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Conference Proceedings © 2012 – ISBN: 978-979-15458-4-6

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The 3rd International Conference on Technology and Operations Management“Sustaining Competitiveness through Green Technology Management”

Bandung – Indonesia, July 4-6, 2012

Cut-off Grade Optimization at Grasberg Surface Mine inConsidering Environmental Impact

Lukman Budi Prasetya1, Togar M. Simatupang2,*

1PT Freeport Indonesia: an affiliate of Freeport McMoran Copper and Gold,

Plaza 89 (5th floors), Jl. HR. Rasuna Said Kav. X-7 no.6, Jakarta 12940, Indonesia2School of Business and Management (SBM) - Institut Teknologi Bandung (ITB),

Jl. Ganesha 10 (Gedung SBM-ITB), Bandung 40132, Indonesia

Abstract. A developed model for optimum cut-off grades is presented that not only relies on economics aspect but alsominimizes adverse environmental impact in the form of acid mine drainage elimination or mitigation against the approach ofpostponing the restoration/reclamation activities at the end of the project’s life. There are three model alternatives developedin this paper: the first model considers the environmental cost during the mining operation, the second model ignores andpostpones the environmental cost to the end of the mine life, and meanwhile, the last model considers fixed breakeven cut-offgrade during the mining operation. The criteria to choose the best alternative are based on environmental acceptance(indicator for minimizing environmental impact) and financial analysis result. Using these criteria and SMART analysis,Model 2 is chosen as best alternative in cut-off grade optimization at Grasberg surface mine to minimize environmentalimpact.

Keywords: Cut-off grade, Optimization, Environmental impact, Mine planning

1. Introduction

There are many sources to increase value in mining operations. The optimal cut-off grade strategy andtactics is one of these sources. The elements of mining operations from resources, infrastructure, mining site,processing, and marketing are mutually dependent, and reinforce and interact positively with each other togenerate combined value greater than the sum of their individual contributions.

It is believed that the public expect the mining industry show care of the environment and try to eliminatethe adverse environmental impacts or at least minimize the intensity as well as the length of them. Sustainabledevelopment requirements finally lead to using improved and environmentally-friendly technologies. Usingsustainable development principles must be started at the beginning of the project.

To produce sustainable results of mining operations, holistic design criteria must be integrated in the designprocess. The best practice is consideration of environmental mine-waste management requirements with special

* Corresponding author.E-mail address: [email protected]

90 L.B. Prasetya and T.M. Simatupang – Cut-off Grade Optimization at Grasberg ...

The 3rd International Conference on Technology and Operations Management (ICTOM)Conference Proceedings © 2012 – ISBN: 978-979-15458-4-6

reference to eliminate or minimize the waste and pollution in the first place at the source. Open pit mining, frothflotation and smelting are the most commonly practice in metal production. This process associated with landdisturbance and causes pollution on the mine site and groundwater contamination in the vicinity by the wastematerials and tailings.

Vietor (2002) reports that the Grasberg mining operation is so large that an immense amount of rock fromabove the ore – some 2.8 billion tons of overburden – has to be dug and safely stored. When the mine wasexpanded, a plan was developed to store 2.4 billion tons over 30 years, with a stated margin of safety, barringearthquakes or sliding due to weak compressible soils. Four valley locations were planned for storage –Carstenszweide, North Grasberg, West Grasberg, and Wanagon.

According to this plan, overburden would be deposited in layers 100 meters thick, separated by berms 100meters wide. Although such storage changed local topography and destroyed vegetation, it maximized stabilityand provided adequate drainage. Overburden storage is the biggest environmental problem – in short term. Thedifficulty is acid drainage from sulfides in the overburden. PTFI has taken plenty of samples of overburden todetermine its likelihood for acidification. Some of samples do indeed show acid rock drainage. Wanagon Lake,next to one of the storage sites, registered a pH as low as 4 – acidity strong enough to kill any plants were it to bereleased from the lake.

To deal with this, PTFI has to develop short-term, medium-term, and long-term plans. Freeport is currentlyputting lime into the east stream of West Grasberg to neutralize the low pH coming out of the overburden. Thatshould raise the pH of Lake Wanagon to 7.0 and keep it there, to prevent any acid mine drainage. Next, Freeportis also driving a tunnel (3.5 kilometers) under Lake Wanagon and would bore up under the east stream to collectthe runoff water. It would be brought to the mill for treatment to recover dissolved copper and used as feedstockfor mill production. In the long term, limestone would become available in huge quantities as part of theoverburden to neutralize any acidity.

Nevertheless, optimum cut-off grade should be determined for each period to reduce the amount of wastematerials stored as overburden.

Deposition of tailings, the waste ore after extraction, is a serious and certainly the most visibleenvironmental problem facing Freeport (Tailing Management Plan 2007). About 223,000 tons of finely groundrock is discharged from the extraction mill every day. These tailings, together with the effluent water from theextraction mill, flows into the Aghawagon and the Otomona Rivers, which merged with the Ajkwa River furtherdown the mountain. From there, the river carries tailings to the lowlands, and the lost speed as the topographyflattened out. In the freshwater swamp area below Timika, the Ajkwa overflows its low banks in a sheetflow anddeposits the tailings as it meandered back and forth, shifting its flow as the tailings filled in vast stretches ofriverbed.

The very process of mining inevitably creates a tailings problem; there is simply no way to avoid it. Theenvironmental problem has two components: water quality and the effects of tailing deposits on flora and fauna.

The physical extraction process used by Freeport does not change the rock chemically. The solvents areadded to help flotation evaporated before the river flowed very far, and are undetectable in the lowlands (Vietor2002). Although the river carries an immense amount of tailings, they are chemically similar to naturalsedimentation, albeit ground somewhat finer. And as a fast-flowing mountain river, the Ajkwa carries a hugevolume of natural sedimentation, even in the absence of mining.

To deal with water quality, PTFI should undertake a long-term environmental monitoring program tomeasure the mine’s effects on water. The metals contained in the tailings are tightly bound in the rock matrix andare not readily bio available. Dissolved arsenic, lead, mercury and other potentially dangerous metals showedconcentrations near detection limits with modern equipment. The effect of tailings deposition on freshwaterswamp forest is a serious problem. Considering the immense impact of tailings as waste ore after extraction,optimum cut-off grade should be determined for each period to reduce the amount of waste materials sent to theriver as tailings (James 1999).

Cut-off grade is one of the most important parameters in mining because of its impact on the overalleconomic value of a mining operation. In practice, achieving the optimum balance is a real challenge. Cut-offgrade optimization is now an accepted principle for open pit planning studies. The objective of cut-off gradeoptimization of mining operation is to maximize the net present value (NPV) of the whole mining project overthe lifespan of the mine. The problem discussed in this paper is to find an optimum balance between the cut-offgrade and environmental management consideration. By using environmental management consideration, it isexpected the cut-off grade optimization not only focusing on maximizing metal production and NPV of the mine,but also reducing environmental impact through optimizing waste production (overburden and tailing materials).

L.B. Prasetya and T.M. Simatupang – Cut-off Grade Optimization at Grasberg ... 91


2. Company Profile

Grasberg is a world-class mining complex in Papua, Indonesia, where Freeport-McMoRan Copper & Gold(FCX) is engaged in exploration and development, mining and milling of ore containing copper, gold and silver.PT Freeport Indonesia (PTFI) commenced mining operations at this site in 1972 and in 1988 discovered theGrasberg mine. Today, after significant production, the Grasberg mining district contains the world’s largestrecoverable copper reserve and the largest gold reserve. FCX own 90.64% of PT Freeport Indonesia, theprincipal operating subsidiary in Indonesia, including 9.36% owned through its wholly owned subsidiary, PTIndocopper Investama. The Government of Indonesia owns the remaining 9.36% of PT Freeport Indonesia. FCXoperates under an agreement with the Government of Indonesia, which allows the company to conductexploration, mining and production activities.

The PTFI Contract of Work (COW) area is located in Papua on the western half of the island of New Guinea,bordered on the south by the Torres Strait and Arafura Sea, which are relatively shallow and transient marineenvironments (Tour Companion 2009). The site is located near Puncak Jaya, or Mount Carstensz, of theSudirman Mountain Range. According to the COW signed between the Government of Indonesia (GOI) andPTFI in 1991, PTFI was granted two working areas defined as:

Contract of Work (COW) Mining Area (COW Area A), covering an area of 100 km2. Activitiesconducted in this area include open-cut and underground mining, ore processing at the mill, andoverburden placement in stockpiles.

Contract of Work (COW) Project Area, a north-south corridor connecting the mining area to theArafura Sea and covering an area of approximately 2,890 km2. The supporting facilities andinfrastructure, including Tembagapura, Ridge Camp, Kuala Kencana, Amamapare Portsite, Timikaairport and others, are situated in this COW Project Area.

The COW Mining and Project Areas of PTFI include all major supporting facilities and infrastructurerequired for operations as well as extensive tropical forest systems that extend from the Arafura Sea up to thehighland area. In addition, some settlement areas are located within the COW Project Area as seen in Figure 1.

Figure 1. PT Freeport Indonesia’s Geography

Portions of the eastern side of the COW Project Area and the eastern and northern sides of the COW MiningArea border the Lorentz National Park (Tour Companion 2009). The boundary between the Park and the COWAreas was previously not clearly defined and appeared to overlap. However, in 1993 and again in 2004, the



COW boundary was redefined to ensure that no conflict occurred on the border between the COW Areas and theLorentz National Park. As a result, the PTFI mining and project activities do not overlap the park area.

When the original COW with the GOI was signed on April 7, 1967, Freeport became the first company toreach a Foreign Capital Investment agreement under a new Indonesian law. Freeport was given full managementcontrol over its operations and undertook to provide all the necessary financing for the project, includinginfrastructure development. The GOI had no obligations and provided no guarantees.

Freeport established a subsidiary, Freeport Indonesia, Incorporated (now PTFI), to undertake developmentof the mine, mill and all appurtenant facilities for an ore deposit known as Ertsberg (Tour Companion 2009).Exploration drilling at Ertsberg began in December 1967. This program was carried out with helicopter logisticsupport. The engineering feasibility investigations were completed in December 1969.

In January 1970, construction began on the necessary engineering works extending 119 km from the coast tothe mine site. A seaport, barge port, road, airstrip, town, mining and processing facilities, slurry pipeline andconcentrate drying facilities were all built in less than three years, where previously there had been no suchfacilities. The first shipment of copper concentrates was made in December 1972.

Initial mining activities exploited the Ertsberg ore body, which has since been depleted. In addition, theGBT (Gunung Bijih Timur) and IOZ (Intermediate Ore Zone) ore bodies have also been mined and are depleted.Currently, mining activities are taking place in the Grasberg, and DOZ (Deep Ore Zone) orebodies. Additionalproven reserves remain to be mined, including DOM open pit and underground, the Big Gossan, Grasberg BlockCave and Kucing Liar as shown in Figure 2.

Figure 2. Grasberg Complex – Future Mines

Initial production from the Ertsberg mine was approximately 7,500 tons of ore/day. Current open-pit andunderground production is approximately 250,000 tons/day. However, production expansion programs continueto be investigated to possibly incrementally increase production up to the permitted 300,000 tons/day. TheGrasberg surface mine life will be until 2017. Meanwhile the Underground mine life will be until 2042 asillustrated in Figure 3.



Figure 3. Projection Mine Scheduling

3. Methodology

By conducting brainstorming with Mine Planning engineers, conceptual framework used in this paper can beshown on Figure 4. Using this information, a framework can be created for structured analysis limitation to findthe root cause of the problem and alternative solutions to overcome the problem.

Figure 4. Conceptual Framework



3.1. Analysis of Business SolutionThe gold, copper, and silver metal price has increased significantly since 2008 to early of 2011. According

to data from London Metal Exchange shown on figures below, the gold, copper, and silver price in January 2011has increased by 52%, 35%, and 78% respectively compared to price in January 2008.

Figure 5. Historical Gold Price

Data source: http://www.kitco.com

Figure 6. Historical Copper Price


Figure 7. Historical Silver Price




The increased trend of metals price as shown on Figures 5-7 above has boosted PT Freeport Indonesia toincrease its mining productivity, especially in Grasberg surface mine to get significant profit along with metalsprice increase.

3.2. Root Cause AnalysisPTFI has planned to increase its copper and gold concentrate production along with the increase trend of

copper and gold prices in world metal market. The fluctuation of metal price in the world market will drive PTFIto set its cut-off grade following the movement of metal price. If metal price increases, the value of mineralreserve at Grasberg mine will also increase. PTFI will decrease the cut-off grade thus giving the company largermineable reserve. When the cut-off grade is dropped off, the mill will require more ore to produce the sameamount of metal on a daily basis. Using the same stripping ratio, more ore to produce will result in the increasedamount of waste materials to be stored as overburden materials and increased amount of tailings as the result ofproduced ore in processing mill.

Referring to the explanation about Overburden Storage and Tailings Deposition on Chapter I, cut-off gradeoptimization should consider the environmental impact by optimizing the number of waste materials in the formof overburden and tailings materials.

Most mining companies, including PTFI, use common cut-off grade optimization that only considers theeconomic aspect. Variables that are involved on common cut-off grade optimization are:

a. Mining throughput/mining capacityb. Milling throughput/milling capacityc. Recovery rate (%)

There will be one additional variable that becomes important factor in this paper and need to be optimized asthe result of environmental consideration. It is waste production in Table 1.

Table 1. Correlations of Cut-Off Grade and Its Variables

Variable Increased cut-off grade Decreased cut-off grade

Mining throughput Increased Decreased

Milling throughput Increased Decreased

Recovery rate Decreased Increased

Waste production Decreased Increased

Definition of each variable can be explained as follow:

a. Mining throughput or mining rate is the total ore excavated from pit and dumped to ore crushers,typically expressed as tons per hour (tph), tons per day (tpd), or million tons per year (Mtpa).

b. Milling throughput or milling rate is the quantity of ore processed (comminuted) by a mill per unit time,typically expressed as tons per hour (tph), tons per day (tpd), or million tons per year (Mtpa). Millingthroughput is dictated by the ore hardness and the power available in the milling circuit to reduce theparticle size to economically liberate the valuable mineral from the gangue material.

c. Recovery rate is typically denoted percent recovery. So for the amount of mineral/valuable metal thatenters a processing circuit, there is a certain amount that is recovered to product and there is a certainamount which is lost to tailings. The recovery is normally associated with product and is a ratio ofamount of mineral in product over the amount of mineral in feed, for a given time (hourly, daily,weekly, monthly or yearly recovery).

Recovery = [tons product per unit time produced x %metal in product][tons feed processed per unit time x % metal in the feed]

d. Waste production is the total waste excavated from pit and dumped to waste dump areas, typicallyexpressed as tons per hour (tph), tons per day (tpd), or million tons per year (Mtpa).

The correlations of cut-off grade and its variables above is depicted in general and not absolute since thereare another uncertain factors that gives contribution to the movement of this correlation such as miningequipments availability, manpower availability, plant/mill availability, etc, which are not discussed in this paper.

According to the latest mine plan (version 11Q1-R2) of Grasberg mine, the actual 2010 data for Grasbergcut-off grade, mining throughput, milling throughput, recovery rate, and waste production can be seen on Table2 below.



Table 2. Actual Grasberg Mine and Mill Production in 2010

PeriodGrasberg Cut-off

Grade (CuEq) %

Mining Throughput

(million tons)

Milling Throughput

(thousand tons)

Recovery Rate

(%)

Waste Production

(million tons)

Jan-2010 0.30 4.88 207 89.6 15.93

Feb-2010 0.62 4.37 213 88.6 14.28

Mar-2010 0.64 4.75 190 86.2 16.61

Apr-2010 0.56 3.90 201 87.5 15.87

May-2010 0.53 5.36 218 89.3 17.50

Jun-2010 0.45 3.79 202 90.6 18.45

Jul-2010 0.30 4.20 241 89.8 19.01

Aug-2010 0.30 3.78 224 88.8 19.21

Sep-2010 0.29 3.37 213 88.8 17.35

Oct-2010 0.30 3.60 216 86.9 18.67

Nov-2010 0.28 4.16 231 89.4 16.83

Dec-2010 0.26 3.50 218 90.2 16.43

There is an opportunity to optimize the number of waste production (waste mined) without jeopardizing theeconomic value of the existing Grasberg mine since the cut-off grade that has been used so far has notconsidered waste production as important variable to minimize environmental impact.

Figure 8 below shows that the cut-off grade will increase starting in the end of 2011 since ore with highergrade will be mined at that time that drives the higher cut-off grade setting to maximize the NPV of theremaining reserve.

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Figure 8. Grasberg Cut-off Grade (2010 Actual and 2011-2012 Forecast)

(Metal Production Plan 2011)

However, the throughput of Grasberg mine will start decreasing from the beginning of 2012 along with thedepletion of Grasberg mine’s reserve.



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Figure 9. Grasberg Mining Throughput (2010 Actual and 2011-2012 Forecast)


In the end of 2012, the milling rate or milling throughput is planned to increase since the materialcharacteristic processed from Grasberg mine will come from soft zone area. The characteristic of the ore willaffect the tonnage number that mill can process on given time. Figure 10 below depicts that the recovery ratewill decrease starting from 2011 as the result of material type and characteristic of type D-ore that will be minedand milled at that time.

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Figure 10. Recovery Rate (2010 Actual and 2011-2012 Forecast)


Along with the decreased of mining throughput, the waste production will also start decreasing starting earlyof 2011as shown in Figure 11. This happens due to the decrease in stripping ratio (the ratio of the amount ofwaste removed to recover ore). The stripping ratio in 2010 is 4.15. Meanwhile, the stripping ratio in 2011 and2012 are 3.75 and 3.27.



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Figure 11. Grasberg Waste Production (2010 Actual and 2011-2012 Forecast)


By using waste production as additional variable in cut-off grade optimization, it is expected that the chosencut-off grade will produce waste:

a. in minimum result (by limiting economic cut-off grade), orb. in optimum result (by balancing cut-off grade)

4. Data Collection and Analysis

4.1. Modeling the effect of modern optimal cut-off grades in profitability of the Grasberg mineAccording to Cut-off Grade Optimization theory, operating costs per unit of operation is recognized to be

the most important sustainable mining practice indicator. In addition, mining operating cost and millingoperating cost will have important roles in determining optimum cut-off grade of mining operation. In this paper,waste disposal operating cost, considered as environmental cost, will also have important role since there is oneadditional variable (waste production). Thus, the background in developing models can be broken down asfollow:

Variable cut-off grade, with waste disposal operating cost considered every year Variable cut-off grade, with waste disposal operating cost considered in the end of the mine life Fixed cut-off grade

Given this consideration, three alternatives/models are developed in this paper to show the effect of themodern optimal cut-off grades in profitability of the Grasberg mine. In the first model, environmental cost isconsidered during the mining operation. In the second model, the environmental cost ignored and postponed tothe end of the mine life. Meanwhile, in the last model, fixed breakeven cut-off grade considered during themining operation. When doing calculation for each model, all variables are included, namely mining throughput,milling throughput, recovery rate, and waste production.

4.1.1. Consider the Environmental Cost during the Mining Operation (Model 1)This alternative will consider the waste disposal operating cost per unit ($/ton of waste) as environmental

cost that occurs during the mining operation until the end of mine life. According to the conceptual frameworkdefined on section 3, the appropriate solution identification for this model will be by balancing cut-off gradesince the cut-off grade on Model 1 will not be limited and be varied. The input data for this model is presentedon Table 3.

Given this alternative, it is expected that environmental impact in form of waste disposal included ondetermining optimum cut-off grade so the NPV of the mining project will also include waste disposal operatingcost per annual. This model will reflect the actual life time of the mine, it is until 2017.



Table 3. Input Data for Model 1

PeriodMining Throughput

(million tons)Milling Throughput

(thousand tons)

RecoveryRate(%)

WasteProduction

(million tons)

Waste disposaloperating cost per

unit ($/ton of waste)

2011 49.68 2,088 83.8 186.20 1.34

2012 48.15 2,177 84.3 157.66 1.47

2013 54.41 2,221 85.9 93.98 1.62

2014 49.73 2,538 87.5 59.82 1.78

2015 55.09 3,343 92.1 3.25 1.96

2016 11.38 2,235 88.3 0.23 2.16

2017 29.42 1,607 86.1 0.23 2.37

4.1.2. Ignore and Postpone the Environmental Cost to the End of the Mine Life (Model 2)On second alternative, the waste disposal cost as environmental cost will be ignored during the calculation

and will be postponed to year 2018 (one year after the end of the mine life). According to the conceptualframework defined on section 3, the appropriate solution identification for this model will be by balancing cut-off grade since the cut-off grade on this model will not be limited and be varied. The input data for this model ispresented on Table 4.

Using this model, there will be rehabilitation/reclamation cost in 2018 on the calculation as the result of theannual waste disposal operating cost that is postponed after the end of the mine life.


PeriodMining Throughput

(million tons)

Milling Throughput

(thousand tons)

Recovery

Rate

(%)

Waste

Production

(million tons)

Waste disposal

operating cost per


2011 49.68 2,088 83.8 186.20 -

2012 48.15 2,177 84.3 157.66 -

2013 54.41 2,221 85.9 93.98 -

2014 49.73 2,538 87.5 59.82 -

2015 55.09 3,343 92.1 3.25 -

2016 11.38 2,235 88.3 0.23 -

2017 29.42 1,607 86.1 0.23 -

4.1.3. Consider Fixed Breakeven Cut-Off Grade during the Mining Operation (Model 3)Model 3 will use fixed breakeven cut-off grade during the mining operation. This alternative will also ignore

and postpone the environmental cost after the end of the mine life, same as Model 2. Based on conceptualframework defined on section 3, the appropriate solution identification for this model will be by limitingeconomic cut-off grade since the cut-off grade on this model will be fixed and be limited on defined number.The input data for this model is presented on Table 5.

Using this alternative, it is expected that the profitability of the project can be maintained on certain leveland the waste production can be produced on optimum result. This model will ignore the lost opportunity thatcan be received if the metal price is getting higher since the cut-off grade is fixed.


Period

Grasberg Cut-

off Grade

(CuEq) %

Mining

Throughput

(million tons)

Milling

Throughput

(thousand tons)

Recovery

Rate

(%)

Waste

Production

(million tons)

Waste disposal

operating cost per


2011 0.41 49.68 2,088 83.8 186.20 -

2012 0.41 48.15 2,177 84.3 157.66 -

2013 0.41 54.41 2,221 85.9 93.98 -

2014 0.41 49.73 2,538 87.5 59.82 -

2015 0.41 55.09 3,343 92.1 3.25 -

2016 0.41 11.38 2,235 88.3 0.23 -

2017 0.41 29.42 1,607 86.1 0.23 -



4.2. Analysis of Business SolutionThe objective of the analysis is to find maximum NPV of mining operation and the optimum result of waste

production. The maximum NPV can be represented mathematically as following:

To find optimum cut-off grade for Model 1 and Model 2, the limiting economic cut-off grade approach isperformed. Balancing cut-off grade is undertaken for Model 3. The optimum cut-off grade by limiting economiccut-off grade can be determined by using given equation below (Rashidinejad 2008):

ciDi + eiFi

Gopt = ------------------------(Si – ri + aiBi) x y

where:ai = Waste disposal operating cost ($/ton of waste)Bi = Waste production (ton)ci = Mining operating cost ($/ton of ore)Di = Mining throughput (ton)ei = Milling operating cost ($/ton of ore)Fi = Milling throughput (ton)Si = Metal price ($/ton of product)ri = Cost to sell metal ($/ton of product)y = Recovery rate

Meanwhile, the optimum cut-off grade by balancing cut-off grade is middle value between:

Fi Fi

----- and -----Di Bi

The interaction between variables that depicts the correlation between cut-off and NPV can be seen on theFigure 12.

MiningThroughput

RecoveryRate

WasteProduction

MillingThroughput

Mining Cost Milling Cost Recovery CostWaste

Disposal Cost

Total Cost

NPV Cut-Off GradeMarketable

Product

Figure 12. Variables Interrelationship between Cut-Off and NPV



4.2.1. Consider the Environmental Cost during the Mining Operation (Model 1)Based on input data from Table 5 and limiting economic cut-off grade, the result of optimum cut-off grade

of Model 1 can be depicted from Table 6. During seven years mining operation until end of mine life in 2017,the total waste produced will be 501 million tons with 2,832 million kgs of marketable product. The NPV of theproject is positive US$ 4,589,689,946 at discount rate 10%. The cash flow already considers the annualoperating cost spent for environmental cost allocation.

Table 6. Optimum Cut-Off Grade for Model 1

Year Pushback Gopt g (g/t) OSRMining

Throughput

Milling

Throughput

Recovery

Rate

Waste

Production

Marketable

ProductCF

Cumulative

Discounted CF

2011 9 0.27 1.07 3.75 49.68 2.09 83.8 186.20 339 406,758,080 369,780,073

2012 9 0.56 1.15 3.27 48.15 2.18 84.3 157.66 359 532,653,611 809,989,669

2013 9 0.30 1.30 1.73 54.41 2.22 85.9 93.98 410 808,729,762 1,417,600,309

2014 9 0.78 1.72 1.20 49.73 2.54 87.5 59.82 519 1,231,234,905 2,258,550,315

2015 9 0.50 2.74 0.06 55.09 3.34 92.1 3.25 809 2,287,038,617 3,678,621,359

2016 9 0.15 1.26 0.02 11.38 2.24 88.3 0.23 280 873,905,431 4,171,918,192

2017 9 0.25 0.52 0.02 29.42 1.61 86.1 0.23 116 397,888,020 4,376,097,660

Total 297.86 16.21 501.37 2,832

Note: g = grade (gram/ton)

OSR = overall stripping ratio

Mining Throughput (million tons)

Milling Throughput (million tons)

Recovery Rate (%)

Waste Production (million tons)

Waste Disposal Opr Cost ($/ton)

Marketable Product (million kgs)

0% 10% 15%

NPV (US$) 6,538,208,426 4,589,689,946 3,921,306,862

This cut-off grade optimization model offers good profitability in term of good financial evaluation andoptimum waste production to minimize environmental impact.

4.2.2. Ignore and Postpone the Environmental Cost to the End of the Mine Life (Model 2)On Model 2 there is reclamation cost in 2018 after end of mine life that is estimated US$ 350,592,880 and

has a negative impact on the cumulative discounted cash flow. By using limiting economic cut-off grade, theresult of optimum cut-off grade of Model 2 can be seen from Table 7 below. The total waste produced will be501 million tons (same as Model 1) with 2,834 million kgs of marketable product (more products resulted thanModel 1). The NPV of the project is positive US$ 5,232,804,619 at discount rate 10%.


Year Pushback Gopt g (g/t) OSRMining

Throughput

Milling

Throughput

Recovery

Rate

Waste

Production

Marketable

ProductCF

Cumulative

Discounted CF

2011 9 0.27 1.07 3.75 49.68 2.09 83.8 186.20 339 656,266,080 596,605,528

2012 9 0.56 1.15 3.27 48.15 2.18 84.3 157.66 359 764,413,811 1,228,352,478

2013 9 0.30 1.30 1.73 54.41 2.22 85.9 93.98 410 960,977,362 1,950,348,994

2014 9 0.78 1.72 1.20 49.73 2.54 87.5 59.82 519 1,337,714,505 2,864,026,000

2015 9 0.50 2.74 0.06 55.09 3.34 92.1 3.25 809 2,293,408,617 4,288,052,313

2016 9 0.15 1.26 0.02 11.38 2.24 88.3 0.23 280 874,402,231 4,781,629,576

2017 9 0.25 0.52 0.02 29.42 1.66 86.1 0.23 118 404,658,638 4,989,283,441

2018 - - - - - - - - - (350,592,880) 4,825,729,276

Total 297.86 16.26 501.37 2,834





Recovery Rate (%)




0% 10% 15%

NPV (US$) 7,291,841,243 5,232,804,619 4,520,896,192



Model 2 offers better profitability and NPV (compared to Model 1) as decision criteria for financialinvestment and optimum waste production (same result with Model 1) to minimize environmental impact.

4.2.3. Consider Fixed Breakeven Cut-Off Grade during the Mining Operation (Model 3)Model 3 uses fixed breakeven cut-off until end of mine life. This fixed cut-off causes two years extension of

mining operation due to the “additional” reserve comes from the lower mining rate compared to the mining rateof Model 1 and Model 2. The optimum cut-off grade from this model is using balancing cut-off grade approach.This is because of the specific interrelationship between the grade-tonnage distributions in the pushbacks andmining throughput, milling throughput, and waste production.

There is reclamation cost as well as Model 2 in 2020. By using balancing cut-off grade, the result ofoptimum cut-off grade of Model 3 can be seen from Table 8. The total waste produced will be 436 million tons(the least amount compared to other models) with 2,688 million kgs of marketable product (the lowest amountamongst the other models). The NPV of the project is positive US$ 4,552,540,019 at discount rate 10%.


Year PushbackBreakeven

Cut-Offg (g/t) OSR

Mining

Throughput

Milling

Throughput

Recovery

Rate

Waste

Production

Marketable

ProductCF

Cumulative

Discounted CF

2011 9 0.41 0.59 1.13 32.29 1.36 84.6 121.03 295 570,951,490 519,046,809

2012 9 0.41 0.63 0.98 31.30 1.42 85.1 102.48 312 665,040,015 1,068,666,656

2013 9 0.41 0.72 0.52 35.37 1.44 86.8 61.09 357 836,050,305 1,696,803,625

2014 9 0.41 0.95 0.36 32.32 1.65 88.4 38.88 451 1,163,811,619 2,491,702,620

2015 9 0.41 1.51 0.02 35.81 2.17 93.0 21.61 704 1,995,265,497 3,730,605,512

2016 9 0.41 0.69 0.01 13.90 1.45 89.2 22.25 244 760,729,941 4,160,017,732

2017 9 0.41 0.29 0.01 14.57 1.08 87.0 20.30 103 352,053,015 4,340,676,594

2018 9 0.41 1.24 0.01 15.20 1.45 85.1 22.90 157 591,516,780 4,932,193,374

2019 9 0.41 0.29 0.01 19.12 1.08 82.9 25.50 66 273,744,012 5,205,937,386

2020 - - - - - - - - - (350,592,880) 4,177,122,428

Total 229.88 13.10 436.04 2,688





Recovery Rate (%)




0% 10% 15%

NPV (US$) 6,343,901,882 4,552,540,019 3,933,179,687

The profitability of this model is 5% and 14% lower than profitability of the first and the second modelrespectively. In addition, the marketable product is also decreased. However, this model offers better result interm of waste production since it produces the least amount of waste compared to Model 1 and Model 2.

5. Proposed Solution

According to the analysis of three models above, each model can be compared, as seen in Table 9, based onits total result in terms of mining throughput, milling throughput, waste production, marketable product,cumulative discounted cash flow, and NPV.

Table 9. Comparison of All Models

AlternativeMining

Throughput

Milling

Throughput

Waste

Production

Marketable

Product

Cumulative

Discounted CFNPV @ 0% NPV @ 10% NPV @ 15%

Model 1 297.86 16.21 501.37 2,832 4,376,097,660 6,538,208,426 4,589,689,946 3,921,306,862

Model 2 297.86 16.26 501.37 2,834 4,825,729,276 7,291,841,243 5,232,804,619 4,520,896,192

Model 3 229.88 13.10 436.04 2,688 4,177,122,428 6,343,901,882 4,552,540,019 3,933,179,687

Note: Mining Throughput (million tons)






The technique used to analyze the selection of three models above is based on the Simple Multi-attributeRating Technique (SMART) analysis. According to Decision Analysis for Management Judgement (Goodwin2004), the main stages in the SMART analysis are shown below:

Stage 1: Identify the decision maker (or decision makers).In this paper, it is assumed that this is just the business owner.

Stage 2: Identify the alternative courses of action.In this paper these are represented by the different three models the business owner can choose.

Stage 3: Identify the attributes which are relevant to the decision problem.The attributes/parameters which distinguish the different models will be environmental acceptance andfinancial analysis (NPV).

Stage 4: For each attribute, assign values to measure the performance of the alternatives on that attribute. Stage 5: Determine a weight for each attribute. Stage 6: For each alternative, take a weighted average of the values assigned to that alternative.

This will measure how well a model performs over all the attributes/parameters. Stage 7: Make a provisional decision. Stage 8: Perform sensitivity analysis to see how robust the decision is to changes in the figures supplied.

The analysis will determine the sensitivity of the outcomes of the model to changes in its parameters.

In order to make a decision there is a need to combine values for different attributes/parameters to gain aview of overall benefits which each model has to offer. An intuitive appealing way of achieving this is to attachweights to each attributes/parameters that reflect their importance to the decision maker. Thus, each attribute foreach model can be assigned with certain weight based on judgment. By using SMART analysis and stagesdefined above, the raw weight and normalized weight for each attribute/parameter can be seen on Table 10.

Table 10. Raw Weights and Normalized Weight of All Models

Model 1

Model 2

Model 3 Sum of

weights

Raw weight 80 180

Normalized weight 44.44 55.56

70

80

75

80

70

100

Attribute/ParameterAlternative

Cut-off grade optimization at Grasberg surface mine in

considering environmental impact

Environmental Acceptance Financial Analysis

70

In Figure 13 the aggregate value of benefits has been plotted against the waste production (in million tons)for each of the models. Model 2 lies on the efficient frontier that comprised of optimal portfolios. Thus the onlymodel which is worth considering is Model 2.



38

40

42

44

46

300 400 500 600

Ag

gre

ga

teB

enef

it

Waste Production (Mt)

EfficientFrontier

Model 3

Model 2

Model 1

Figure 13. A Plot of Aggregate Benefits against Waste Production for the Three Models

Sensitivity analysis shows that the each model is less sensitive to change in environmental acceptance asshown in Figure 14 for the Cut-off Grade Optimization Model. The aggregate benefit of each model is moresensitive to change in the financial analysis (NPV) as shown in the Figure 15. Furthermore, Model 2 gives thehighest value of benefits for all weights between 0 and 100.

30

40

50

60

70

80

90

0 50 100

Ag

gre

ga

teb

enef

its

Raw weight on Environmental Acceptance

Model 1

Model 2

Model 3

Figure 14. Sensitivity of Cut-off Grade Optimization Model to Environmental Acceptance



0

10

20

30

40

50

0 50 100

Ag

gre

ga

teb

enef

its

Raw weight on Financial Analysis

Model 1

Model 2

Model 3

Figure 15. Sensitivity of Cut-off Grade Optimization Model to Financial Analysis (NPV)

6. Conclusions

In this paper cut-off grade optimization in Grasberg surface mine in considering environmental impact notonly focusing on maximizing net present value (NPV) of the whole mining project over the lifespan of the mine,but also finding an optimum balance between the cut-off grade and environmental management considerationthrough optimizing waste production (overburden and tailing materials).

There are three models developed (based on Rashidinejad et al., 2008) as follows:

Model 1 – Consider the Environmental Cost during the Mining Operation Model 2 – Ignore and Postpone the Environmental Cost to the End of the Mine Life Model 3 – Consider Fixed Breakeven Cut-Off Grade during the Mining Operation

Model 2 is chosen according to the SMART analysis result based on weighting on environmental acceptanceand financial analysis (NPV).

References

[1] Goodwin, P. and Wright, G. (2004). Decision Analysis for Management Judgment. 3rd ed. West Sussex: John Wiley

& Sons, Ltd.

[2] James, P. M. (1999). The Miner and Sustainable Development. Min. Eng-Littleton, SME, pp. 89-92.

[3] Lane, K.F. (1988). The Economic Definition of Ore: Cutoff grades in Theory and Practice. London: Mining Journal

Books Ltd.

[4] Metal Production Plan (2011). 11Q1-R2 Forecast Metal Production Plan. PT Freeport Indonesia: Mine Engineering

Department.

[5] Rashidinejad, F., Osanloo, M. and Rezai, B. (2008). “An environmental oriented model for optimum cut-off grades in

open pit mining projects to minimize acid mine drainage”, International Journal of Environmental Science and

Technology, Vol. 5, No. 2, pp. 183-194.

[6] Tailing Management Plan (2007). PT Freeport Indonesia, Geo and Technical Services Department.

[7] Tour Companion (2009). PT Freeport Indonesia: Corporate Communication Department.

[8] Vietor, R. (2002). Freeport Indonesia. Harvard Business Case. Harvard Business School.



Cite this paper

Prasetya, L.B., and Simatupang, T.M. (2012). “Cut-off Grade Optimization at Grasberg Surface Mine in Considering

Environmental Impact,” Proceedings of The 3rd International Conference on Technology and Operations Management:

Sustaining Competitiveness through Green Technology Management, Bandung–Indonesia (July 4-6), pp. 89-106. ISBN:

978-979-15458-4-6.

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