The intention of this report is to provide a high-level ...

The intention of this report is to provide a high-level comparison of a few alternative hauling technologies, which can guide future work with the Original Equipment Manufacturers (OEM’s) and Operators to further investigate them. The report is a high level screening study based on a generalized and simplified mine plan and, as such, forward looking assumptions should not be based on it.

The cost estimates are high-level (-50% to +100%) and the mining cost is in undiscounted nominal terms. Based on the information available at the time and the limited engagement from OEMs, Stantec made several assumptions to help guide the study. As technologies are tested and proven in the oil sands, the results from the study may change. Technical risks of the technologies in the oil sands mining environment and Alberta’s cold climate also need to be assessed and addressed

-Canada’s Oil Sands Innovation Alliance Greenhouse Gas Environmental Priority Area

EVALUATION OF ALTERNATE ORE

AND WASTE HAULAGE

TECHNOLOGIES

December 12, 2019

Prepared for:

Canada’s Oil Sands Innovation Alliance (COSIA)

Prepared by:

Stantec Consulting Ltd. 200, 325 – 25 Street SE Calgary, Alberta T2A 7H8

Project Number 129500171

EVALUATION OF ALTERNATE ORE AND WASTE HAULAGE TECHNOLOGIES

This document entitled EVALUATION OF ALTERNATE ORE AND WASTE HAULAGE TECHNOLOGIES was

prepared by Stantec Consulting Ltd. (“Stantec”) for the account of COSIA (the “Client”). Any reliance on this

document by any third party is strictly prohibited. The material in it reflects Stantec’s professional judgment in

light of the scope, schedule and other limitations stated in the document and in the contract between Stantec

and the Client. The opinions in the document are based on conditions and information existing at the time the

document was published and do not take into account any subsequent changes. In preparing the document,

Stantec did not verify information supplied to it by others. Any use which a third party makes of this document

is the responsibility of such third party. Such third party agrees that Stantec shall not be responsible for costs

or damages of any kind, if any, suffered by it or any other third party as a result of decisions made or actions

taken based on this document.

Prepared by (signature)

Keith Wilson, P.Eng.


Table of Contents

EXECUTIVE SUMMARY ............................................................................................................ I

1.0 INTRODUCTION .......................................................................................................... 1.1

1.1 PURPOSE OF THE STUDY ......................................................................................... 1.1

1.2 STUDY APPROACH .................................................................................................... 1.2 1.2.1 Virtual Mine Site Description and Basis ....................................................... 1.3 1.2.2 Ore and Waste Haulage Technologies ........................................................ 1.9

1.3 ORGANIZATION OF THIS REPORT............................................................................ 1.9

2.0 OPTIONS SELECTION ................................................................................................ 2.1

2.1 INITIAL OPTIONS REVIEW ......................................................................................... 2.1

2.2 FINAL OPTION SELECTION ....................................................................................... 2.2

3.0 BASE CASE - CONVENTIONAL HAUL TRUCK ......................................................... 3.1

3.1 HAUL TECHNOLOGY OVERVIEW .............................................................................. 3.1

3.2 ANALYSIS METHODOLOGY ....................................................................................... 3.1

3.3 ASSUMPTIONS ........................................................................................................... 3.1 3.3.1 General Assumptions .................................................................................. 3.1 3.3.2 Costing Assumptions .................................................................................. 3.3 3.3.3 GHG Emission Assumptions ....................................................................... 3.4

3.4 TRUCK HOURS ........................................................................................................... 3.4

3.5 CAPITAL AND OPERATING COSTS ........................................................................... 3.7 3.5.1 Site Infrastructure ........................................................................................ 3.7 3.5.2 Equipment ................................................................................................... 3.7 3.5.3 Base Case Cost Summary .......................................................................... 3.7

3.6 PREDICTED GHG EMISSIONS ................................................................................... 3.8

3.7 CONCLUSIONS REGARDING THE BASE CASE ........................................................ 3.9

4.0 TROLLEY ASSIST CASE ............................................................................................ 4.1




4.4 PRELIMINARY TROLLEY SYSTEM ANALYSIS .......................................................... 4.3

4.5 TRUCK HOURS ........................................................................................................... 4.5

4.6 CAPITAL AND OPERATING COSTS ........................................................................... 4.5 4.6.1 Site Infrastructure ........................................................................................ 4.5 4.6.2 Equipment ................................................................................................... 4.6 4.6.3 Trolley Assist Case Cost Summary ............................................................. 4.7


4.8 CONCLUSIONS REGARDING THE TROLLEY ASSIST CASE.................................... 4.9


5.0 LNG SUBSTITUTION CASE ........................................................................................ 5.1



5.3 ASSUMPTIONS ........................................................................................................... 5.1 5.3.1 General Assumptions .................................................................................. 5.1 5.3.2 GHG Emission Assumptions ....................................................................... 5.2

5.4 TRUCK HOURS ........................................................................................................... 5.2

5.5 CAPITAL AND OPERATING COSTS ........................................................................... 5.2 5.5.1 Site Infrastructure ........................................................................................ 5.2 5.5.2 Equipment ................................................................................................... 5.4 5.5.3 LNG Substitution Case Cost Summary ....................................................... 5.4


5.7 CONCLUSIONS REGARDING THE LNG SUBSTITUTION CASE ............................... 5.7

6.0 REAR DUMP TRAILER CASE..................................................................................... 6.1




6.4 TRUCK HOURS ........................................................................................................... 6.4

6.5 CAPITAL AND OPERATING COSTS ........................................................................... 6.6 6.5.1 Site Infrastructure ........................................................................................ 6.6 6.5.2 Equipment ................................................................................................... 6.6 6.5.3 Rear Dump Trailer Cost Summary .............................................................. 6.6


6.7 CONCLUSIONS REGARDING THE REAR DUMP TRAILER CASE ............................ 6.8

7.0 COMPARISON OF CASES .......................................................................................... 7.1

7.1 CAPTAL AND OPERATING COSTS ............................................................................ 7.1


7.3 RISK ANALYSIS .......................................................................................................... 7.4

8.0 CONCLUSIONS ........................................................................................................... 8.1

8.1 BASE CASE ................................................................................................................. 8.1

8.2 TROLLEY ASSIST CASE ............................................................................................. 8.1

8.3 LNG DIESEL SUBSTITUTION CASE ........................................................................... 8.1

8.4 REAR DUMP TRAILER ................................................................................................ 8.2

8.5 CONCLUSION ............................................................................................................. 8.3

9.0 REFERENCES ............................................................................................................. 9.1

APPENDIX A ............................................................................................................................. 1


LIST OF TABLES

Table 1.1 VM3 Conventioal Case Annual Mine and Tailings Production Schedule ............................... 1.4 Table 1.2 VM3 Conventional Case Mine Waste Disposal Schedue (Mbcm) ......................................... 1.7 Table 3.1 Haul Segment Properties ....................................................................................................... 3.2 Table 3.2 Ultra Class Truck Fuel Burn ................................................................................................... 3.2 Table 3.3 Fixed Cycle Time Components .............................................................................................. 3.3 Table 3.4 Truck Time Usage Model ....................................................................................................... 3.3 Table 3.5 Base Case Ultra Class Truck Operating Cost Assumptions .................................................. 3.3 Table 3.6 Base Case Energy Cost Estimate .......................................................................................... 3.3 Table 3.7 Ultra Class Truck Purchase Price........................................................................................... 3.4 Table 3.8 Diesel Combustion GHG Emissions ....................................................................................... 3.4 Table 3.9 Base Case Cost Summary ..................................................................................................... 3.6 Table 4.1 Substation Operating Time Per Number of Simultaneous Trucks ......................................... 4.2 Table 4.2 Trolley Assist System Infrastructure Costs ............................................................................. 4.2 Table 4.3 Trolley Assist Ultra Class Truck Operating Cost .................................................................... 4.3 Table 4-4 Trolley Assist Case GHG Emission Assumptions .................................................................. 4.3 Table 4-5 Trolley Assist Case Site Infrastructure Capital Costs ............................................................. 4.5 Table 4.6 Trolley Assist Case Equipment Capital Costs ........................................................................ 4.5 Table 4.7 Trolley Assist Case LOM Cost Summary ............................................................................... 4.6 Table 4.8 Trolley System Benefit Analysis Summary ............................................................................. 4.8 Table 5.1 LNG Substitution Case GHG Emission Assumptions ............................................................ 5.2 Table 5.2 LNG Fugitive Emissions Assumptions ................................................................................... 5.2 Table 5.3 LNG Substitution Case Infrastructure Capital Cost Estimate ................................................. 5.3 Table 5.4 LNG Substitution Case Infrastructure Operating Cost Estimate ............................................ 5.3 Table 5.5 LNG Substitution Case Equipment Operating Csot Estimate ................................................ 5.4 Table 5.6 LNG Substitution Case GHG Emissions ................................................................................ 5.5 Table 6.1 Theoretical 793F Rear Dump Trailer Configureation ............................................................. 6.2 Table 6.2 793F Fuel Consumption ......................................................................................................... 6.3 Table 6.3 Rear Dump Trailer Fixed Cycle Times ................................................................................... 6.3 Table 6.4 250t Haul Truck and 400t Trailer Capital Cost ....................................................................... 6.4 Table 6.5 Rear Dump Trailer Operating Costs ....................................................................................... 6.4 Table 6.6 Rear Dump Trailer LOM Costs ............................................................................................... 6.6 Table 7.1 LOM CapEx and OpEx Cost Summary .................................................................................. 7.1 Table 7.2 LOM Energy Cnsumption and GHG Emisssion Summary ..................................................... 7.3 Table 7.3 Risk Analysis Summary .......................................................................................................... 7.4

LIST OF FIGURES

Figure 1-1 VM3 Conventioal Case Overburden Crest Advances ............................................................ 1.5 Figure 1-2 VM3 Conventional Case Site Layout ...................................................................................... 1.6 Figure 3-1 Base Case Truck Hours and Fleet Size ................................................................................. 3.5 Figure 3-2 Base Case Mining Cost Timeline ........................................................................................... 3.7 Figure 3-3 Base Case GHG Emissions Timeline ..................................................................................... 3.8 Figure 4-1 Trolley Assist Case Truck Hours ............................................................................................ 4.4 Figure 4-2 Trolley Assist Case Cost Timeline .......................................................................................... 4.6 Figure 4-3 Trolley Assist Case GHG Emissions Timeline ....................................................................... 4.7 Figure 4-4 Relationship Between Trolley System Length and Cost Savings by Road Type ................... 4.9 Figure 4-5 Average Trucks per Trolley Assist Substation ...................................................................... 4.10 Figure 5-1 50% LNG Substitution Case Cost Timeline ............................................................................ 5.5 Figure 5-2 90% LNG Substitution Case Cost Timeline ............................................................................ 5.5


Figure 5-3 LNG Substitution Case GHG Emissions ................................................................................ 5.6 Figure 6-1 Rear Dump Trailer .................................................................................................................. 6.1 Figure 6-2 Average Cycle Time Comparison ........................................................................................... 6.5 Figure 6-3 Rear Dump Trailer Case Truck Hours .................................................................................... 6.5 Figure 6-4 Rear Dump Trailer Case Cost Timeline ................................................................................. 6.7 Figure 6-5 Rear Dump Trailer Case Emissions Timeline ........................................................................ 6.8 Figure 7-1 Comparison of CapEx and OpEx Costs ................................................................................. 7.2


i

Executive Summary

Study Purpose and Cases

The purpose of this study was to assess the impacts on costs, mine site infrastructure requirements, and

GHGs for alternative or and waste haul technologies over a base mine plan. For the haulage technologies

listed below, full life of mine plans with relative costing were developed for the mine site conditions

described in the “Fines Management Study: Report Issued for Review February 2, 2017” submitted to the

COSIA DPL Group by Norwest Corporation (Norwest) in 2017 and in Table ES.1 below.

Table ES.1 VM3 Conventional Case Annual Mine and Tailings Production Schedule

Ore Grade Wt% Bitumen

Fines Wt% of Mineral

Waste to Ore Volume Ratio

Out of Pit Area Overburden

Type In-Pit

Foundation

10.7 22 1.6 Un-Constrained Dominant Clearwater

Poor (Basal Clays)

The alternative ore and waste hauling technologies assessed based on the VM3 site conditions include:

1. Base Case – Conventional Ultra Class (400t) haul trucks operating on diesel fuel

2. Trolley Assist Case – Ultra Class (400t) haul trucks with electric trolley assist on pre-determined

haul segments

3. LNG 50% Substitution Case – Ultra Class (400t) haul trucks with fumigated injection technology

resulting in a 50% LNG to diesel substitution rate

4. LNG 90% Substitution Case – Ultra Class (400t) haul trucks in direct injection technology


5. Rear Dump Trailer Case – Utilizing smaller 250t haul trucks set up as tractor units to pull a trailer

with ultra class (400t) payload capacity.

For each of the cases, estimates of costs, site infrastructure, and GHG emissions were developed.

Mining Cost Results

Figure ES-1 illustrates the incremental undiscounted costs over the base case for each of the alternative

haulage technologies. Only costs related to the mine haul fleet which vary between the technologies were

estimated. All other costs were understood to be the same between the cases and were not considered

for the purpose of this study.


ii

Figure ES-1 Estimated Incremental Costs Compared to the Base Case

• All cases resulted in decreased mining costs except for the rear dump trailer case which resulted

in increased life of mine cost. This assumes there are no extraordinary costs associated with

developing, testing, and implementing each technology.

• The LNG Case at 90% diesel substitution resulted in the lowest undiscounted cost. This assumes

that LNG is produced on-site using existing in-place natural gas service. LNG at 50% diesel

substitution and the trolley assist cases were essentially equivalent in cost over the life of mine.

Discussion of Mining Costs

Based on the assumptions for energy cost, diesel was the most expensive fuel used for the mine truck

fleet. Therefore, substitution of diesel for alternative energy sources reduced overall life of mine cost. The

trolley assist case reduced engine load on uphill gradients where the trolley system was installed by

powering the electric drive motors directly from the electrical grid. Additionally, fewer haul trucks are

required over the life of mine due to a significant increase in speed along trolley segments. The rear

dump trailer case increased the overall truck gross weight leading to increased cycle times. The

additional truck hours and truck units over the life of mine added cost despite the lower hourly operating

cost and capital purchase cost of the mine trucks themselves. As a truck using this configuration is not

currently in production, high level assumptions regarding truck performance and cost were required for

analysis. Fixed cycle time components including spot and dump times were increased to consider the

complexity and inefficiencies related to dump trailer operation. Additionally, this truck configuration was

applied to all mine material. There may be an opportunity to apply this technology to specific hauls where

rolling resistances and haul road gradients are limited and truck performance is not reduced significantly;

however, there were no haul routes that had reduced cycle times in the analysis. The LNG substitution

cases resulted in significantly reduced life of mine costs due to the relatively inexpensive cost of LNG

when compared to diesel. These cases assumed LNG would be produced on-site in an LNG plant using


iii

existing natural gas service. Depending on technology development and overall LNG demand in the

Athabasca region, a regional LNG supplier may reduce the requirement for an on-site LNG plant;

however, the unit cost of LNG may increase from this analysis.

GHG Emission Results

Figure ES-2 shows the incremental GHG emissions compared to the base case conventional diesel-

powered truck fleet.

Figure ES-2 Estimated Incremental GHG Emissions Compared to the Base Case

All cases reduced life of mine GHG emissions with the exception of the LNG 50% substitution case. For

each case with electricity consumption, emissions were calculated using both the Alberta grid average

GHG intensity values found in the Carbon Offset Emission Factors Handbook published by the Alberta

Government and a GHG intensity for on-site co-gen power generation provided by COSIA.

GHG Emission Discussion

Due to Alberta’s reliance on coal, the GHG intensity factor for the Alberta grid average is significantly

higher than alternative electrical generation technologies. As shown, co-gen power generation can

significantly reduce the GHG emissions of an operation; therefore, two values are shown for the trolley

assist and LNG substitution cases. Trolley assist technology reduces diesel consumption significantly on

up-hill gradients where engine load factors are expected to be 100%. The GHG emission results are

highly sensitive to the GHG intensity of power generation due to the power demands associated with the

trolley assist technology. The rear dump trailer utilizes a smaller chassis and engine size to transport the

equivalent payload of an ultra-class truck. The increased payloads lead to longer cycle times and

increased truck hours over the life of the mine. However, the decreased fuel consumption of the smaller

engine offsets the increase in truck hours to slightly reduce diesel consumption over the life of mine. This

truck configuration was highly conceptual, and the assumptions made on truck performance and fuel


iv

economy may be refined through further development altering the results of this study. LNG substitution

may reduce life of mine GHG emissions due to the lower GHG intensity associated with the combustion of

LNG. However, fugitive emissions, the release of methane gas into the environment during the transport

and storage of LNG, may offset the benefit of the lower combustion GHG intensity. Methane’s global

warming potential (GWP) is estimated to be 25 times that of carbon dioxide; therefore, direct release into

the environment is especially harmful. This is shown with the LNG 50% substitution case using fumigated

injection technology which is understood to suffer from fugitive emissions exceeding 4% of total fuel

usage. When accounting for fugitive emissions, the fumigated injection technology increased the overall

GHG emissions over the life of the mine. Direct injection technology associated with the 90% substitution

case has a much lower estimate of fugitive emissions of just 0.75%. Based on the assumptions in this

study, 90% diesel substitution would significantly reduce the GHG emissions over the life of the mine.

Further development of the LNG substitution technologies limiting or eliminating fugitive emissions would

provide further benefit on top of this analysis.


Introduction

wn v:\1295\active\129500171\reports\final\alternate ore and waste technologies_final.docx 1.1

1.0 INTRODUCTION

Stantec Consulting Ltd. (Stantec) was commissioned by Canada’s Oil Sands Innovation Alliance (COSIA)

to complete a high-level study of selected alternative haulage technologies to further understand the

environmental and cost impacts for use in oil sands mining. This work was intended to build on the results

of studies prepared by AECOM and GTI Corporation (GTI Corp) which focused on less energy intensive

alternatives for ore handling in an oil sands mine.

Increased focus on reducing greenhouse gas emissions (GHG) from mine operations while reducing or

optimizing mine operating costs has resulted in the development of several alternative waste and ore

haulage technologies. Additionally, existing haulage technologies and methods which have been

implemented throughout the mining industry should be assessed for their viability for use in an oil sands

setting. The desire to advance the development and implementation of technologies that result in

decreased GHG intensity and cost is primarily due to the increased focus of regulators and the

communities on GHG emissions and the prolonged period of depressed prices of crude oil which began

in in 2014.

The operating oil sands open pit mines primarily utilize 400 short ton ultra-class mining trucks paired with

large electric cable or hydraulic shovels to haul material. The GHG emissions from diesel combustion in

mine haul trucks is considerable. Alternative technologies and methods of transporting ore and waste can

be assessed for environmental impacts following their implementation. Cost, equipment productivity, and

required mine infrastructure for operating diesel powered mine haul trucks is well understood by the oil

sands operators, with minor variation between operations. The alternative methods and technologies

available have been developed, to varying degrees, for full scale implementation which often results in

less confidence in the cost estimate and indirect impacts to the operation. Implementation of alternative

technologies in other global regions may be necessary or applicable due to factors such as limited

resources, mine geometry and geology, and weather that may differ in open pit oil sand scenarios.

GHG emissions can vary significantly between technologies as the combustion of LNG or the use of

electric trolley assist systems typically results in decreased GHG intensity as compared to diesel

combustion. However, it is necessary to understand the current development of the technology, the direct

and indirect consequences of implementing alternative technologies, and the overall impact to GHG

emissions.

1.1 PURPOSE OF THE STUDY

The primary purpose of the Study was to estimate, at a conceptual level, how selected ore and waste

haulage technologies could incrementally impact mining capital and operating costs (CapEx and OpEx)

and mine fleet GHG emissions.


Introduction


1.2 STUDY APPROACH

The basis of the Study used a conceptual life of mine (LOM) plan completed on a virtual mine site

prepared for the “Fines Management Study: Report Issued for Review February 2, 2017” submitted to the

COSIA DPL Group by Norwest Corporation (Norwest) in 2017. The current Study focused on the costs

and emissions related to the mine haulage fleet only, no consideration was given to any other aspects of

mine development, cost, or impacts outside of this scope.

Work completed for the Study was primarily composed of the development of a conceptual life of mine

haul network, assessed for each status map period of the Fines Management Study. Haul routes were

drawn between source and destination centroids following a consistent process. The conceptual mine

plan used as a basis of this Study should be regarded as a pre-scoping level of detail as noted in the

Fines Management Study. Therefore, equipment hours, costs, and GHG emissions are considered

comparable to each other for identification of trends; however, cost estimates may not be directly

comparable to those based on more detailed engineering work such as pre-feasibility or feasibility

studies.

The Study focused on existing technologies that may be available for implementation at an oil sands mine

in the near future. A total of five cases were identified for evaluation listed below.

• Base Case – Conventional Ultra Class (400t) haul trucks operating on diesel fuel

• Trolley Assist Case – Ultra Class (400t) haul trucks with electric trolley assist on pre-determined

haul segments

• LNG 50% Substitution Case – Ultra Class (400t) haul trucks with fumigated injection technology


• LNG 90% Substitution Case – Ultra Class (400t) haul trucks in direct injection technology


• Rear Dump Trailer Case – Utilizing smaller 250t haul trucks set up as tractor units to pull a trailer

with ultra class (400t) payload capacity

In each case, the conceptual mine plan was unchanged, with the mine advance, ore and waste

movements, and placement constant. All cases were analyzed for incremental changes to the base case.

Each case was analyzed in the following order:

• Calculate mine truck fleet equipment hours

• Calculate mine truck fleet energy consumption and resulting GHG emissions

• Estimate mine CapEx and OpEx based on mine truck fleet and supporting energy technology

only


Introduction


This evaluation was completed at a concept level and as such the associated cost estimates are

expected to be in the range of -50% to +100%.

In order to simulate the effects of a carbon tax on the selected technologies, a tax of $30/t for GHG

emissions was applied to years 1 – 4 of the planning cycle. This tax was increased to $50/t in year 5 and

onward.

1.2.1 Virtual Mine Site Description and Basis

The virtual mine site used for this Study was based on the VM3 Conventional Case (VM3) found in the

Fines Management Study. The conceptual mine plan was based on a recovery of 200,000 barrels of

whole bitumen per calendar day. The VM3 case annual mine and tailings production schedule is found in

Table 1.1.


Introduction


Table.1 VM3 Conventional Case Annual Mine and Tailings Production Schedule

Period Ore (Mt)

Ore (Mbcm)

Mine Waste (Mbcm)

Ore Rejects (Mbcm)

FTT Deposit (Mm3)

Flot Tails Deposit (Mm3)

PSV U/F Deposit (Mm3)

FFT Inventory

(Mm3)

1 30.5 14.5 23.2 0.4 0.6 1.2 13.0 13.3

2 61.0 29.0 46.4 0.9 1.2 2.4 26.0 35.6

3 91.4 43.5 69.7 1.3 1.8 3.7 39.0 65.3

4 121.9 58.1 92.9 1.7 2.4 4.9 51.9 101.9

5 121.9 58.1 92.9 1.7 2.4 4.9 51.9 131.8

6 121.9 58.1 92.9 1.7 2.4 4.9 51.9 158.6

7 121.9 58.1 92.9 1.7 2.4 4.9 51.9 183.9

8 121.9 58.1 92.9 1.7 2.4 4.9 51.9 207.7

9 121.9 58.1 92.9 1.7 2.4 4.9 51.9 230.5

10 121.9 58.1 92.9 1.7 2.4 4.9 51.9 252.5

11 121.9 58.1 92.9 1.7 2.4 4.9 51.9 273.9

12 121.9 58.1 92.9 1.7 2.4 4.9 51.9 294.7

13 121.9 58.1 92.9 1.7 2.4 4.9 51.9 315.3

14 121.9 58.1 92.9 1.7 2.4 4.9 51.9 335.6

15 121.9 58.1 92.9 1.7 2.4 4.9 51.9 355.8

16 121.9 58.1 92.9 1.7 2.4 4.9 51.9 375.9

17 121.9 58.1 92.9 1.7 2.4 4.9 51.9 395.9

18 121.9 58.1 92.9 1.7 2.4 4.9 51.9 415.8

19 121.9 58.1 92.9 1.7 2.4 4.9 51.9 435.7

20 121.9 58.1 92.9 1.7 2.4 4.9 51.9 455.4

21 121.9 58.1 92.9 1.7 2.4 4.9 51.9 475.1

22 121.9 58.1 92.9 1.7 2.4 4.9 51.9 494.7

23 121.9 58.1 92.9 1.7 2.4 4.9 51.9 514.3

24 121.9 58.1 92.9 1.7 2.4 4.9 51.9 533.8

25 121.9 58.1 92.9 1.7 2.4 4.9 51.9 553.2

26 121.9 58.1 92.9 1.7 2.4 4.9 51.9 572.6

27 121.9 58.1 92.9 1.7 2.4 4.9 51.9 592.0

28 121.9 58.1 92.9 1.7 2.4 4.9 51.9 611.3

29 121.9 58.1 92.9 1.7 2.4 4.9 51.9 630.5

30 121.9 58.1 92.9 1.7 2.4 4.9 51.9 649.8

31 121.9 58.1 92.9 1.7 2.4 4.9 51.9 668.9

32 121.9 58.1 92.9 1.7 2.4 4.9 51.9 688.1

33 121.9 58.1 92.9 1.7 2.4 4.9 51.9 707.1

34 121.9 58.1 92.9 1.7 2.4 4.9 51.9 726.1

35 121.9 58.1 92.9 1.7 2.4 4.9 51.9 745.1

36 121.9 58.1 92.9 1.7 2.4 4.9 51.9 763.9

37 121.9 58.1 92.9 1.7 2.4 4.9 51.9 782.8

38 121.9 58.1 92.9 1.7 2.4 4.9 51.9 801.6

39 121.9 58.1 92.9 1.7 2.4 4.9 51.9 820.3

40 121.9 58.1 92.9 1.7 2.4 4.9 51.9 839.0

Totals 4,693.5 2,235.0 3,576.0 67.1 93.9 187.7 1,999.5

The layout for ex-pit and in-pit waste and tailings disposal areas was based on a high level mine face

advance schedule as shown on Figure 1-1. Tailings and waste disposal areas were designed to provide

sufficient containment based on the volumes in Table 1.1 and constructed to minimize waste haulage.


Introduction


Figure 1-1 VM3 Conventional Case Overburden Crest Advances

The mine advances from the northeast corner of the pit to minimize distances to the External Tailings

Area (ETA) starter dyke and the Ore Preparation Plant (OPP). Mining progresses southward to open in-pit

tailings capacity before mining westward to expose the footprint for Dyke 1 to Dyke 3. For this Study, the

relocation of the ore crushers C1 and C2 to the locations identified as C3 and C4 was not incorporated.

The basis for this decision was to provide the largest distribution of hauls throughout the mine life for the

analysis of each technology. The site layout shown on Figure 1-2 shows the ex-pit and in-pit waste and

tailings disposal areas used in this Study. The Fines Management Study VM3 case truck hours were

based on adjusted straight-line centroid to centroid distances.


Introduction


Figure 1-2 VM3 Conventional Case Site Layout

Mine waste disposal is typically hauled to the location resulting in the shortest haul, optimizing estimated

mine fleet truck hours. The mine waste disposal schedule is shown in Table 1.2. Average annual haul

distances for both ore and waste are shown in Table 1.3.

Additional details and descriptions of the conceptual mine plan and structures are available in the Fines

Management Study report.


Introduction


Table 1.2 VM3 Conventional Case Mine Waste Disposal Schedule (Mbcm)

Period MWD

1 MWD

2 MWD

3 MWD

4 MWD

5 MWD

6 MWD

7 MWD

8

ETA Starter Dyke

ETA SD d/s

Buttress

Dyke 1

Dyke 2

Dyke 3

Dyke 4

ITA 1 ITA2 Total

PP

64.6

64.6

129.2

01

1.1

2.5

3.6

02

2.3

5.0

7.3

03

2.9

8.0

10.9

04 76.9 2.0

2.3

81.2

05 86.9 3.0 3.0

92.9

06 42.9 5.2 44.8

92.9

07 25.0 3.0 49.9

15.0

92.9

08

92.9

92.9

09

92.9

92.9

10

92.9

92.9

11

43.9 39.0

-

10.0

92.9

12 5.0

16.9 18.0

6.0

47.0

92.9

13

40.2

-

52.7

92.9

14

10.0

82.9

92.9

15

5.0

87.9

92.9

16

8.0

8.4

76.5

92.9

17

13.0

79.9

92.9

18

92.9

92.9

19

12.0

80.9

92.9

20

30.0

62.9

92.9

21

82.9

10.0

92.9

22

81.9

11.0

92.9

23

82.9

10.0

92.9

24

83.9

9.0

92.9

25

54.0

23.0

15.9 92.9

26

40.0

52.9 92.9

27

25.0 27.9

40.0

92.9

28

63.9

29.0

92.9

29

92.9

92.9

30

92.9

92.9

31

31.0

59.0 2.9

92.9

32

31.0

59.0 2.9

92.9

33

67.9

25.0

92.9

34

22.6 52.7

17.6

92.9

35

92.9

92.9

36

92.9

92.9

37

92.9

92.9

38

92.9

92.9

39

92.9

92.9

40

92.9

92.9

Total 236.7 84.1 437.2 105.2 - 514.6 368.1 610.1 64.6 17.8 42.4 - 290.0 48.4 688.6 68.8 3,576.6


Introduction


Table 1.3 VM3 Conventional Case Mine Average Haul Distance (km one-way)

Period Ore Average Haul Distance

(km one-way) Waste Average Haul Distance

(km one-way)

PP 0.00 6.66

01 1.37 7.88

02 1.37 7.83

03 1.32 8.09

04 1.30 5.79

05 2.65 2.95

06 3.06 2.90

07 3.06 2.35

08 4.20 1.91

09 4.20 1.91

10 5.14 2.67

11 3.02 4.73

12 4.12 3.50

13 4.12 3.94

14 4.49 2.59

15 6.20 3.46

16 6.20 3.83

17 6.19 3.75

18 6.19 3.75

19 4.38 3.15

20 4.38 2.69

21 3.80 2.30

22 2.69 2.30

23 5.89 3.91

24 5.89 3.93

25 4.22 2.73

26 7.10 1.72

27 4.73 2.86

28 4.73 1.58

29 4.90 2.19

30 4.90 2.19

31 1.31 4.33

32 1.31 4.33

33 5.27 3.65

34 5.27 2.00

35 6.83 2.01

36 6.83 2.01

37 4.08 3.09

38 4.08 3.09

39 4.09 4.55

40 4.09 4.55


Introduction


1.2.2 Ore and Waste Haulage Technologies

A total of four alternative haulage technologies were compared to conventional diesel powered rear dump

haul trucks typically used in the oil sands. These consisted of:

• Trolley Assist – Ultra Class (400t) haul trucks with electric trolley assist on pre-determined haul

segments

• LNG 50% Substitution – Ultra Class (400t) haul trucks


• Rear Dump Trailer – Utilizing smaller 250t haul trucks set up as tractor units to pull a trailer with

ultra class (400t) payload capacity.

All analyses were completed using the same conceptual mine plan described in the previous section, no

changes were made to the production or placement schedules between the cases.

1.3 ORGANIZATION OF THIS REPORT

This report is organized as follows:

• Section 1: This section describes the background for the Study, the approach and methodology,

and the design basis for cases evaluated.

• Section 2: This section provides details on the option selection process.

• Section 3 to Section 6: These sections provide the details for the Alternative Technology Cases.

Each case is described in similar sequential steps.

• Section 7: This section provides a comparison of the results from a cost, GHG emissions, and

risk perspective.

• Section 8: This section provides conclusions from the Study.


Options Selection


2.0 OPTIONS SELECTION

2.1 INITIAL OPTIONS REVIEW

Stantec reviewed the range of alternate haulage technologies as identified previously by AECOM and

GTI. During the project kick-off meeting with the COSIA working group, these alternate technologies

were discussed.

AECOM had identified three non-haulage options that offered potential for reducing GGG emissions:

• Troughed belt conveyors

• Slurry pipeline

• RopeCon

AECOM also identified two haulage options that outperformed their base case which consisted of

conventional diesel haulage:

• Belly dump haulage

• Trolley Assist

The non-haulage options were deferred as they were considered to be beyond the scope of this

evaluation. The meeting attendees, which included representatives from current oil sands operators,

concluded that the belly dump haulage option was not suited for implementation in the oil sands and was

therefore excluded from further study.

GTI identified over forty technologies that were further subdivided into four categories:

• Alternative fuels

• Electrification

• Powertrain

• Miscellaneous Improvements

The meeting attendees identified the following options as meriting another level of review in determining

which 3 options would be carried forward in the technology review process.

• CNG powered haulage with regenerative breaking

• LNG powered haulage with regenerative breaking

• Trolley Assist technologies


Options Selection


• Renewable fuels

• Diesel Hybrid technologies

• Other novel haul truck designs

2.2 FINAL OPTION SELECTION

Stantec had originally envisioned engaging the major equipment manufacturers to provide support related

to the selected haulage technologies. This assumption proved to be incorrect as the manufacturers were

unwilling to engage Stantec with advice or input related to future haulage technology or support related to

expected CapEx or OpEx.

This reluctance on the part of the major equipment manufacturers limited the ability to explore alternate

technology options related to specific CNG/LNG, renewable fuel, regenerative breaking, or diesel hybrid

powered haul trucks. As a result, Stantec and the COSIA working group chose to evaluate two LNG

powered technologies with diesel substitutions of 50% and 90% without delving into the details of the

specific engine technologies. It was agreed that this range of potential diesel substitutions would be

reasonable given the state of current and near future technologies.

A Trolley Assist technology remained as one of the options for review along with a rear dump trailer that

could potentially haul an Ultra-Class payload with a smaller tractor unit. In summary the four alternate

technologies consisted of:

• Trolley Assist – Ultra Class (400t) haul trucks



• Rear Dump Trailer – Utilizing smaller 250t haul trucks set up as tractor units to pull a trailer with

Ultra Class (400t) payload capacity


Base Case - Conventional Haul Truck


3.0 BASE CASE - CONVENTIONAL HAUL TRUCK

Most currently operating open pit oil sands mines operate diesel fueled ultra class rear dump haul trucks

with a payload of approximately 400 short tons. The conventional case uses assumptions typical of an

existing operating oil sands open pit mine.

3.1 HAUL TECHNOLOGY OVERVIEW

Diesel fueled haul trucks are deployed in open pit mines throughout the world, including mineable oil

sands. Trucks are powered by a large diesel combustion engine and can be electric or mechanically

driven. Infrastructure is relatively simple, with on site fueling stations located within the mine site limiting

impact to operations when fueling is required. A stable supply of diesel and a comprehensive supply

network in Alberta results in a relatively low risk and low complexity operating environment.

3.2 ANALYSIS METHODOLOGY

The base case analysis was completed following a conventional truck hour estimation methodology.

Typical haul routes were drawn in Hexagon’s MineSight software between source and destination

centroids, following a simplistic road network accounting for ramp grades, on-bench haul segments, and

long term pit access ramps. Lines were exported and processed in Microsoft Excel, attributing haul

segments with properties such as road grade, rolling resistance, and speed restrictions as shown in Table

3.1. The processed haul routes were imported into RPM’s Talpac software where an estimate of empty

and loaded travel times and engine duty cycle was simulated using the current CAT 797F haul truck from

the Talpac equipment database.

Talpac data was exported for individual segments where diesel consumption was estimated based on

engine duty cycle. Assumptions regarding estimated fuel burn of an ultra-class truck are shown below in

Table 3.2. Total cycle time was estimated as the combination of the Talpac travel times and the fixed

cycle time components shown in Table 3.3.

Capital and operating costs were then calculated based on annual total fleet truck hours and time usage

assumptions detailed in Tables 3.4 - 3.7.

Greenhouse gas emissions were then estimated based on the diesel fuel combustion and the GHG

intensity factor for diesel shown in Table 3.8.

3.3 ASSUMPTIONS

3.3.1 General Assumptions

Talpac import data was prepared based on MineSight string data with segments attributed with the below

properties.




Table 3.1 Haul Segment Properties

Segment Rolling Resistance

[%] Max Speed

[Km/h]

Around Shovel 5 15

Ore Bench 5 65

Down Grade 2.5 25

Flat Haul 2.5 65

Up Grade 2.5 50

Around Dump 5 15

An engine fuel burn curve was developed using data from the CAT Handbook 47. Fuel burn carries a

linear relationship with engine duty cycle, therefore it was possible to calculate a formula based on the

Talpac segment duty cycle. CAT estimates a 10% engine duty cycle at idle.

Table 3.2 Ultra Class Truck Fuel Burn

Based on CAT handbook values, plotted linear fuel consumption for line of best fit

Truck Duty Cycle Fuel Consumption

797F

15* 143

25* 215

35* 286

45* 358

55** 429

65** 501

75** 572

85** 644

95** 715

100** 751

10 / Idle 107

* From CAT Handbook 47

** Calculated based on line of best fit formula

Fixed cycle time components are added to the Talpac travel time estimate to calculate average cycle

time. Fixed cycle time components consist of spot times, load times, dump times, and queue times.

y = 7.154x + 35.78R² = 1

0

50

100

150

200

250

300

350

400

0* 10* 20* 30* 40* 50*




Table 3.3 Fixed Cycle Time Components

Segment Segment Time

Spot @ Shovel 0.5

Spot @ Dump 0.5

Load 2.0

Dump 1.3

Queue Total 2.0

Total Fixed Cycle Time 6.3

Truck fleet hours were based on a time usage model including physical availability (PA), use of availability

(UA), and operating efficiency (OE).

Table 3.4 Truck Time Usage Model

Truck KPI's

Truck UA 90%

Truck PA 82%

Truck OE 90%

NOH / Truck 5,818 per year

Lifetime 70,000

3.3.2 Costing Assumptions

Operating costs were based on annual total truck fleet hours and diesel consumption.

Table 3.5 Base Case Ultra Class Truck Operating Cost Assumptions

Expense Cost (C$/NOH)

Parts 350.00

Lube 30.00

Tires 90.00

Maintenance Labour 216.87

Operator Labour 86.70

Total 773.57

Table 3.6 Base Case Energy Cost Estimate

Energy Cost (C$/L)

Diesel 0.90

Capital costs are based on a truck lifetime of 70,000 hours, increasing to 100,000 hours towards end of

mine life to reduce truck purchases in the final operating years of the mine. The truck purchase price is




estimated in Table 3.7, this value is considered reasonable for comparison between the cases, however,

actual purchase cost for an ultra-class truck varies with the specific truck model, features, and the

operators negotiation with the manufacturer.

Table 3.7 Ultra Class Truck Purchase Price

Truck Purchase Price (C$)

Ultra Class 6,700,000

3.3.3 GHG Emission Assumptions

Greenhouse gas emissions for diesel consumption are based on the Carbon Offset Emission Factors

Handbook published by the Alberta Government in March 2015. CO2eq intensity for diesel was calculated

by incorporating the Global Warming Potential of Methane and N2O as shown in Table 3.8.

Table 3.8 Diesel Combustion GHG Emissions

Emission Factor Emissions

CO2 Emissions 2.663 x 10-3 t/L

CH4 Emissions 0.133 x 10-3 t/L

N2O Emissions 0.400 x 10-3 t/L

CH4 GWP 25

N2O GWP 298

CO2eq Emissions 2.786 x 10-3 t/L

3.4 TRUCK HOURS

Truck hours for the base case fleet were calculated with the conceptual mine material balance and total

cycle times. Minor waste smoothing was performed to reduce truck hour requirement spikes in Year 6, 23,

24, and 26. Total fleet truck hours averaged approximately 400,000 NOH/yr with a total fleet size of

approximately 70 ultra class trucks as illustrated on Figure 3-1.

For this study, haul strings were drawn from each source centroid to each structure source destination for

the specific status map. Haul strings were created to account for source and destination elevations, ramp

locations, and advancing face configurations to simulate realistic haul profiles for analysis. As shown in

Table 3.9, haul distances have consistently increased when compared to the VM3 Conventional Case

from the Fines Management Study which estimated straight line centroid to centroid distances. As the

Fines Management Study was focused on fluid fines inventory, this method was applicable and provided

a reasonable estimate of truck hours to compare incremental variance between the cases. However, this

Study required further analysis of the truck haul profile segments in order to simulate conditions in a

typical operating oil sands mine. As shown, haul distances have increased most significantly for in-pit




mine waste structures where the haul would be required to either ramp down to pit bottom for access to

dyke and low level in-pit dumps or use a waste bench access road along the pit wall for waste dumps at

higher elevations. Life of mine haul profile maps are shown in Appendix A.

Figure 3-1 Base Case Truck Hours and Fleet Size




Table 3.9 Base Case vs VM3 Fines Study Haul Distances

Period

VM3 Fines Study Base Case

Ore Average Haul Distance

(km one-way)

Waste Average Haul Distance

(km one-way)

Ore Average Haul Distance

(km one-way)

Waste Average Haul Distance

(km one-way)

PP 0.0 6.7 0.0 8.9

01 1.4 7.9 3.0 10.9

02 1.4 7.8 3.0 10.9

03 1.3 8.1 2.9 11.1

04 1.3 5.8 2.9 7.3

05 2.6 2.9 2.9 7.2

06 3.1 2.9 3.5 5.1

07 3.1 2.3 3.5 4.5

08 4.2 1.9 4.2 3.4

09 4.2 1.9 4.2 3.4

10 5.1 2.7 5.4 2.8

11 3.0 4.7 4.4 6.7

12 4.1 3.5 4.0 6.8

13 4.1 3.9 4.0 6.8

14 4.5 2.6 5.1 6.0

15 6.2 3.5 6.3 8.2

16 6.2 3.8 6.3 8.2

17 6.2 3.8 8.1 3.9

18 6.2 3.8 8.1 3.8

19 4.4 3.2 6.2 10.0

20 4.4 2.7 6.2 8.9

21 3.8 2.3 5.5 6.0

22 2.7 2.3 5.5 6.0

23 5.9 3.9 8.7 6.1

24 5.9 3.9 8.7 6.1

25 4.2 2.7 7.5 5.4

26 7.1 1.7 10.4 8.7

27 4.7 2.9 8.6 5.3

28 4.7 1.6 8.6 4.2

29 4.9 2.2 9.5 4.5

30 4.9 2.2 9.5 4.5

31 1.3 4.3 8.2 4.5

32 1.3 4.3 8.2 4.5

33 5.3 3.7 10.3 6.5

34 5.3 2.0 10.3 5.1

35 6.8 2.0 11.9 3.7

36 6.8 2.0 11.9 3.7

37 4.1 3.1 9.6 7.5

38 4.1 3.1 9.6 7.5

39 4.1 4.5 9.1 7.1

40 4.1 4.5 9.1 7.1




3.5 CAPITAL AND OPERATING COSTS

Capital and Operating Costs are estimated based on fleet truck hours. The Base Case is assumed to

have no incremental capital infrastructure planned as the infrastructure is required in all cases.

3.5.1 Site Infrastructure

No additional site infrastructure is required in the base case.

3.5.1.1 Capital Cost


3.5.1.2 Operating Expenses


3.5.2 Equipment

Equipment for the base case consists entirely of the conventional ultra class mining trucks.


Capital cost is based on the annual required fleet hours and replacement schedule for each truck. Total

truck CapEx is estimated at $1,434M.


Operating cost includes operator and maintenance labour, parts, tires, and lube applied per net operating

hour. Mine haulage fleet fuel consumption is based on estimated fuel consumption by truck cycle and is

included in the OpEx estimate. Total OpEx over the 40-year mine life is estimated to be $17,233M.

3.5.3 Base Case Cost Summary

Total costs are $19,500M over the 40-year mine life for the base case. Truck operating costs make up

61% of the total estimated cost, with diesel accounting for nearly 28% of total mine cost. The base case

cost estimate includes capital cost for mining truck purchases and related operating expenses as shown

in Table 3.9. Annual cost varies with truck fleet hours based on length and profile of hauls and the

replacement schedule for mine haul trucks as shown on Figure 3-2.

Table 3.9 Base Case Cost Summary

Costs Total Cost ($M) Unit Cost ($/BCM)

Truck CAPEX 1,434 0.25

Truck OPEX 11,854 2.04

Diesel 5,379 0.93

Carbon Tax 811 0.14

Total 19,477 3.35




Figure 3-2 Base Case Mining Cost Timeline

3.6 PREDICTED GHG EMISSIONS

Greenhouse gas emissions are estimated for the energy consumed by the truck fleet only. Emissions

from other parts of the operation such as other mobile equipment and processing are assumed to be

constant between all cases and were not considered. GHG emissions are calculated solely on the

consumption of diesel fuel which varies with the truck fleet hours and average engine duty cycle. The total

GHG emissions over the LOM was estimated to be 16.6 Mt CO2eq. The annual emission diesel

consumption and corresponding emissions are shown on Figure 3-3.




Figure 3-3 Base Case GHG Emissions Timeline

3.7 CONCLUSIONS REGARDING THE BASE CASE

The base case is a conventional open pit mining estimate. Truck hours are generated from a simplistic

haul network simulated by the Talpac software. Fuel burn rates are typically applied as an average per

net operating hour and therefore fuel burn by duty cycle remains theoretical and is difficult to verify. Diesel

consumption could, therefore, vary with a more detailed analysis or with operator data. However, this

methodology is applied consistently to the other cases and provides a fair comparison.

The base case provides the basis of analysis for the remaining cases.


Trolley Assist Case


4.0 TROLLEY ASSIST CASE

Trolley assist systems have been implemented in several open pit mines throughout the world; however,

are relatively rare in North America.


Trolley assist systems provide electric current from an overhead wire directly to the electric drive motors

in a diesel-electric haul truck, bypassing the diesel engine and therefore reducing the engine duty cycle to

idle for the period the truck is connected to the system. The trolley assist system typically consists of an

electric substation connected to a high voltage cable strung along a semi-permanent haul route. Mine

haul trucks must have a pantograph and control system installed to facilitate connection to the trolley

cable.

Trolley assist systems provide benefits to conventional diesel-powered operations by reducing engine

duty cycle and therefore diesel consumption which may be advantageous in regions where diesel supply

is limited. In most regions, GHG emissions from electrical generation are of lower intensity than that of

diesel combustion, leading to an overall reduction to GHG emissions. However, this is highly dependent

on the method of electrical generation as GHG intensity between coal, natural gas, and renewable

electrical generation may significantly alter the results of analysis.


Using the base case haul strings and material balance as a basis, opportunities for trolley assist systems

was assessed based on haul road lifespan and extent of use. Typically, waste hauls primarily operate

along overburden benches that are part of the active mining face, and there is limited opportunity to install

a trolley assist system. Pit floor access ramps, such as ore haul ramps, are the primary candidate as they

are typically long term roads that are used consistently throughout their lifespan.

Specific haul segments that were candidates for a trolley assist system were identified for each haul

system. The base case engine duty cycle was reduced to idle along these segments, and the segment

cycle time was reduced to account for an estimated 40% increase in loaded uphill speed as per

discussions with suppliers. Diesel consumption for each segment was recalculated and electrical usage

was estimated by assuming an energy consumption equal to the gross engine power over the segment

time connected to the trolley system.

Truck hours, diesel and electricity consumption, GHG emissions, and costs were then re-estimated using

the same logic as utilized in the base case. Infrastructure cost was estimated based on the active trolley

system in each year and required truck infrastructure for truck fleets assigned to the trolley assist haul

systems.


Trolley Assist Case


4.3 ASSUMPTIONS


The majority of assumptions apply from the base case. Truck productivities on the haul segments where

trolley assist was installed were increased to account for the 40% increase in truck speed. Power

consumption while on the trolley system was estimated to be equal to the gross output power of a CAT

797 engine, or 2,983 KW.

The Siemens E-House 11 MW substation was understood to be the most powerful system available at

the time of the Study. The substation is capable of powering between one and four haul trucks over a

maximum trolley length of 850 m, the maximum time the trolley system is capable of powering a given

number of trucks is shown in Table 4.1.

Table 4.1 Substation Operating Time per Number of Simultaneous Trucks

Simultaneous Trucks Operating Time

1-2 Continuously

3 10 minutes

4 1 minute


Additional cost assumptions in the trolley assist case primarily consist of the cost to purchase and install

the required mine site and haul truck infrastructure. Quotes were provided by a supplier familiar with the

system. Infrastructure costs are defined in Table 4.2. Due to cable expansion and contraction due to heat

and cable wear, it was assumed that cable could not be reused following trolley system decommissioning.

However, it was assumed that the substations could be reused, at an estimated 40% of the cost of a new

substations, accounting for pad prep, equipment moves, and rehabilitation and maintenance of the unit.

Table 4.2 Trolley Assist System Infrastructure Costs

Infrastructure Component Cost (C$)

Cable Length / Substation 850 m

Cable Cost 1,600,000

Cable Reuse None

Substation Cost 3,500,000

Substation Relocation Cost 1,400,000

Truck Pantograph Cost 54,000

Truck Controls Cost 380,000

Due to the reduced duty cycle on engine components and the theoretical improvement in road

maintenance required to operate a trolley assist system, it was assumed that maintenance costs would

decrease from the base case. A 10% reduction in parts and maintenance labour per net operating hour

was estimated as shown in Table 4.3.


Trolley Assist Case


Table 4.3 Trolley Assist Ultra Class Truck Operating Cost


Parts 315.00

Lube 30.00

Tires 90.00

Maintenance Labour 195.18

Operator Labour 86.70

Total 716.88


Diesel combustion emissions are considered the same as the base case. Electrical generation emissions

are estimated from the Carbon Offset Emission Factors Handbook published by the Alberta Government

in March 2015 as shown in Table 4.4. The Alberta electrical grid still consists of significant coal fired

generation; as a sensitivity, the GHG emissions related to a site-based co-generation system have been

calculated based on a GHG intensity factor of 0.100 x 10-3 t/KWh as provided by the COSIA group.

4.4 Trolley Assist Case GHG Emission Assumptions

Energy Type CO2eq Emissions

Diesel 2.786 x 10-3 t/L

Electricity AB Average 0.640 x 10-3 t/KWh

Electricity Co-Gen 0.100 x 10-3 t/KWh

4.4 PRELIMINARY TROLLEY SYSTEM ANALYSIS

A high-level analysis of the haulage routes was completed to identify routes which provide the highest

benefit to GHG emissions and system cost. This analysis assessed each trolley system independently,

assuming the full capital cost for substations and cable for each system. Equipment capital cost was not

considered as this was understood to be relatively insignificant and applied to all systems throughout the

mine life. As shown in Table 4.5, typically, long term ore hauls along pit access ramps provide the highest

return on investment. Waste hauls such as trolley systems 2, 4, 5, 11, and 12 are often found on

overburden benches requiring limited uphill haulage and waste is assigned to several disposal areas

reducing the overall usage of any given haul system resulting in near break even or negative returns. Flat

hauls such as trolley systems 7, 9, and 14 can provide significant benefits if the total utilization of the

system is high enough over an extended lifetime. All trolley systems with any incremental savings

compared to the base case were selected for the LOM analysis as the primary focus of the scenario is to

reduce GHG emissions. The relationship between trolley length and cost savings, by type of haul is

shown on Figure 4-4.


Trolley Assist Case


Table 4.5 Trolley System Benefit Analysis Summary

Trolley System

ID Material Type

First Year of Operation

LifeSpan (Years)

Length (Km)

Incr Savings to Base Case ($M)

Incr Emissions (CO2eq kt)

1 Ore Ramp 1 20 1.3 $ 65.9 -97

2 Waste Ramp 6 2 0.7 $ (4.0) -1

3 Ore Ramp 8 4 1.8 $ 41.5 -71

4 Waste Ramp 11 3 0.7 $ 3.0 -10

5 Waste Ramp 11 3 0.9 $ 1.3 -13

6 Ore Ramp 12 9 1.8 $ 90.9 -135

7 Ore Flat 15 4 3.1 $ 18.3 -45

8 Ore Ramp 21 12 1.3 $ 100.3 -142

9 Ore Flat 21 20 2.8 $ 115.2 -155

10 Ore Ramp 23 10 0.7 $ 42.0 -60

11 Waste Ramp 25 5 1.2 $ (1.4) -10

12 Waste Flat 25 5 1.6 $ (5.1) -4

13 Ore Ramp 32 9 2.1 $ 110.0 -161

14 Ore Flat 32 9 2.2 $ 42.6 -73

15 Ore Ramp 38 3 0.5 $ 6.4 -14

Figure 4-1 Relationship Between Trolley System Length and Cost Savings by Road Type


Trolley Assist Case


4.5 TRUCK HOURS

Truck hours are largely comparable to the base case, the 40% increase in truck speed when on trolley

assist segments resulted in a decrease of overall truck hours by 3.5%. Over the life of mine, seven fewer

mine haul trucks are required to meet the total material movement. Total fleet truck hours are shown on

Figure 4-2. Appendix A shows the annual mine status maps with the trolley assist systems in place.

Figure 4-2 Trolley Assist Case Truck Hours


The main expenses involved in a trolley assist system are the infrastructure components including the

substation, cable, truck pantographs, and the electricity required to operate the trucks when attached to

the system. The cost of these components is offset by the reduced diesel consumption, reduced

operating cost per operating hour, and reduced fleet truck hours requiring less trucks overall.


In general, the majority of the site infrastructure required for trolley assist systems would already exist in

an operating oil sands mine. Additional infrastructure consists of substations and the overhead DC

catenary system along the selected haul route. As discussed above, the Siemens 11MW substation was

selected as Siemens is currently believed to be one of the industry leaders in trolley assist technology.


Trolley Assist Case



Capital costs for the trolley assist infrastructure were estimated based on the mine development.

Substations were purchased in the year required or reused if decommissioned in the previous year. It was

assumed that no reuse of the poles or cable is possible based on discussions with the provider. It is

believed that cable reuse is challenging due to cable wear and effects of repetitive expansion and

contraction resulting from cable heat. Life of mine infrastructure capital costs are shown in Table 4.6.

Table 4.6 Trolley Assist Case Site Infrastructure Capital Costs

Expense Unit Cost (C$M) Cost (C$M)

Cable Installation 1.6 / km 30.5

Substation Purchase 3.5 45.5

Substation Relocation 1.4 22.4

Total 98.4


Incremental site operating expenses were not calculated. It was assumed the existing line crews on site

have the capability to maintain the equipment.

4.6.2 Equipment

Equipment costs are dominated by the truck purchase cost and operating cost. Pantographs and control

systems were assumed to be installed as required, and energy costs recalculated based on diesel and

electricity consumption.


The trolley assist system was assumed to be active beginning in the first year of production throughout

the entire mine life. Capital costs were assumed to occur in the year required with no lead time. As costs

are undiscounted, this has limited impact on the Study.

Overall, fewer trucks were required to be purchased over the LOM as total fleet truck hours were reduced

due to increased travel speeds on the trolley segments. Pantographs and control systems were installed

on the number of trucks required to operate on the trolley assist haul systems. Trucks were retrofitted with

the trolley assist equipment as required based on the annual truck requirements and replacement

schedules. This may provide a slightly conservative estimate as equipment optimization may ensure

trolley assist equipment is not installed on a truck nearing its lifetime hours. However, the pantographs

and control systems were assumed to have the same replacement schedule as the haul trucks

themselves. Equipment was not reused on a replacement truck nor were the pantographs assumed to

require replacement either due to limited life expectancy or anticipated damage. The assumptions may be

refined with further investigation; however, the total cost of the pantographs and control systems is

estimated to be less than 5% of the total life of mine CAPEX and adjustments to these assumptions


Trolley Assist Case


would not be expected to impact the findings of the Study. The equipment capital cost components over

the LOM are shown in Table 4.7.

Table 4.7 Trolley Assist Case Equipment Capital Costs

Expense Cost (C$M)

Truck Purchases 1,386.9

Pantographs and Controls 76.4

Total 1,463.3


Operating cost includes operator and maintenance labour, parts, tires, and lube applied per net operating

hour plus the fuel and energy costs required for truck operation. Total OpEx over the 40-year mine life is

estimated to be $15,059M.

4.6.3 Trolley Assist Case Cost Summary

Total LOM costs for the trolley assist case were estimated at $17,279M as compared to $19,477M in the

base case, an 11% decrease. Diesel consumption was reduced by 21% or 1.25 billion litres of fuel. Truck

operating costs not including fuel made up a comparable 64% of total LOM costs. The total cost of the

trolley system equipment including substations, cable and poles, and truck equipment only account for

1.1% of the total LOM cost as shown in Table 4.8. A timeline of costs over the LOM is shown on Figure 4-

3.

Table 4.8 Trolley Assist Case LOM Cost Summary

Costs Total Cost (C$M) Unit Cost (C$/BCM)


Trolley CAPEX 175 0.03


Diesel 4,254 0.73

Power 196 0.03

Carbon Tax 658 0.11

Total 17,279 2.97


Trolley Assist Case


Figure 4-3 Trolley Assist Case Cost Timeline


As in the base case, greenhouse gas emissions are estimated for the energy consumed by the truck fleet

only. Emissions from other parts of the operation such as other mobile equipment and processing are

assumed to be constant between all cases and were not considered. GHG emissions were the product of

diesel combustion and energy consumption. The total GHG emissions over the LOM was estimated to be

15.7 Mt CO2eq using the Alberta average GHG intensity for electrical generation and 13.6 Mt using a co-

gen power source with diesel emissions making up 84% and 97% of emissions, respectively. The annual

emissions from the mine haul fleet are shown on Figure 4-4.

Annual emissions decreased by between 3% and 8% using the Alberta average GHG intensity for

electrical generation and 9% to 25% using a co-gen electrical generating system. Annual GHG reduction

due to trolley assist systems vary depending on several compounding factors. As shown on Figure 4-4,

annual GHG emissions vary considerably between certain years. This is due to variances in total truck

hours either based on total material moved or the average haul profile based on mine development and

mine waste placement locations. Fleet emissions are a function of the total fleet hours and the average

engine duty cycle; again, a factor of the average haul profile. In years where the mine waste haul diesel

consumption makes up a smaller proportion of the total fleet consumption, trolley assist systems have a

larger impact on fleet emissions. This is seen in years 1 through 3 where mine waste is hauled to nearby

ex-pit dumps and when in-pit waste disposal is possible avoiding large elevation changes utilizing top


Trolley Assist Case


waste bench pit wall roads throughout the mine life. Larger incremental impacts to the fleet GHG

emissions are also realized when the waste destinations allow for utilization of the trolley assist system as

seen in years 23 and 24. Similarly, decreased impacts to GHG emissions are seen in years where the

haul profile results increased engine duty cycles where the diesel savings are proportionally smaller. This

is seen most evidently in years 19 and 20 where total diesel consumption increased by up to 25% of

preceding years due to changes in the mine waste haul profile.

Figure 4-4 Trolley Assist Case GHG Emissions Timeline

4.8 CONCLUSIONS REGARDING THE TROLLEY ASSIST CASE

Trolley assist systems provide significant benefit by reducing diesel demand and can provide net benefits

to GHG emissions and mine operating costs if deployed where most effective. Trolley assist systems are

currently deployed in several mines globally, these mines often have further benefits as the diesel fuel

supply may be limited or more cost intensive than in the Canadian oil sands.

Challenges of successful deployment of a trolley assist system in the oil sands include:

• Weather - icing of cables and pantographs resulting in reduced efficiency or increased

maintenance of the system

• Poor road conditions – limited tolerance vertically and horizontally along the trolley system to

maintain connection may be a challenge to successful implementation of a trolley assist system

due to the soft ground conditions found in the oil sands. Increased road maintenance may be

required to maintain the haul road within tolerance of the overhead trolley infrastructure. A cost

for increased road maintained was not estimated


Trolley Assist Case


GHG emissions are reduced by utilizing the trolley assist technology over the life of mine. This analysis

was completed using an Alberta average GHG intensity for electricity generation of 640 g/KWh and a co-

gen GHG intensity factor of 100 g/KWh. The Alberta electricity generation consists of a variety of

technologies including coal, natural gas, and renewable sources. As Alberta transitions towards greener

electricity generation, the GHG intensity would be expected to decrease resulting in further GHG

emissions reduction.

As discussed above, the substations are capable of powering a limited number of trucks attached to the

trolley system simultaneously. Oil sands mines typically have larger truck fleets and it was necessary to

estimate the average number of trucks per trolley system to assess if this may cause a limitation to the

implementation of trolley assist technology. However, as shown on Figure 4-5, the average trucks along a

single 850m length of trolley system in any period rarely exceeds two trucks, which the Siemens 11 MW

system can power indefinitely. Additionally, the average time spent attached to a trolley system is 2.2

minutes limiting the likelihood of exceeding the peak usage times. No consideration has been given for

haul congestion or truck bunching due to operational inefficiencies.

Figure 4-5 Average Trucks per Trolley Assist Substation

Trolley assist technology is proven in the full-scale mining environment and may provide significant

benefits to oil sands mine operators through both cost and GHG emissions.


LNG Substitution Case


5.0 LNG SUBSTITUTION CASE

LNG substitution technology allows a diesel combustion engine to use LNG as an alternative fuel source,

often at a lower unit cost.


A review of both previous studies mentioned above, and current industry literature, point to LNG engine

technologies with varying engine architectures, diesel substitution rates, projected rates of methane slip,

and timelines to full commercial readiness at the ultra-class scale. Stantec has applied LNG substitution

factors of 50% and 90% for the purposes of examining the cost and GHG reduction impacts of

incorporating LNG engine technology in oil sands ore and waste haulage fleets.


The base case was used as the basis for this analysis. Diesel consumption was reduced by the

substitution factors of 50% and 90% and LNG use was estimated based on the heating value ratio of

1.68:1.

Annual LNG usage was used to calculate a daily demand that was the basis for site infrastructure sizing.

GHG emissions were then recalculated and a CapEx and OpEx estimate was completed.

5.3 ASSUMPTIONS

GFS Corporation provided support through discussions and conceptual costing data related to their

fumigated LNG technology. Stantec was unable to engage either Caterpillar or Westport in relation to

their HPDI technology for Ultra Class haul fleets.


The primary assumptions for the LNG substitution cases are the substitution rates themselves.

Substitutions rates vary significantly based on the selected technology and the ability to scale the

technology to a commercial mining operation. For the basis of the Study a 50% substitution rate was

assumed for fumigated LNG technology and 90% substitution for a direct injection (HPDI) system. Diesel

consumption was reduced by the substitution factor and replaced by LNG at an equivalency factor of

1.68:1 based on the lower heating value of LNG when compared to diesel fuel.

LNG site infrastructure is based on the total annual LNG demand for each case. LNG storage facilities

were sized to maintain a minimum of 2 days of LNG capacity. In practice, actual LNG storage size would

be based on the supply system and risk tolerance of the operation.




Fumigated LNG technology has been tested and implemented at mining operations with substitution rates

typically in the 35%-50% range. Direct injection technology is still in development and assumptions from

the fumigated case were used to close any data gaps, primarily for costing purposes.

It was assumed that no performance reduction results from LNG substitution.


GHG emissions for LNG is based on the GHG Emissions from natural gas combustion found in the

Carbon Offset Emission Factors Handbook published by the Alberta Government in March 2015. Diesel

and electricity emissions are based on the same source and are consistent with the other cases, co-gen

power emissions have also been estimated for comparative purposes. GHG emission intensity factors are

shown in Table 5.1.

Table 5.1 LNG Substitution Case GHG Emission Assumptions

Energy Type CO2eq Emissions

Diesel 2.786 x 10^-3 t/L

Electricity AB Average 0.640 x 10-3 t/KWh

Electricity Co-Gen 0.100 x 10-3 t/KWh

LNG 1.192 x 10-3 t/L

LNG combustion is less GHG intensive than conventional diesel combustion; however, fugitive emissions

resulting from the evaporation of methane during the storage and transportation of LNG can offset the

lower GHG intensity from LNG combustion. An estimate of fugitive emissions (i.e. methane slip) per unit

combusted for each of the two substitution technologies is shown in Table 5.2.

Table 5.2 LNG Fugitive Emissions Assumptions

Fumigated 50% Direct Injection HPDI

Fugitive Emissions 4.00% 0.75%

5.4 TRUCK HOURS

Truck hours are assumed to be unchanged from the base case.



The site infrastructure required to support an LNG ultra-class haulage fleet includes an LNG production

plant, LNG storage facilities, LNG fueling depot(s), and mobile LNG refueling equipment. Stantec has

assumed that the infrastructure required to deliver and store natural gas to the virtual mine would be

included in the base case and therefore has not been considered as an additional cost for the LNG

substitution cases.





Stantec estimated the capital and operating costs associated with the required LNG site infrastructure

based on information provided by Plum Energy and Chart Industries.

Two LNG production modules, each with a daily production capacity of 100,000 gallons (~380,000 litres),

will be required for both substitution cases. LNG storage units with capacities of 100,000 gallons

(~380,000 litres) and 50,000 gallons (~190,000 litres) have been utilized. Stantec has incorporated a 2-

day storage requirement in the planning assumptions. As such the 50% substitution case will require

200,000 gallons of storage over the life of mine plan while the 90% substitution case will require 250,000

gallons.

The infrastructure assumptions have also included the requirements for two 8-bay LNG/diesel

combination fuel depots and two LNG mobile fuel trucks.

Capital cost for site infrastructure for the two cases is shown in Table 5.3.

Table 5.3 LNG Substitution Case Infrastructure Capital Cost Estimate

Capital Infrastructure LNG 50% (C$M) LNG 90% (C$M)

Truck Outfitting 110.4 110.4

LNG Plant 67.2 67.2

LNG Fuel Storage 2.8 3.5

8-Bay LNG Fuel Depot 4.0 4.0

LNG Mobile Fuel Truck 0.7 0.7

Total 185.1 185.8


Operating expenses include natural gas supply, LNG plant and fuel depot electrical power consumption,

annual maintenance costs, and operating labour. Total operating cost over the LOM is shown in Table

5.4.

Table 5.4 LNG Substitution Case Infrastructure Operating Cost Estimate

Operating Cost Fumigated 50% (C$M) Direct Injection HPDI (C$M)

LNG Plant Maintenance Cost 45.7 50.4

LNG Fuel Depot and Storage Maintenance Cost 5.0 5.2

Labour Cost 57.5 57.5

Power 73.2 80.3

Total 181.5 193.4




5.5.2 Equipment

GFS Corp. provided support through discussions and conceptual costing data related to their fumigated

LNG technology. It was assumed that all mine haul trucks would be equipped with the LNG equipment

when commissioned.


As the technology does not currently exist for Ultra Class 400t haulage fleets, GFS Corp. assisted

Stantec with estimating costs of outfitting the trucks with LNG equipment at $516,000.

Total cost for outfitting trucks with the required equipment was $110.4 M in both cases. Stantec was not

able to attain an estimate from a supplier for the HPDI case; therefore truck equipment capital costs were

assumed to be the same as the cost for a fumigated system.


Operating costs include operator and maintenance labour, parts, tires, and lube applied per net operating

hour plus the fuel and energy costs required for truck operation. Aside from the fuel and energy costs,

Stantec has assumed that the remainder of the operating costs are equivalent to the base case haulage

estimate.

Total OpEx over the 40-year mine life for both cases is shown in Table 5.5.

Table 5.5 LNG Substitution Case Equipment Operating Cost Estimate

Fumigated 50% Direct Injection HPDI 90%

Consumables

Diesel (L) 2,988 598

LNG (L) 5,020 9,036

Operating Cost

Diesel ($M) 2,689 538

LNG ($M) 251 452

Operating Cost ($M) 11,854 11,854

Total ($M) 14,795 12,844

5.5.3 LNG Substitution Case Cost Summary

Total LOM costs for the LNG substitution cases were estimated at $17,401M and $15,305M for the 50%

and 90% substitution rates, respectively, as compared to $19,477M in the base case. This represents an

11% and 21% reduction in total costs for the 50% and 90% substitution rates, respectively. Fuel costs

are reduced from 29% of the base case total costs to 18% in the 50% substitution case down to 6% of

total costs for the 90% substitution case. Infrastructure costs are estimated to be just over 1% of total




LOM costs in both cases. A timeline of costs over the LOM are shown on Figure 5-1 and Figure 5-2 for

the 50% substitution case and 90% substitution case, respectively.

Figure 5-1 50% LNG Substitution Case Cost Timeline

Figure 5-2 90% LNG Substitution Case Cost Timeline





GHG emissions are based on the diesel and LNG use for the mine truck operating fleet, the power

required to operate the additional site infrastructure, and the fugitive emissions for each technology. For

the 50% Substitution Case, the reduction in GHG emissions from LNG combustion is more than offset by

the fugitive emissions due to the high rate of methane slip of 4% associated with the fumigated

technology. This results in a net increase of CO2eq emissions by over 4% when compared to the base

case. Due to the lower rate of fugitive emissions in the HPDI technology, the 90% substitution case

benefits from the lower GHG intensity of LNG combustion and therefore results in a 15% reduction in

CO2eq emissions over the LOM as shown in Table 5.6. If the LNG technologies continue to develop and

reduces or eliminates fugitive emissions, Figure 5-3 shows that both cases would result in significant

reductions in mine fleet GHG emissions.

Table 5.6 LNG Substitution Case GHG Emissions

Fumigated 50%

(Mt CO2eq) Direct Injection HPDI 90%

(MT CO2eq)

Diesel 8.3 1.7

LNG 6.0 10.8

Power 0.9 1.0

Fugitive Emissions 2.1 0.7

Total 17.4 14.2

Figure 5-3 LNG Substitution Case GHG Emissions Timeline




5.7 CONCLUSIONS REGARDING THE LNG SUBSTITUTION CASE

LNG substitution technology is currently deployed at varying substitution rates throughout the mining

industry. Cost reduction is possible due to the low cost of natural gas in Alberta; however, GHG emission

reductions may only be realized if the technology development limits or eliminates the impacts of fugitive

emissions. Site infrastructure and equipment would be similar to existing operations; however, this would

introduce another plant and storage site to the operation.

As Stantec was unable to attain specific data from suppliers, further discussions with manufacturers

would be required to assess the development and deployment costs of direct injection technology.


Rear Dump Trailer Case


6.0 REAR DUMP TRAILER CASE


Tractor trailer arrangements are typically used in the coal mining industry with articulating bottom dump or

rear dump trailers. The trailer usually has a larger payload than the equivalent conventional rear dump

truck due a change in load dynamics primarily due to the additional axle. Material is loaded, hauled, and

dumped in a similar way as the base case; however, a similar ultra-class payload can be achieved with a

smaller haul truck. The rear dump trailer utilizes large hydraulic rams connected to the front of the trailer

to lift the box, as shown on Figure 6-1.

Figure 6-1 Rear Dump Trailer


For the purposes of the Study, Stantec discussed the rear dump trailer technology with a supplier that

currently provides smaller models to the mining industry. A theoretical truck was assumed to have ultra

class payload capacity while using a smaller mining truck for propulsion. Simulations of truck travel times

for this theoretical configuration were calculated in Runge’s Talpac software. It was expected that the

additional payload would lead to increased travel times where the trucks were limited to rimpull such as

on long up-grades and along ore benches which have higher rolling resistances. Travel times combined

with fixed times were used to generate cycle times and truck hours. The same process was followed as

the base case to estimate cost and GHG emissions.




6.3 ASSUMPTIONS

A rear dump trailer at ultra-class scale has not been developed or designed; therefore, most assumptions

were based on professional judgement and scaled up from relevant existing data. This analysis should be

considered as high-level and further discussions and trials with manufacturers would be required to

increase confidence in the estimates provided.


Rear dump trailers typically have a payload capacity equal to 1.6 to 1.7 times that of the equivalent rear

dump haul truck. Initially, the Study considered the use of an ultra-class truck with a rear dump trailer with

a capacity of up to 640 short tons, however, following discussions with a manufacturer of smaller rear

dump trailers, concerns regarding trailer stability and the ability to successfully scale up the hydraulic

rams to this size it was decided to assume equivalent ultra-class payload of 400 short tons using a

smaller mining truck as the tractor unit. A 400 short ton trailer payload was estimated to be equivalent to a

250 short ton mining truck, therefore, the CAT 793F was selected as the tractor unit.

The theoretical 793F tractor trailer unit was set up in Talpac software for haul simulations using the same

haul systems as in the base case. The Talpac equipment database was used to identify a rear dump and

tractor trailer example to be the basis the theoretical truck. The example identified was the relationship

between the CAT 767C bottom dump trailer and the CAT 777C rear dump haul truck. The necessary

inputs into the Talpac software include empty and full weight axle weight distribution. Empty truck weight

was estimated based on the incremental empty truck weight of the 767C per kg of payload increase when

compared to the 777C. Using this ratio of 0.52kg incremental trailer weight per kg of increased payload,

an empty truck weight of 234,093 kg was used to set up the truck. Axle weight distributions were

assumed be the same as the 767C. The Talpac 793F rear dump trailer truck was given the properties

shown in Table 6.1.

Table 6.1 Theoretical 793F Rear Dump Trailer Configuration

Axle Full

Distribution Empty

Distribution Full Weight Empty Weight Payload

1 17% 30% 102,708 70,254 32,454

2 39% 37% 229,897 87,752 142,145

3 44% 33% 264,488 76,087 188,401

Total 100% 100% 597,093 234,093 363,000

793F fuel consumption was based on the same methodology as the base case 797F, where the

relationship between duty cycle and fuel consumption in the CAT Handbook was used to develop a

formula for fuel consumption. 793F fuel consumption is assumed to be approximately 66% of that of a

797F at 100% duty cycle as shown in Table 6.2.




Table 6.2 793F Fuel Consumption

Based on CAT handbook values, plotted linear fuel consumption for line of best fit

Truck Duty Cycle Fuel Consumption

793F

15* 95

25* 143

35* 190

45* 238

55** 285

65** 333

75** 380

85** 428

95** 475

100** 499

10 71

* From CAT Handbook 47

** Calculated based on formula

Due to the inefficient nature of operating and maneuvering a truck and trailer when compared to a

convention rear dump box, and the extended hydraulic rams required to lift the trailer to height, certain

fixed time haul components have been increased as shown in Table 6.3.

Table 6.3 Rear Dump Trailer Fixed Cycle Times

Segment Segment Time

(Rear Dump Truck) Segment Time

(Rear Dump Trailer)

Spot @ Shovel 0.5 1.0*

Spot @ Dump 0.5 1.0*

Load 2.0 2.0

Dump 1.3 2.6*

Queue Total 2.0 2.0

Total Fixed Cycle Time 6.3 8.6

*Increased by a factor of 2 to account for trailer inefficiency

y = 4.753x + 23.685R² = 1

0

50

100

150

200

250

0* 10* 20* 30* 40* 50*





Truck purchase price and trailer incremental cost were estimated as proportional to the ultra-class base

case costs. As shown in Table 6.4, the total cost for the unit is $5.7M compared to the ultra-class truck

purchase price of $6.7M.

Table 6.4 250t Haul Truck and 400t Trailer Capital Cost

Component Purchase Price

250t Truck $ 4,400,000

400t Trailer (Incremental) $ 1,300,000

Total $ 5,700,000

Operating costs include operator and maintenance labour, parts, lube, and tires. Hourly rates for parts

and maintenance labour were ratioed to 80% of those for an ultra class truck based on the ratio of

payload for the rear dump trucks (62.5%) plus 25% for maintenance of the trailer system. As shown in

Table 6.5, operating costs per net operating hour are estimated to be $660/NOH compared to $716/NOH

for the ultra-class trucks

Table 6.5 Rear Dump Trailer Operating Costs


Parts $ 280.00

Lube $ 30.00

Tires $ 90.00

Maint Labour $ 173.50

Operator Labour $ 86.70

Total $ 660.20

Trucks were assumed to have a similar operating life of 70,000 hours extending to 100,000 hours within

the last 5 years of mine life as in the base case. Road construction costs were assumed to be

comparable to the Base Case; however, road running width and berm heights may be reduced if these

trucks were the largest trucks used at the operation.


Emissions assumptions for diesel combustion are consistent with those used in the previous sections.

6.4 TRUCK HOURS

Due to the increased payload and load on the truck engines, travel times along segments with

acceleration or uphill grades increased significantly. Overall, cycle times increased by an average of 24%

when compared to the cycle times of the ultra-class truck as shown on Figure 6-2.




Figure 6-2 Average Cycle Time Comparison

As a result of the increased travel times and fixed times as discussed above, total fleet truck hours over

the LOM increased by 24%, or an average of 18 trucks as can be seen on Figure 6-3.

Figure 6-3 Rear Dump Trailer Case Truck Hours





Capital and operating costs have been estimated consistently with the base case.


No additional site infrastructure is required compared to the base case.





6.5.2 Equipment

The reduced equipment CapEx and OpEx costs are cancelled out by the increased truck hours due to

increased cycle times resulting in higher equipment costs overall.


An average of 80 trucks are required compared to the base case of 62. Total truck CapEx is estimated to

be $1,516M compared to $1,434M in the base case, an increase of 6%.


Despite the decreased operating cost per hour, the increased truck hours result in total operating costs of

$17,869M including fuel, an increase of over 3% to the base case.

6.5.3 Rear Dump Trailer Cost Summary

Total costs over the LOM increased nearly 4% from the base case due to the increased truck hours. No

consideration was given to potential congestion or increased infrastructure required to maintain and

support the additional truck fleet which would further inflate costs. The LOM cost estimate is shown in

Table 6.6 with the cost timeline shown on Figure 6-4.

Table 6.6 Rear Dump Trailer LOM Costs

Costs Total Cost ($M) Unit Cost ($/BCM)



Diesel 5,279 0.91

Carbon Tax 795 0.14

Total 20,181 3.47




Figure 6-4 Rear Dump Trailer Case Cost Timeline


Like the Base Case, GHG Emissions are based solely on the combustion of diesel fuel for the haul truck

fleet. Due to the decreased fuel consumption of the 793F engine, total diesel usage is comparable to the

base case despite a 24% increase in total fleet truck hours. GHG emissions for the LOM of the rear dump

trailer case are estimated to be 16.3Mt, a timeline is shown on Figure 6-5.




Figure 6-5 Rear Dump Trailer Case Emissions Timeline

6.7 CONCLUSIONS REGARDING THE REAR DUMP TRAILER CASE

Rear dump trailers are an effective way of increasing the payload capacity of an equivalent rear dump

truck. This technology has been implemented in mining operations elsewhere, typically in flat lying

thermal coal deposits. The increased payload leads to increased cycle times where significant change in

elevation is encountered as the truck speed is limited by the engine duty cycle. Therefore, these trucks

are more effective on longer hauls along top waste benches than on hauls that must climb from pit

bottom. It may be beneficial to assess the implementation of the rear dump trailer technology restricted to

top waste bench mining which avoid larger elevation changes.

Rear dump trailers have been developed at a smaller scale; however, no operational examples have

been developed at the ultra-class payload scale. Concerns regarding trailer stability, ease of operations,

efficiency for loading at the face, and mechanical limitations of the lifting hydraulics remain. This case was

assessed primarily on assumptions that were scaled from the base case and therefore the level of

accuracy should be considered lower than that of the base case.


Comparison of Cases


7.0 COMPARISON OF CASES

All cases may be directly compared based on CapEx, OpEx, and GHG Emissions. However, the current

level of development and therefore accuracy of analysis varies between the technologies. All other costs

and factors related to the operations is assumed to be consistent throughout the cases.

7.1 CAPTAL AND OPERATING COSTS

Capital and operating costs between the cases vary with the technology, primarily due to fuel costs. Truck

CapEx and OpEx are decreased in the trolley assist case due to the increased ramp speeds resulting in

decreased overall truck hours and assumed maintenance benefits of improved road conditions. The

opposite is true for the rear dump trailer case as cycle times increased due to the additional payload

resulting in a 24% increase to truck hours resulting in an overall cost increase of 4%. The LNG

substitution cases assume equivalent truck hours and truck CapEx and OpEx as the base case and only

differentiated on cost of fuel and LNG infrastructure. Both cases resulted in decreased cost due to the low

natural gas prices, resulting in a total decrease in LOM costs of up to $4 billion in the 90% direct injection

case. A detailed comparison of CapEx and OpEx costs between the cases is shown on Table 7.1 and

Figure 7-1.


Comparison of Cases


Table 7.1 LOM CapEx and OpEx Cost Summary

Base Case Trolley Assist Rear Dump

Trailer LNG 50% LNG 90%

Costs ($M)

Truck CAPEX 1,434 1,387 1,516 1,434 1,434

LNG CAPEX - - - 185.1 185.8

Trolley CAPEX - 175 - - -

Truck OPEX 11,854 10,609 12,590 11,854 11,854

LNG OPEX - - - 108 113

Diesel 5,379 4,254 5,279 2,689 538

Power - 196 - 73 80

LNG - - - 251 452

Carbon Tax 811 658 795 806 648

Total 19,477 17,279 20,181 17,401 15,305

Unit Cost ($/BCM)

Truck CAPEX 0.25 0.24 0.26 0.25 0.25

LNG CAPEX - - - 0.03 0.03

Trolley CAPEX - 0.03 - - -

Truck OPEX 2.04 1.83 2.17 2.04 2.04

LNG OPEX - - - 0.02 0.02

Diesel 0.93 0.73 0.91 0.46 0.09

Power - 0.03 - 0.01 0.01

LNG - - - 0.04 0.08

Carbon Tax 0.14 0.11 0.14 0.14 0.11

Total 3.35 2.97 3.47 2.99 2.63


Comparison of Cases


Figure 7-1 Comparison of CapEx and OpEx Costs


Alternative energy sources for the mine truck fleet result in decreased GHG emission intensity. The trolley

assist case uses power from the electrical grid to reduce the engine duty cycle along trolley segments

from 100% down to idle or around 10%. Emissions related to electricity generation in Alberta still include

coal power plants and therefore the GHG intensity from the electricity usage may be reduced if alternative

or renewable sources are used for electricity generation; therefore, an alternate case assuming co-

generation power is included in the analysis. With that considered, the trolley assist Case still results in

decreased emissions of 5.5% and 18% for the Alberta average and co-gen generation GHG intensities,

respectively.

The rear dump trailer case did result in increased truck hours, however, the reduced fuel consumption of

the 793F engine counterbalances the increased hours. Diesel consumption and therefore GHG emissions

are comparable to the base case and due to the level of accuracy with this scenario, should be

considered equivalent.

LNG combustion does result in lower GHG emissions and intensity; however, fugitive emissions during

the transport and injection of the fuel into the engine may offset any gains. As shown in the LNG 50%

Substitution Case where fugitive emissions were estimated to be 4%, the impact of fugitive emissions

eliminate any potential gains from the combustion of natural gas and increased overall emissions by over

4%. However, the improved direct injection technology of the LNG 90% substitution case may result in

fugitive emissions of approximately 0.75% resulting in a net decrease of GHG emissions of 15% when

compared to the base case. Direct injection technology is currently being developed by a number of

manufacturers; however, these manufacturers were not willing to share details of the technology with

Stantec at this time. As discussed in section 5.3, volumetrically, more LNG is consumed than the


Comparison of Cases


equivalent units of diesel based on the lower heating value at a ratio of 1.68:1. Electrical emissions

related to the operation of the on-site LNG plant due to were estimated and accounted for in the analysis.

A detailed comparison of GHG emissions between the cases is shown in Table 7.2.

Table 7.2 LOM Energy Consumption and GHG Emission Summary

Units Base Case Trolley Assist

Rear Dump Trailer LNG 50% LNG 90%

Energy Consumption

Diesel [Million L] 5,976 4,726 5,866 2,988 598

Power [Million KWh] - 3,916 - 1,465 1,606

LNG [Million L] - - - 5,020 9,036

GHG Emissions CO2e

Diesel [CO2eq Mt] 16.65 13.17 16.34 8.32 1.66

Electricity AB Avg (Co-Gen) [CO2eq Mt] -

2.5 (0.4) -

0.9 (0.1)

1 (0.2)

LNG [CO2eq Mt] - - - 5.98 10.77

Fugitive Emissions [CO2eq Mt] - - - 2.11 0.71

Total AB Avg (Co-Gen) [CO2eq Mt] 16.65 15.7 (13.6) 16.34 17.4 (16.6) 14.2 (13.3)

GHG Intensity

Diesel [Kg/bcm] 2.86 2.27 2.81 1.43 0.29

Electricity AB Avg (Co-Gen) [Kg/bcm] -

0.43 (0.07) -

0.16 (0.03)

0.18 (0.03)

LNG [Kg/bcm] - - - 1.03 1.85

Fugitive Emissions [Kg/bcm] - - - 0.36 0.12

Total AB Avg (Co-Gen) [Kg/bcm] 2.86

2.7 (2.33) 2.81

2.99 (2.85)

2.44 (2.29)

7.3 RISK ANALYSIS

Stantec prepared a risk analysis between the cases and reviewed this with the COSIA advisory group at

the May 30th review meeting. Risks were assessed in the following categories:

• Technology Development

• Operational Complexity

• Safety and Environmental

• Cost Estimate Certainty

• GHG Estimate Certainty


Comparison of Cases


Risk level was assessed from Low, which would be comparable to the base case (a technology that is

understood and implemented in the Canadian oil sands) through to high, where the risk of the

technologies successful deployment requires more development, results in increased EH&S risk, or

where the certainty of estimate was low due to the required level of assumptions. As shown, the LNG

90% Substitution Case received a high level of risk in all categories, this was primarily due to the level

and detail of the development of the technology provided to Stantec for this Study and may not fully

reflect the level of risk associated with the technology following a more in-depth analysis and discussions

with the manufacturers. A summary of the risk analysis is shown in Table 7.3.

Table 7.3 Risk Analysis Summary

Base Case 797F

Trolley Assist

Rear Dump Trailer

LNG 50%

LNG 90%

Technology Development

High Theoretical, not at scale

L M H M H Medium Demonstrated/Tested

Low Currently implemented in Oil Sands

Operational Complexity

High Complex additional facilities and development of new standard operating procedures (SOP’s)

L M M H H Medium Understood procedures, limited new resources or skills


Safety and Environmental Risk

High Significant changes to procedures, emergency response, high consequence to environment

L L L H H Medium Minor training and updates to existing procedures required

Low Current procedures, emergency response, and environmental response apply

Cost Estimate Certainty Risk

High Order of maginitude cost, based on assumptions

L L H M H Medium Estimates provided by supplier currently supplied


GHG Estimate Certainty Risk

High Theoretical

L L M H H Medium Demonstrated/Tested by supplier

Low Understood/calculable


Conclusions


8.0 CONCLUSIONS

8.1 BASE CASE

The base case hauls ore and waste using conventional ultra class mining trucks. Costs, productivities,

and GHG emissions are understood by operators in the Canadian oil sands; this was considered the

baseline for the Study.

8.2 TROLLEY ASSIST CASE

Trolley assist provides electric power directly to the wheel motors on a diesel-electric mining truck when

the truck connects to overhead cables. Significant infrastructure planning and cost is required to

implement a trolley assist system. As the truck is connected to the trolley assist system, the engine load

can be reduced to idle leading to fuel savings of up to 20%. Increased productivity due to increased

speeds along the trolley assist system and improved road maintenance may decrease overall LOM costs.

GHG emissions were shown to decrease by almost 6%, with further opportunity if electricity generation is

less GHG intensive than the Alberta average such as that of a co-generation plant resulting in an 18%

reduction in GHG emissions.

Trolley assist technology is well developed, implemented in the mining industry, and the technology itself

is of fairly low risk. Further analysis would be required regarding cost, infrastructure planning, and the

probability of success in the Canadian oil sands. Decreased diesel demand is often a benefit for mining

operations that have implemented a trolley assist system as these areas typically have supply

constraints. Soft ground conditions may make it difficult to maintain the roads within the tolerances

required to effectively operate a trolley assist system.

Trolley assist systems may benefit from an autonomous haul system as they would be expected to

operate within the horizontal tolerance better than human operated trucks. Road maintenance would

remain key to the success of the system as vertical tolerance is limited.

8.3 LNG DIESEL SUBSTITUTION CASE

LNG substitution provides an opportunity for mining operators to drastically lower their costs by using

natural gas supply lines to supply methane to an LNG plant. The cost of LNG is approximately 10% of the

cost of diesel, not including LNG plant CapEx and OpEx which are relatively small compared to the cost

of fuel.

Fumigated LNG technology with substitution rates of up to 50% is currently deployed in various stages

throughout the mining industry. The Study estimates that mining costs can be reduced by approximately

10% over the LOM. GHG emissions from LNG combustion is less intensive; however, fumigated

technology results in up to 4% fugitive emissions from the transportation, storage, and injection of LNG

resulting in a net increase to GHG emissions over the LOM.


Conclusions


Direct injection technology is still under development by a number of manufacturers and suppliers. This

technology allows substitution rates of up to 90%. At this substitution rate, LOM costs may decrease by

up to 20%; however, the cost estimate certainty remains low as Stantec was unable to receive support

from OEM’s on cost estimates. Fugitive emissions are reduced to just 0.75% resulting in significant GHG

emissions reductions, indicated as up to 15% by the Study.

Environmental, health, and safety risks to LNG substitution are understood to be higher than that of

conventional diesel fuel. Aside from fugitive emissions, fuel spills and damage to the LNG fuel and

storage tanks may result in serious hazards. LNG fuel will begin to evaporate when outside of the

containment tank and fumes are highly flammable increasing the risk of a fire or explosion. Methane

carries a global warming potential of 25 times that of carbon dioxide; therefore, evaporating methane from

a spill is more difficult to contain and more harmful to the environment than that of a diesel spill.

Operational complexities of constructing and operating an LNG plant will require additional footprint and

expertise on oil sands sites. This may be avoided if a regional LNG supplier was to be set up to provide

LNG to the mines.

Economics may be altered as demand for LNG and natural gas increase, replacing diesel as the primary

fuel source for the mining fleet. With decreased demand, if the price of LNG increases and the price of

diesel decreases, the economic benefit of the technology may be decreased.

LNG technology provides a variety of opportunities to reduce both cost and GHG footprint. Further

studies and investigations should be carried out; and, include discussions with suppliers and

manufacturers to understand the challenges, cost, and timelines related to the implementation of direct

injection systems.

8.4 REAR DUMP TRAILER

Rear dump trailers provide an opportunity to increase the payload of a mining haul truck by a factor of 1.6

to 1.7. While successfully utilized in flat lying coal deposits with longer hauls, site wide implementation of

the rear dump trailer haul technology was not beneficial in this Study, and increased costs by 4%.

Increased cycle times due to longer travel times along grades, during acceleration, and spot and dump

times increased LOM truck hours by 24%. Haul road congestion and decreased productivities may be

expected; however, they were not evaluated at this level of Study.

GHG Emissions were effectively the same as the base case as the decreased fuel consumption of the

smaller truck engines was completely offset by the increased fleet size and truck hours.

A rear dump trailer with ultra-class truck payloads does not currently exist, as far as Stantec’s high level

research indicated. Therefore, the cost, productivity, and GHG emissions estimates are based on a

variety of assumptions and therefore they should be assumed to carry a greater margin of error than the

base case. The viability of scaling this technology to ultra-class payloads remains unproven and further

investigation and trial would be required to assess further.


Conclusions


8.5 CONCLUSION

The Study evaluated alternative ore and waste haulage technologies related to haulage by mine trucks.

These technologies primarily focused on alternative energy sources whether that be electricity, LNG, or

increasing payload of a smaller, more efficient powertrain. Development of the technologies varies, which

impacted Stantec’s ability to attain operational data for this assessment. The Study indicates that further

assessment of trolley assist systems and LNG substitution using direct injection technology would be both

economically and environmentally beneficial.

As shown in Table 8.1, all cases resulted in a reduction in GHG emissions when compared to the base

case except for the LNG 50% substitution case when fugitive emissions were considered. As discussed,

further development of the fumigated technology limiting or eliminating fugitive emissions is

recommended. GHG emissions may be reduced by up to nearly 20% using the trolley assist or direct

injection LNG technologies coupled with co-gen electrical supply.

Table 8.1 GHG Emissions Summary



GHG Emissions CO2e

Diesel [CO2eq Mt] 16.6 13.2 16.3 8.3 1.7

Electricity AB Avg (Co-Gen) [CO2eq Mt] - 2.5 (0.4) - 0.9 (0.1) 1 (0.2)

LNG [CO2eq Mt] - - - 6.0 10.8

Fugitive Emissions [CO2eq Mt] - - - 2.1 0.7

Total AB Avg (Co-Gen) [CO2eq Mt] 16.6 15.7 (13.6) 16.3 17.4 (16.6) 14.2 (13.3)

GHG Intensity

Diesel [Kg/bcm] 2.86 2.27 2.81 1.43 0.29

Electricity AB Avg (Co-Gen) [Kg/bcm] - 0.43 (0.07) - 0.16 (0.03) 0.18 (0.03)

LNG [Kg/bcm] - - - 1.03 1.85

Fugitive Emissions [Kg/bcm] - - - 0.36 0.12

Total AB Avg (Co-Gen) [Kg/bcm] 2.86 2.7 (2.33) 2.81 2.99 (2.85) 2.44 (2.29)

Capital costs incurred depend on the selected technology. The trolley assist case results in fewer truck

purchases due to increased truck speeds while connected to the trolley assist system; however,

additional mine and equipment infrastructure is required when compared to the base case. The additional

capital cost is offset by a decrease in mine operating costs resulting from reduced truck maintenance

costs and the benefit of powering the mine fleet off of the electrical grid compared to diesel along high

engine load road segments. The LNG substitution cases result in additional capital and operating costs

due to the installation and operation of the on-site LNG plant, storage, fueling equipment, and haul truck

outfitting. These additional costs are more than offset by fuel cost savings as the cost of LNG produced

from an in-place natural gas supply line is estimated to be $0.05 per litre compared to the assumed $0.90

per litre of diesel fuel. Increased cycle times accompanying the rear dump trailer case resulted in 52

additional truck units purchased throughout the life of mine; and, despite the decreased truck capital cost

and reduced hourly operating costs, life of mine costs increased by nearly 4%. Table 8.2 shows the total

life of mine costs of implementing each technology.


Conclusions


Table 8.2 GHG Emissions Summary



LOM Cost

Truck CAPEX [Million's $] 1,434 1,387 1,516 1,434 1,434

LNG CAPEX [Million's $] - - - 185 186

Trolley CAPEX [Million's $] - 175 - - -

Truck OPEX [Million's $] 11,854 10,609 12,590 11,854 11,854

LNG OPEX [Million's $] - - - 108 113

Diesel [Million's $] 5,379 4,254 5,279 2,689 538

Power [Million's $] - 196 - 73 80

LNG [Million's $] - - - 251 452

Carbon Tax [Million's $] 811 658 795 806 648

Total [Million's $] 19,477 17,279 20,181 17,401 15,305 Unit Cost

Truck CAPEX [$/BCM] 0.25 0.24 0.26 0.25 0.25

LNG CAPEX [$/BCM] - - - 0.03 0.03

Trolley CAPEX [$/BCM] - 0.03 - - -

Truck OPEX [$/BCM] 2.04 1.83 2.17 2.04 2.04

LNG OPEX [$/BCM] - - - 0.02 0.02

Diesel [$/BCM] 0.93 0.73 0.91 0.46 0.09

Power [$/BCM] - 0.03 - 0.01 0.01

LNG [$/BCM] - - - 0.04 0.08

Carbon Tax [$/BCM] 0.14 0.11 0.14 0.14 0.11

Total [$/BCM] 3.35 2.97 3.47 2.99 2.63

The above results can be used to evaluate the unit cost savings per GHG emission reductions as shown

on Figure 8-1. As shown, the rear dump trailer results in a higher incremental cost while reducing GHG

intensity slightly. LNG at 50% substitution rates results in $0.36/BCM cost saving but increases GHG

intensity on the Alberta electrical grid; or, slightly reduces GHG intensity with co-gen power. Trolley assist

reduces unit cost by approximately $0.37/BCM; however, due to the reliance on electrical power, the

GHG intensity reduction is highly dependent on the power source. Using co-gen power, trolley assist may

provide a significant reduction in GHG intensity. LNG at 90% substitution provides the largest unit cost

reduction at $0.71/BCM while also providing the largest reduction in GHG intensity when using co-gen

power.


Conclusions


Figure 8-1 GHG Intensity Reduction vs. Mining Unit Cost Reduction

Based on the data presented, the trolley assist and LNG 90% technologies appear to provide the most

opportunity to reduce both mining unit costs and GHG intensity. LNG at 50% substitution rates may

provide an opportunity to reduce GHG intensity if the technology development can limit or eliminate

fugitive emissions. Due to the high GHG intensity of the Alberta electrical grid, an alternative energy

source such as a co-gen power unit is required to maximize the benefit from the trolley assist technology.


9.1 9.1

9.0 REFERENCES

Caterpillar; 2007. Caterpillar Performance Handbook; a publication by Caterpillar, Peoria, Illinois,

U.S.A. January 2017.

Norwest Corporation; 2015. Fluid Fine Tails Thermal Drying versus Consolidated Tailings; a High

Level Assessment of Cost Impacts. Submitted to COSIA March 5, 2015.

Alberta Government; 2015. Carbon Offset Emission Factors Handbook; ESRD Climate Change,

2015, No. 1.

Prometheus Energy. LNG Quick Facts. Retrieved from

:http://www.prometheusenergy.com/_pdf/LNGQuickFacts.pdf

Gti; Technology Scan, Ultra-Class Mine Haul Truck GHG Reduction Study, Gas Technology

Institute. A PowerPoint presentation provided by COSIA.


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