Work out the tons and grade that you will get

from those limits

Work out how long it will take (time)

Optimize and iterate to add further value to the

project.

Repeat the whole process every time a new

geological model is produced as the project

evolves.

The overall steps in the process are described

below:

Footprint Finder. This is an application which

works off the geological block model and whose

primary objective is to help assess the best

elevation (or elevations) for the block caving

footprint (Z extent of the mine)

Generate draw points. Setting up draw points

requires assessment of draw point spacing,

tunnel orientation etc. (X,Y extents)

Construct slice file. This is the process of

conversion of a geological model to be aligned

with the draw points such that each draw pointhas an in-situ (un-mixed) resource above it.

Compute best Height of Draw (HOD). Each

draw column is evaluated to assess the best or

highest dollar value which can be achieved for a

given set of mining costs and product revenue

and recovery factors.

Production scheduling. This is the heart of the

PCBC system. It is important to distinguish


2/17

2

between production (tons and grade produced)

and development scheduling (tunneling and

development). PCBC does production

scheduling. This provides the tons and grade

forecasts for the project which has been

described as the mine planners promise to the

shareholders as to what the mine can produce.

Advanced schedules. No schedule is ever

complete or final. During the project evaluation

stage, new pricing or geometrical options will be

considered and new geological models generated

as the exploration drilling progresses. During

production, new schedules are generated

whenever the actual production varies from the

plan (which is always). So the need for a

scheduler which can run in typically less than 20

to 30 minutes per run is important.

Operating mine set up. Once a mine is going

into production, then it is possible to set up a

database to store production tons and draw point

assay and other observational data. The

importance of accurately recording and

managing the tonnages extracted from each draw

point has long been recognized.

CMS can be used to help manage the daily (or

shift based) draw order. This is the daily

tonnage target set for each draw point. This is

essential if a managed block cave is to be

maintained.

Geological/geotechnical monitoring. Tools have

been developed within PCBC to help store,

display and analyze observed data

Least Squares (LSQ) and grade reconciliation

can be used to base schedules on observed assaydata instead of block model data for more

accurate schedules

During the above process, it is essential to have

appropriate tools to interrogate and query the

results generated. Over the years, a substantial

toolbox has evolved based on project and user

requirements.

In this paper

This paper describes the various components in

the PCBC product. It is not intended to provide any

explanation as to how these components work or are

used.

Components of PCBC

The various components of PCBC have evolved

to support the above project workflow. PCBC runs

inside the Gemcom GEMSTMmine planning package

developed by Gemcom Software International Inc.

(Figure 1) The ability of PCBC to work inside of this

framework has proven invaluable over the years and

has allowed our development efforts to focus on the

block cave part of the problem minimizing the need

to develop and maintain the underlying graphical and

database subsystems.

Figure 1 Typical view of PCBC running inside the GEMS

general mine planning package

Components of PCBC are described below

including initial assessment of footprint location,

model set up and mineable reserve assessment, then

scheduling and production management.

Foundation

This is the framework within which PCBC

operates. The various components are summarized

as follows:

Graphical interface

Blocks

Lines

Points

Triangulations

SQL database / workspaces

Profile editors / parameter management

Footprint Finder

Input for Footprint Finder utility comes from a

geological block model together with mining costs,

revenue factors, etc. The program will look at each

level in the block model and then construct vertical

columns accumulating the dollar value. Vertical

mixing is applied to each column using an algorithmbased on Laubschers mixing method (Laubscher,

1994).

This is very useful to obtain an initial idea of

where to locate a footprint and what the initial

footprint shape might be. Figure 2 shows

accumulated columns plotted according to value.


3/17

3

Figure 2 Footprint Finder example on one level

Repetition of this process on each level allows

the tons and value generated to be plotted as showninFigure 3.

-

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

9,000

-

100

200

300

400

500

600

700

800

900

1,000

2560

2620

2680

2740

2800

2860

2920

2980

3040

3100

3160

3220

3280

3340

3400

3460

3520

3580

3640

DollarValue(M$)

Tonnage(Mt)

Elevation

Tons Dollar value

Figure 3 Footprint Finder : Tons and dollar value vs

footprint elevation

An example from Freeports DOZ mine is shown in

Figure 4.

Figure 4 Footprint Finder example (DOZ mine)

The higher grade zones are shown in warmer

colors. This type of value plot assists considerably

with the process of defining a reasonable

economically and geotechnically feasible outline.

PCBC

Overall steps of a typical project (from the

program, not project perspective) are as follows:

Set up the initial working environment inside a

GEMS project.

Slice file construction (Figure 5). This is an

integral part of the process. Utilizing user-

defined draw cone shapes, a column of rock

above each draw point is simulated and stored in

what is termed a slice file. The term slice as the

total column is broken into slices which match

the vertical spacing of the geological block

model.

Figure 5 Schematic of block model to slice file conversion

Draw point locations are used to construct a

vertical column which is then intersected with theblock model. The various overlaps of the draw cones

are resolved so as to not double count material and

this is accumulated into the slice file for each draw

point. This is referred to as a NoMix slice file,

since no material mixing has yet been applied.

Figure 6 shows a section of a block model and

the resulting NoMix slice file with one column per

draw point.


4/17

4

Figure 6 Block model to slice file conversion

A variety of material mixing algorithms may

then be applied to the slice file to simulate the

actual material mixing which takes place as

material is extracted from the draw points.

Best HOD. The Best HOD utility will

accumulate tons, grade and dollar value in each

draw column (after application of vertical

mixing) to provide an estimate of mineable

reserves for different footprint shapes. As this

process uses actual draw point locations and

assumed draw column shapes, it is generally

considered more geometrically accurate than theFootprint Finder.

Figure 7 Best HOD based footprint (bottom) vs Footprintfinder result (top) (Cadia East)

Figure 7 shows that the results from Footprint

Finder and Best HOD tools are typically quite similar

as one would hope.

Once the basic preparation work has been done,

production schedules can be generated.

A typical schedule requires input of the

following key components (Figure 8):

Sequence to develop the draw points (and

undercut)

Constraints on the maximum draw rate which

can be applied to draw points

Tonnages required in each scheduling period

Information to control the cave shape. It is usual

to look at different strategies and compare

Numerous other inputs, constraints and reporting

control options

Figure 8 Production scheduling components in PCBC

A basic schedule will open draw points

according to the sequence and deplete tons from eachaccording the Production Rate Curve (PRC), apply

material mixing if required and report tons and grade

mined in a variety of formats.

An advanced schedule could look at changing

parameters for individual or groups of draw points,

adjusting the schedule to past tons mined, having the

HOD profile follow a given cave shape and adding

information to report undercut tons separately from

production tons.

Experience has shown that it is very useful to

have a clean and efficient interface between PCBC

and Microsoft Excel. This allows reports to begenerated in a format which can quickly be further

analyzed by engineers.

In addition, when dozens or hundreds of

schedules are being run, it is useful to have what is

called a playback tool. This allows various aspects

of the schedule to be studied visually to look for

trends (or data input errors!)


5/17

5

The production scheduler can just as easily be

used for forward looking schedules or for analysis of

past performance. This is very useful for grade

calibration and reconciliation purposes.

Cave Management System

CMS was originally developed for FreeportDOZ mine and then further refined for use at Finsch

mine. Currently there are seven mines using or

planning to use CMS. CMS aims to generate a draw

order for each draw point every day or shift. It uses

the recent historical (actual) tonnages to adjust and

manage the draw and provides the supporting

database, reporting and user interface to facilitate this

process. At De Beers Finsch mine, CMS has been

closely integrated with the Sandvik Automine

system.

Figure 9 How CMS fits in between historical tons andfuture plans

Figure 9 shows how CMS fits in between thehistorical tons mined and the requirement to adjust

the plan of the next few months (using PCBC

schedules) in a process called Catch-up to fit in

with the long term plan. (Diering, 2004)

Figure 10 Categorization of draw points for priority

assignment

Each draw point can be categorized in a variety

of ways (Figure 10), including over-draw, under-

draw, normal, draw-bell development, wet muck

(which is a safely concern) or as requiring special

treatment. The tonnage for each category is set

accordingly.

Figure 11 Excel map format for draw point result display

Figure 11 shows an example of daily production

data displayed using Excel. It is important to have a

clean interface between the CMS database and Excel

for ease of analysis by the draw control personnel.

LSQ

The LSQ tool is intended for operating mines.

Once a mine has been in operation for a few years, it

will likely have a draw point sampling program. The

draw point assay values can be stored and sorted per

draw point and then composited into 10m or 15m

intervals to provide some averaging of the highly

variable assays.

Subject to a variety of constraints, a least

squares trend line is put through the composites and

then this can be extrapolated for a short distance upthe draw column into what is essentially the un-

mined part of the column (Figure 12).

This becomes particularly useful when the draw

point assays suggest that the draw point should

remain open (usually after 100% draw) when the

slice file values suggest that the draw point should be

closed. For draw points where the sample trend

differs from the slice file, then the slice file values are

replaced with the sampled values for selected draw

points. This is somewhat similar to the open pit

practice of taking blast-hole samples to improve the

local grade of a bench about to be blasted and mined.

Figure 12 shows a single draw column with

sampled values at various heights (HOD) above the

draw point. The graph shows these together with the

trend line and some extrapolated points. Maximum

and minimum grade values are set so that steep up or

downward trends do not generate unrealistic grade

values.


6/17

6

Figure 12 Sample compositing and trend line analysis in

LSQ

The LSQ tool can either be run as a stand-alone

tool or right within the PCBC production scheduler.

Operations tools and reconciliation

Once a mine is in operation, there is a variety of

useful ways in which draw point sampling data

(grade, geotechnical and geological) can be displayed

and analyzed. A key reason for doing this type of

work is so that we can better understand if or wherethere is irregular behavior with the cave itself. Some

of the analysis types are listed below:

Use of draw point assays for grade reconciliation

and for calibration of the model

Use of draw point assays for improved short

term forecasting using the LSQ tool already

mentioned.

Use of geological samples to supplement the

reconciliation process or to better understand

horizontal and vertical migration of material

within the cave (Figure 13)

Use of geotechnical (fragmentation) data tobetter understand the relationship between draw

rate at draw points and rock type or mining area.

Use of convergence data in production tunnels to

help prevent excessive closure (or collapse) of

these tunnels. Freeport has shown quite

convincingly at their DOZ mine that a diligent

program of monitoring convergence in these

tunnels is beneficial. In areas where high

convergence rates are observed, adjacent draw

points have an increased tonnage target which

tends to relieve the high stresses.

Seismic data and/or extensometers can be used to

help predict the location of the cave back which

can in turn be used to set up surfaces for

simulation of the rilling process which

migrates material non-vertically.

The residual slice file model can be used to re-

estimate a block model which can be used either

in a multi-lift mining situation or as part of a new

block model for a super-pit which some mines

are considering.

Figure 13 Example of graphical display of geological data

Figure 14 Example of residual slice file to block modelconversion

Figure 14 shows an example in which the

residual slice file (after simulation of mining the full

block cave tons) is used to re-estimate a geological

block model. This block model can then be used for

planning of another future mining block.

Recent Developments

PCBC is over 20 years old and hence should be

considered as a mature product. As such the basicplanning and scheduling work flow is well covered.

On the other hand, being mature and with a good

foundation, PCBC has provided a useful foundation

for a number of recent developments which are

summarized in this section.

Upgrades to material flow tools

Playback utility

Display tools

Each of these is considered in more detail

Material flow upgrades

Material flow is an integral part of the block

cave mining (and material depletion) process. The

entry of dilution is a significant factor in the planning

process and modeling of this has proven to be

difficult. As such, a variety of different mixing tools

have been developed within PCBC and users are then

given the choice as to which approach they would

like to adopt. This is summarized inTable 1.


7/17

7

Method Ease

of use

Linear? Comment

No mixing Easy Yes No mixing base

case (In-situ)

Pre-Vertical

mixing

Easy Yes PCBC Default

(includes pre-

erosion)

Laubscher

mixing

Easy Yes Uses Laubscher

tables

Sequential

mixing

Harder No Older method,

includes

toppling

Template

Mixing

Harder No Most flexible

option available

REBOP

interface

Harder No Not yet

generally

available

Table 1 Material mixing options in PCBC

The linear methods can be applied with the Best

HOD utility to find mineable reserves before the

schedule is run. For the non-linear methods, the

mineable reserve will be a function of the mining

sequence and draw strategy. Therefore, mixing hasto be built right into the production scheduler. This is

one of the key differentiators between PCBC and

other commercial scheduling tools.

The pre-mix option in PCBC was recently

upgraded to allow for the inclusion of a draw cone

erosion mechanism. This is useful as there is

increasing evidence that draw cone radii may not be

as large as is often hoped and also that the draw cone

radius changes with time. A fraction of each slice is

frozen and then an erosion rate is specified which

allows this material to be mixed with material higher

up each draw column.

Template Mixing was introduced in to PCBC in

2006. (Diering, 2007). It allows a variety of mixing

mechanisms to be simulated including vertical

mixing, rilling, toppling and fines migration. (Figure

15)

Figure 15 Movement mechanisms in a block cave

It differs from other material flow algorithms

such as discrete particle and cellular automaton

methods. A major advantage of Template Mixing is

its speed. Figure 16 shows a few steps in a depletion

simulation. Blue represents dilution, yellow is ore

and the intermediate colors represent progressive

mixing as the ore is extracted.

Figure 16 Template Mixing 2D example

Figure 17 shows an example for our sand-box

project using toppling, rilling and normal mixing.


8/17

8

Figure 17 Sandbox example with toppling, rilling andvertical mixing

In 2008, a joint initiative was done with Rio

Tinto, Itasca and Gemcom to provide the potential to

combine the PCBC and REBOP programs. This was

done using a hand-shake mechanism so as to

minimize the changes required to each program and

to keep them as independent as possible to facilitate

future development.

Figure 18 REBOP results displayed in PCBC (Markers leftand cones to right)

Figure 18 shows two examples of REBOP

results plotted within the PCBC program. The results

from REBOP are used directly in the production

scheduler and also for modification of the slice file.

As a separate, but related project, Gemcom

worked with Rio Tinto to calibrate PCBC and

REBOP against one another. Figure 19 shows the

geometry of the calibration problem. 50 fictitious

draw points were located in this block model for

testing purposes.

Figure 19 Block model used for PCBC/REBOP calibration

Results from the calibration exercise were reallyencouraging, suggesting ways to improve both the

PCBC and REBOP modeling processes. A sample

calibration curve of Cu grade is shown inFigure 20.

0.000.20

0.40

0.60

0.80

1.00

1.20

1.40

1.60

1.80

2.00

Jan-08

Jul-08

Jan-09

Jul-09

Jan-10

Jul-10

Jan-11

Jul-11

Jan-12

Jul-12

Jan-13

Jul-13

Jan-14

Jul-14

Cu%

Cu% Rebop vs PCBC (N2E5)

Cu%_M3P3

Cu% Tm4

Figure 20 Example calibration curve for PCBC (orange) vsREBOP (green)

The original version of PCBC used what we

term Laubscher mixing (Laubscher, 1994). This

was replaced by pre-vertical and sequential mixing

options in 1994 in PCBC. However, there are still

projects (or people) who like to be able to compare

back against the Laubscher mixing. So it was re-

introduced into PCBC in 2008. It is also useful forcomparison against Footprint Finder results which

use the same mixing.


9/17

9

Figure 21 Dilution entry. Pre-vertical mixing (top) vsLaubscher mixing (bottom)

Figure 21 shows an example comparing dilution

entry from a single draw column. PCBC pre-vertical

mixing has more of an S-curve dilution entry where

Laubscher mixing has a straight line dilution entry

Playback Utility

This tool is used to playback or study results

from a production schedule. Display options include

Triangular Irregular Networks (TINs), contours, pie

charting, and 3D columns. Playback examples are

shown in the later sections on Freeport DOZ and

Palabora.

Display tools

Over the years, a variety of different graphical

display tools have been developed. The more recent

ones are the Excel interface which allows any draw

point related data to be exported directly into Excel in

the correct cell row and column positions for direct

display in Excel as shown inFigure 22

Figure 22 Excel map transfer utility example

The Excel map format is useful for a single

attribute per draw point such as HOD. However, if

one has multiple attributes (which sum to 100%), a

very useful display option is the pie chart. Theprogram will plot a pie chart at each draw point

location using data directly from the underlying

database from what is called multi-bucket format.

(Figure 23)

Figure 23 Example of Pie chart display

In addition to the static displays available, a

more dynamic display of selected information for

individual draw points by right click or mouse

movement over draw points can be very useful

(Figure 24)


10/17

10

Figure 24 CMS control panel with right click anddisplay information

Other options are size based plots (Figure 13),

3D draw columns (Figure 14) and plotting of draw

points in appropriate shapes.

Project examples

Freeport DOZ

PT Freeport Indonesia has been using PCBC

since around 2000. They are currently mining close

to 80,000 t/d, making it a large block cave mine (T.

Casten, 2008). PCBC and CMS are used extensively

for planning and scheduling at the DOZ mine as wellas for daily draw control. Figure 25 shows a plot of

forecast rock types at one step during a production

schedule. Figure 26 shows a plot of HOD for the

same mining step.

Figure 25 Forecast rock types at Freeport DOZ minegenerated in Playback tool

Figure 26 Height of draw profile at Freeport DOZ minefrom Playback tool

Freeport Grasberg

The Grasberg block cave is scheduled to start

production as the Grasberg open pit slows down at

the end of its life. (Figure 27) (Brannon, Casten, &Johnson, 2004) This will be a very large block cave

with production up to 160,000t/d. Numerous

scheduling options have been evaluated using PCBC

and particular emphasis has been placed on effective

modeling of large open pit failures which will

generate additional dilution material.

Figure 27 Grasberg block cave in close proximity to the

large open pit

Figure 27 shows the proximity of the block cave

draw columns to the large open pit.


11/17

11

Figure 28 Column values from Footprint Finder used forfootprint assessment

Figure 28 gives an idea of the variability of the

orebody edges and also alludes to the difficulties in

sequencing and scheduling such a large orebody (grid

size above is 200m!).

Northparkes

PCBC was first used for Northparkes E26 Lift 1

around 1994 and then for Lift 2 planning and

currently for Lift 2 North (Figure 29) (Ross, 2008)

and E 48. Each lift has provided surprises andchallenges from a modeling perspective.

Figure 29Northparkes E26 mining

Salvador

The Salvador mine in Chile has used PCBC

both for the detailed scheduling of individual mining

panels (Figure 30) as well as for combined

scheduling of multiple mining blocks (Figure 31).

Figure 30 Slice file display and layout at Salvador Mine

Figure 31 Scheduling of multiple mining panels at

Salvador Mine

As this is an older mine, current work is looking

to re-estimate the residual grades in older mined out

areas for use with future planning.


12/17

12

Andina

Figure 32 View of three panels (lifts) at Andina mine

Figure 33 Plan of Andina third panel showing grizzly andLHD sectors and existing development

PCBC has been used extensively at Codelcos

Andina mine for a number of years. Challenges in

modeling this deposit include the multi-lift aspect

together with reliable estimation of residual grades of

mined out blocks (Figure 32), the effective

scheduling of grizzly and LHD sectors (Figure 33),

the sheer size of the project and caving issues related

to primary and secondary rock types.

Palabora

The Rio Tinto Palabora mine in South Africa

started block cave production in 2000. (Moss,

Russell, & Jones, 2004)

As the scheduler can work with historical

tonnages as easily as forward looking tonnages, the

playback tool can thus also be used for historical

analysis or reconciliation purposes.

Figure 34 Monthly tonnage display (poor draw control(top) and good draw control (bottom)

Palabora went through a period during which it

was difficult to achieve good draw control.

However, more recently, the draw control has been

much improved. (Pretorius & Ngidi, 2008) This isshown clearly inFigure 34.

Figure 35 Seismic data display example from Palabora

Figure 35, also from Palabora shows a plot of

seismic events for one month together with draw

points and the cave Height of Draw profile (which is

different from cave back profile).

Ridgeway

The Ridgeway Deeps Mine of Newcrest used

PCBC with the Template Mixing option to studyrilling and how this impacted the mineable reserve

and overall production schedule (Burgio & Diering,

2008) (Figure 36)


13/17

13

Figure 36 Section of Ridgeway deeps block cave modelshowing irregular cave propagation on right side

Different scenarios were modeled to see the

effect of limited cave propagation on the East side of

the cave.

Cadia East

The Cadia East project of Newcrest provided

interesting modeling challenges as it is a large multi-

lift project. (Figure 37)Extensive use has been made

of the Footprint Finder tool to assist with

determination of elevations together with more

accurate schedules from PCBC.

Figure 37 Multi-lift example from Cadia East, Newcrest

Finsch

The Finsch Block 4 block cave is an example of

mining beneath an old open pit (Richter & Diering,

2004) (Figure 38). As mining progresses, additional

pit wall material is failing into the developing cave.

The remaining ore and ore/waste combination has to

be continually updated as additional material fails

into the cave.

Figure 38 Schematic of open pit, cave zone and Block 4draw points at De Beers Finsch mine

Figure 39 shows a section with some of the

residual draw columns. These are trimmed against

the known topography and the new failure material

(red) then starts to mix with the existing material

(blue). The mixing zone is shown by theintermediate colors.

Figure 39 Addition of new failure material and mixing of

this material with existing cave rock mass

Figure 40 is similar toFigure 39 except that the

sequential mixing in PCBC is turned off. This

example shows the importance of being able to

model this process in a non-linear manner. The final

mineable reserve is required to be adjusted monthly

or every time the failure surface is modified.

Additional tools in PCBC allow for the addition of

anticipated material for the remainder of the life of

the Block 4 block cave as well.


14/17

14

Figure 40 Addition of new failure material withoutadditional mixing

Calibration examples

Freeport DOZ

A detailed description of the calibration curves

in figures Figure 41 and Figure 42 is beyond the

scope of this paper. (Villa, Prasetyo, & Diering,

2008) Figure 41 is for grade and it shows the extent

to which the PCBC model can be changed to improve

the fit actual against actual observations.

Figure 41 Freeport DOZ. Calibration of grade

Figure 42 is for the Marble rock type. It shows

how the original PCBC marble curve (bottom) can be

changed to more closely approximate the geological

draw point observations (higher curves).

Figure 42 Freeport DOZ. Calibration of Marble rock type

Geological observations are made routinely at

draw points of up to 8 different rock types. These

were also fed into the geological block model so that

comparisons could be made of the observed vs model

rock types. Figure 43 shows the modeled rock types

vs time and Figure 44 the observed rock types vs

time. A detailed study of the differences between the

two can be very informative and lead to ways to

improve the model which may not be apparent from

the grade model / assays. The geological modeling

thus provides another dimension into the

calibration process.

Figure 43 Geological composition from block model andPCBC production schedule

Figure 44 Geological composition based on draw point

observations

Palabora

Work has been done at Palabora to improve the

short term grade estimates using the LSQ tool

described above. Figure 45 shows the improvement

in the short term comparing the PCBC LSQ forecast

vs Samples.


15/17

15

Figure 45 Measured vs PCBC standard and LSQ adjusted

grades

Figure 46 shows a similar set of graphs, but

comparing hang up frequency. In this case, there was

no initial model forecast for hang-ups, but based on

the LSQ approach, a reasonable forecast for short

term hang up frequency was achieved.

Figure 46 Measured vs LSQ modeled Hang-ups

Salvador

Various calibration runs were done at Salvador

mine. Two examples are shown in Figure 47 and

Figure 48. A detailed explanation of the curves is

beyond the scope of this paper, but the graphs show

how mixing parameters were adjusted to improve

both the model results and the confidence in other

forecast results.

Figure 47 Various PCBC runs vs assayed results for IWsector, Salvador mine for 8 years

Figure 48 Various PCBC runs vs assayed results for ICE

sector, Salvador mine for 17 months

Example of block model adjustment

In this example (Figure 49Figure 35), variousattempts were made to calibrate the PCBC results

with the observed mill feed grades. However, the

PCBC grades were too high irrespective of the

mixing parameters used. This is an example in which

the underlying block model is at fault. Re-

estimation of the block model with different

interpolation parameters has largely resolved this

discrepancy.

Figure 49 Calibration example in which the block modelrequired re-estimation

Example involving old mining areas

This example considered two separate runs. In

the first (Figure 50), the block model was notadjusted correctly for historic mining. Once this had

been recognized and appropriate changes made to the

area in which mining had taken place, a much better

fit between PCBC model grades and observed mill

grades was obtained. (Figure 51)


16/17

16

Figure 50 Grade curves measured vs PCBC beforeadjustment for mined out area

Figure 51 Grade curves measured vs PCBC after

adjustment for mined out area

Concluding remarks

PCBC has been applied to a variety of different

block cave projects and mines over the last 20 years.

Every project has its own unique challenges some of

which have been described in this paper. As the

program has evolved to meet these new problems, its

capability has been enhanced.A key component of the modeling and program

development process has been the ongoing

calibration of PCBC against observations / sampling.

This process has clearly indicated that it is not always

the material mixing which required the most

adjustment. Careful attention is also required in areas

of past mining, or for open pit failure material or

even to the geological block model itself.

The calibration examples also clearly show the

benefits to be gained from doing a calibration

exercise using both grades and rock types. In each

case, a clearer understanding caving mechanisms is

gained from the work. This type of calibration also

strongly justifies the effort of taking draw point

samples for grade and rock types.

The development process for PCBC has been

significantly enhanced by collaborative projects with

key clients and this assistance is gratefully

acknowledged.

Acknowledgements

The authors would like to thank the following

mining companies for permissions to publish

information and figures pertaining to their projects in

this paper: Freeport-McMoRan Copper & Gold Inc.,

Rio Tinto, Newcrest Mining Limited, De Beers

Consolidated Mines Finsch mine, Codelco DivisinSalvador, Codelco Divisin Andina and Palabora

Mining Company.

The authors also gratefully acknowledge

assistance with the development of the software from

Freeport-McMoRan Copper & Gold Inc., PT

Freeport Indonesia, Rio Tinto, De Beers

Consolidated Mines Finsch mine, Codelco Divisin

Andina and Palabora Mining Company.

References

1. Brannon, C., Casten, T., & Johnson, M. (2004).

Design of the Grasberg block cave mine.

MassMin, (pp. 623 - 628). Santiago.

2. Burgio, N., & Diering, T. (2008). Simulating

irregular cave propagation using PCBC.

MassMin, (pp. 1033 - 1042). Lulea.

3. Diering, T. (2004). Combining long term

scheduling and daily draw control for block cave

mines.MassMin, (pp. 486 - 490). Santiago.

4. Diering, T. (2000). PC-BC: A block cave design

and draw control system. MassMin, (pp. 469-

484). Brisbane.

5.

Diering, T. (2007). Template Mixing: A

Depletion Engine for Block Cave Scheduling.

APCOM, (pp. 313 - 320). Santiago.

6. Laubscher, D. (1994). Cave Mining: State of the

Art. SAIMM, October, 279 - 293.

7.

Moss, A., Russell, F., & Jones, C. (2004).

Caving and Fragmentation at Palabora:


17/17

17

Prediction to Production. MassMin, (pp. 585 -

590). Santiago.

8. Pretorius, D., & Ngidi, S. (2008). Cave

management ensuring optimal life of mine at

Palabora.MassMin, (pp. 63 - 72). Lulea.

9. Richter, O., & Diering, T. (2004). Production

Scheduling at Finsch Diamond Mine. MassMin,

(pp. 453 - 458). Santiago.

10. Ross, I. (2008). Northparkes E26 Lift 2 block

cave A case study. MassMin, (pp. 25 - 34).

Lulea.

11. T. Casten, L. R. (2008). P.T. Freeport Indonesia's

Deep Ore Zone mine - expanding to 80,000

tonnes per day.MassMin.Lulea.

12. Villa, D., Prasetyo, R., & Diering, T. (2008).

Calibration of mixing model to predict grade at

Freeports DOZ Mine. Massmin, (pp. 1053 -

1062). Lulea.

Documents

PCBC Block Cave Scheduling