Berlin, 22 March 2012
The Availability of Global Fossil Energy: Methods for Reserve, Resource, and Cost Estimation
Roberto F. Aguilera
Centre for Research in Energy and Minerals Economics
OBJECTIVES
 To discuss accessibility and reliability of fossil fuel reserve, resource and cost data
 To present methods for evaluating fossil fuel quantities
 To examine challenges of estimating current and future production costs CRICOS Provider Code Curtin 00301J (WA) 02637B (NSW) www.business.curtin.edu.au/creme
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QUESTIONS  Is depletion likely to create significant scarcities and dramatic cost increases?
 Will society experience a smooth or bumpy transition as it moves to non‐fossil energy?
 What is the role of fossil energy in the long‐
term energy mix?
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GEM WORLD PRIMARY ENERGY SUBSTITUTION
1
Measured
f, fraction of total market
Gases-calculated
Oil-calculated
0.8
Wood
Wood-calculated
Coal calculated
Coal
Nuclear calculated
0.6
Hydro calculated
Oil
0.4
0.2
Gases
Nuclear
Hydro
0
1850
1875
1900
1925
1950
1975
2000
2025
YEAR
Source: Aguilera and Aguilera (2012), Technological Forecasting & Social Change
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Source: Aguilera and Aguilera (2012), Technological Forecasting & Social Change
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Source: Aguilera and Aguilera (2012), Technological Forecasting & Social Change
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Source: Aguilera and Aguilera (2012), Technological Forecasting & Social Change
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CO2: POTENTIAL VS HISTORICAL VS SCENARIOS
“ The choice of energy mix & associated investment will determine whether, and if so, at what level and cost, greenhouse concentrations can be stabilized… ”
Source: IPCC WGIII (2001)
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THE DEBATE
Fixed stock paradigm:
“the pessimists”
Opportunity cost paradigm:
“the optimists”
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THE DEBATE
“the middle of the road”
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METHODS FOR FUTURE SUPPLY PROSPECTS
Models:








Lifecycle
Rate of effort
Econometric
Geologic‐volumetric; geoscientific
Subjective probability
Discovery process
Size distribution
Simulation; optimization
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COMPLEX METHODS
 e.g. geoscientific; geologic‐
volumetric; simulation; optimization USGS World Petroleum Assessment 2000
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FIELD BY FIELD
 Field by field or project by project assessment
“Projections of liquids production
before 2015 are based largely on a
project‐by‐project assessment of
production volumes and associated
scheduling
timelines,
with
consideration given to the decline
rates of active projects, planned
exploration and development activity,
and
country‐specific
geopolitical
situations and fiscal regimes.”
Source: US EIA International Energy Outlook (2010)
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SIMPLE MODELS
 e.g. lifecycle; size distribution
Source: adapted from Barton (1995), USGS
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SIZE DISTRIBUTION MODELS
10000
Cumulative Number of Discovered Fields
Pareto curve
1000
Undiscovered
oil and gas
100
Limit of economic
perceptibility
10
Discovered oil
and gas
1
0,1
0,01
0,1
1
10
100
1000
10000
Field Size, in mmBOE
Source: adapted from Barton (1995), USGS
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VARIABLE SHAPE DISTRIBUTION MODEL (VSD)
 Used to estimate oil and gas quantities in previously unassessed geological provinces
 Unlike other models, VSD is not based on an assumed distribution (e.g. Pareto or lognormal)
Source: Aguilera (2006), Colorado School of Mines
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VARIABLE SHAPE DISTRIBUTION MODEL (VSD)
VSD Equations
NonlinearLeast
LeastSquare
Square
Nonlinear
RegressionModel:
Model:
Regression
Subjectto:
to:
Subject

Vi 
n

min {V x , a p ,Vs , , S }  (Vi  V i ) 2
i 1
Parameters:
Para
meters:
v olume
VxVx Maximum
Maximum volume
al slop
a pap Fract
Fractal
slopee
Approximate volume
VsVs Approximate
volume
Separation
ψ ψ Separa
tion ratio
rat io
S
Severity
exponent
S Sever ity exp onen t
1



log N x  log N m
a
p
(
)


 

Vm 
 1  Vm  log V x  log Vm 

  V x    
  
 
 
Vx 

  N t  V x 





 


1

 



log

log
N
N
x
m
a


p
(
)

 


log

log
V
V
x
m

V

  1  Vm 

  
 m   V x   Vs  
( )  [1  ( )]  1  exp    



Vx 
 N t  V x 








  






 
S
Source: Aguilera (2006), Colorado School of Mines
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Source: Aguilera et al (2012), Mathematical Geosciences, forthcoming
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FRIO STRANDPLAIN PLAY, TEXAS, 1985
Only the largest nine data points are shown. The remaining data has been truncated due to economic considerations.
Source: Crovelli and Barton (1993), USGS
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Source: Aguilera et al (2012), Mathematical Geosciences, forthcoming
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Source: Aguilera et al (2012), Mathematical Geosciences, forthcoming
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Source: Aguilera et al (2012), Mathematical Geosciences, forthcoming
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Source: Aguilera et al (2012), Mathematical Geosciences, forthcoming
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Source: Aguilera et al (2012), Mathematical Geosciences, forthcoming
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USGS WORLD PETROLEUM ASSESSMENT (2000)
 USGS (2000) divides world into 937 provinces; evaluates less than half
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VARIABLE SHAPE DISTRIBUTION MODEL (VSD)
Source: Aguilera et al. (2012), UN IYPE Series, Springer, forthcoming
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VARIABLE SHAPE DISTRIBUTION MODEL (VSD)
Source: Aguilera et al. (2012), UN IYPE Series, Springer, forthcoming
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VARIABLE SHAPE DISTRIBUTION MODEL (VSD)
Source: Aguilera et al. (2012), UN IYPE Series, Springer, forthcoming
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VARIABLE SHAPE DISTRIBUTION MODEL (VSD)
Source: Aguilera et al. (2012), UN IYPE Series, Springer, forthcoming
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VARIABLE SHAPE DISTRIBUTION MODEL (VSD)
Source: Aguilera et al. (2012), UN IYPE Series, Springer, forthcoming
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VARIABLE SHAPE DISTRIBUTION MODEL (VSD)
Source: Aguilera et al. (2012), UN IYPE Series, Springer, forthcoming
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VSD PETROLEUM (CONVENTIONAL)
7000
6000
2280 BBOE
Reserve growth = 2280 BBOE
1093 BBOE
VSD estimate for 528 previously
unassessed provinces = 1093
BBOE
5000
Volume (BBOE)
4000
3000
2000
USGS (2000) data for 409
provinces = 3563 BBOE
TOTAL (FUTURE)
6936 BBOE
3563 BBOE
Cumulative Production = 1415
BBOE (BP 2011)
1000
0
‐1000
Cum. Prod.
‐2000
Oil, Gas and NGL (World)
Source: Aguilera et al. (2012), UN IYPE Series, Springer, forthcoming
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CONVENTIONAL OIL RESERVES AND RESOURCES
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
Reserves +
Resources
BGR
(EJ)
Reserves +
Resources
USGS
(EJ)
United States of America
Canada
Western Europe, incl. Turkey
Central and Eastern Europe
Former Soviet Union
Northern Africa
Eastern Africa
Western and Central Africa
Southern Africa
Middle East
China
Other East Asia
India
Other South Asia
Japan
Other Pacific Asia
Australia, New Zealand and other Oceania
Latin America and the Carribean
Circum-Arctic
582
129
275
19
1743
573
17
556
227
5175
181
58
50
15
1
69
153
1093
-
659
57
671
26
1906
410
7
517
121
4621
237
1
58
13
0
202
86
1279
768
World
10916
11639
Source: Global Energy Assessment (2012), Cambridge University Press, forthcoming
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CONVENTIONAL GAS RESERVES AND RESOURCES
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
Reserves +
Resources
BGR
(EJ)
Reserves +
Resources
USGS
(EJ)
United States of America
Canada
Western Europe, incl. Turkey
Central and Eastern Europe
Former Soviet Union
Northern Africa
Eastern Africa
Western and Central Africa
Southern Africa
Middle East
China
Other East Asia
India
Other South Asia
Japan
Other Pacific Asia
Australia, New Zealand and other Oceania
Latin America and the Carribean
Circum-Arctic
1002
324
475
54
6684
634
23
396
91
4097
461
86
75
130
1
193
577
700
-
732
79
657
41
3382
363
11
297
61
3041
126
3
56
117
0
452
216
831
1748
World
16003
12213
Source: Global Energy Assessment (2012), Cambridge University Press, forthcoming
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COAL RESOURCES
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
Hard
Coal
Lignite/
Brown Coal
(EJ)
(EJ)
United States of America
Canada
Western Europe, incl. Turkey
Central and Eastern Europe
Former Soviet Union
Northern Africa
Eastern Africa
Western and Central Africa
Southern Africa
Middle East
China
Other East Asia
India
Other South Asia
Japan
Other Pacific Asia
Australia, New Zealand and other Oceania
Latin America and the Carribean
163816
3560
7416
5192
76947
10
22
72
1178
1125
121693
1298
3954
83
297
2696
941
753
16382
610
449
2405
14204
0.4
0.4
2.6
0
0
2966
3085
329
1753
11
1720
551
202
World
391053
44670
Source: Global Energy Assessment (2012), Cambridge University Press, forthcoming
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SHALE TECHNOLOGY: Horizontal drilling
& hydraulic fracturing
“ the dramatic increase
in tight oil has been
made possible by the
same technology combo,
hydraulic fracturing and
horizontal drilling, that
created the ‘shale gale’ ”
Daniel Yergin, Wall Street Journal, 12 Dec 2011
Source: American Petroleum Institute (2010)
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WORLD GAS SUPPLY CURVE
Source: Ripple (2011), Australian Ambassador’s Speaker Series
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VARIABLE SHAPE DISTRIBUTION MODEL (VSD)
CONVENTIONAL AND UNCONVENTIONAL GAS ENDOWMENTS
USGS (1995, 2000) and MMS (1996) data for 216
provinces = 11,644 tcf
CUMULATIVE NUMBER OF PROVINCES
10000
VSD for 216 provinces = 11,378 tcf (R2=0.98)
VSD for 937 provinces = 15,079 tcf
1000
15 tight gas provinces in U.S. and Canada
VSD Conv and tight gas=30,159 TCF
100
VSD Conv tight shale gas = 40,212 TCF
VSD Conv tight shale CBM = 45,238 TCF
10
1
1.E+00
1.E+01
1.E+02
1.E+03
1.E+04
1.E+05
1.E+06
CONVENTIONAL GAS ENDOWMENT (BCF)
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1.E+08
Source: Aguilera et al. (2012), submitted to SPE APOGCE
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FOSSIL ENERGY QUANTITIES AND LIFE EXPECTANCIES
Source: Aguilera and Aguilera (2012), Technological Forecasting & Social Change
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CUMULATIVE AVAILABILITY CURVE
Price
($ / boe)
Cumulative
Quantity
(boe)
ALL TIME
Source: Aguilera et al. (2009), Energy Journal
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COMPARATIVE COST CURVE
Average
Total
Cost
C2
C1
A
0
B
a
b
Quantity
Source: Aguilera et al. (2009), Energy Journal
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Source: Aguilera et al. (2009), Energy Journal
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GLOBAL CUMULATIVE LONG-RUN SUPPLY CURVE FOR CONVENTIONAL PETROLEUM AND
UNCONVENTIONAL SOURCES OF LIQUIDS INCLUDING HEAVY OIL, OIL SANDS AND OIL SHALE
38.00
36.00
Conventional Petroleum, Heavy Oil, Oil-Sands and
Oil Shale = 30 trillion BOE
34.00
Average Total Production Cost (2006 US$/BOE)
32.00
Oil Shale =
14 trillion
BOE
30.00
28.00
26.00
24.00
22.00
Oil Sands =
5 trillion
BOE
20.00
18.00
16.00
14.00
12.00
Heavy Oil =
4 trillion
BOE
10.00
8.00
6.00
4.00
2.00
0.00
0
2
4
6
8
10
12
14
16
18
20
Future Volume (trillion BOE)
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24
26
28
30
32
Source: Aguilera et al. (2009), Energy Journal
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LIQUID SUPPLY COST CURVE
Source: Farrell (2008), University of California, Berkeley
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GLOBAL CUMULATIVE LONG-RUN SUPPLY CURVE FOR COAL, CONVENTIONAL PETROLEUM AND
UNCONVENTIONAL SOURCES OF LIQUIDS INCLUDING HEAVY OIL, OIL SANDS AND OIL SHALE
38.00
36.00
Coal, Conventional Petroleum, Heavy Oil, Oil-Sands
and Oil Shale = 68 trillion BOE
34.00
Average Total Production Cost (2006 US$/BOE)
32.00
Oil Shale
30.00
28.00
26.00
24.00
22.00
Oil Sands
20.00
Coal: Eastern
Europe, FSU,
Asia
18.00
16.00
Coal:
Western
Europe
14.00
Coal: United
States and
Latin America
12.00
10.00
Heavy Oil
Coal:
Australia
8.00
6.00
Coal: Africa
4.00
Coal:
Canada
2.00
0.00
0
5
10
15
20
25
30
35
40
Future Volume (trillion BOE)
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50
55
60
65
70
Source: Aguilera (2006), Colorado School of Mines
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GLOBAL CUMULATIVE LONG-RUN SUPPLY CURVE FOR GAS HYDRATES, COAL, CONVENTIONAL
PETROLEUM AND UNCONVENTIONAL SOURCES OF LIQUIDS INCLUDING HEAVY OIL, OIL SANDS AND OIL
SHALE
42.00
40.00
38.00
36.00
Average Total Production Cost (2006 US$/BOE)
34.00
32.00
30.00
28.00
26.00
24.00
22.00
20.00
18.00
16.00
14.00
12.00
10.00
8.00
Gas Hydrates, Coal, Conventional Petroleum,
Heavy Oil, Oil Sands and Oil-Shale = 449 trillion
BOE
6.00
4.00
2.00
0.00
0
50
100
150
200
250
Future Volume (trillion BOE)
CRICOS Provider Code Curtin 00301J (WA) 02637B (NSW) 300
350
400
450
Source: Aguilera (2006), Colorado School of Mines
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COST ESTIMATION: IEA
“This analysis is based on two main elements:

A survey of the capital‐spending programmes of 50 of the largest upstream oil and gas companies (national and international companies and pure exploration and production companies), covering actual capital spending from 2000 to 2007 and their plans or forecasts of spending through to 2012. Companies were selected on the basis of their size as measured by their production and reserves, though geographical spread and data availability also played a role. The surveyed companies account for close to 80% of world oil production and 79% of oil reserves, 66% of gas production and 71% of gas reserves. Total industry investment was calculated by adjusting upwards the spending of the 50 companies, according to their share of world oil and gas production for each year.

A review of all major upstream projects worldwide — sanctioned (approved by the company
board) and planned — which are due to be brought on stream before 2015. This review covers
over 570 projects, each involving a capacity addition of more than 5 thousand barrels of oil
per day (kb/d). Projects include conventional oil and gas production, non‐conventional oil
sands and coal‐ and gas‐to‐liquids.
Data was obtained from companies’ annual and financial reports, corporate presentations, press reports, trade publications and direct contacts in the industry.”
Source: International Energy Agency (WEO 2008)
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Source: International Energy Agency (2009)
Source: International Energy Agency (WEO 2008)
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IEA LONG‐TERM GAS SUPPLY CURVE
Note: Areas indicate availability of gas resources as a function of estimated costs of production in 2008. Only
sources with significant potential production before 2030 are included. These costs are based on the economics
of gas production only, not taking into account the value or cost of any liquids production. However, some costs
for associated gas production are shared with liquids production costs, thereby generally lowering overall costs
for associated gas. Transportation costs are additional and apply to all resource types.
Source: International Energy Agency (WEO 2009)
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Source: International Energy Agency (WEO 2011)
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Source: International Energy Agency (WEO 2011)
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BACK‐OF‐ENVELOPE COST CALCULATION
 From Rosneft Oil Company Financial Statement 2011
opex 2011
USD
capex 2011
USD
Production & Operating
Expense
6.540E+09
Depreciation
5.996E+09
Pipeline
Tariffs & Transport Cost
7.329E+09
Production 2011
BOE
Oil
9.320E+08
Exploration Expense
4.480E+09
TOTAL
1.432E+10
opex USD/BOE = $1.432E+10 / 9.320E+08 BOE
= $15.36 per BOE
capex USD/BOE = $5.996E+09 / 9.320E+08 BOE
= $24.63 per BOE
TOTAL COST = $39.99 per BOE
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Source: Wood Mackenzie (2004)
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ANOTHER METHOD: RESOURCE CATEGORIES
 Five categories based on cost:





CI – Proved (P90) reserves
CII – Probable (P50) reserves
CIII – Possible (P10) reserves
CIV – Enhanced recovery
CV – Deep offshore
Source: Aguilera and Ripple (2012), Applied Energy, forthcoming
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GAS PRODUCTION COSTS: EUROPE
Cost
Category
CI
CII
CIII
CIV
CV
Production costs (2009)
Technology
Lower Bound Upper Bound
change (USD/MCF)
(USD/MCF)
in %/yr
Natural Gas
0.50
0.90
1.50%
0.90
1.40
1.50%
1.40
2.30
1.50%
2.30
3.10
1.00%
3.10
3.75
1.00%
Production costs (2030)
Lower Bound Upper Bound
(USD/MCF)
(USD/MCF)
0.35
0.65
1.00
1.85
2.50
0.65
1.00
1.65
2.50
3.00
Source: Aguilera and Ripple (2012), Applied Energy, forthcoming
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FUTURE GAS PRODUCTION COSTS: EUROPE
Cost
Category
CI
CII
CIII
CIV
CV
Production costs (2009)
Technology
Lower Bound Upper Bound
change (USD/MCF)
(USD/MCF)
in %/yr
Natural Gas
0.50
0.90
1.50%
0.90
1.40
1.50%
1.40
2.30
1.50%
2.30
3.10
1.00%
3.10
3.75
1.00%
Production costs (2030)
Lower Bound Upper Bound
(USD/MCF)
(USD/MCF)
0.35
0.65
1.00
1.85
2.50
0.65
1.00
1.65
2.50
3.00
Source: Aguilera and Ripple (2012), Applied Energy, forthcoming
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FUTURE GAS PRODUCTION COSTS: EUROPE
Cost
Category
CI
CII
CIII
CIV
CV
Production costs (2009)
Technology
Lower Bound Upper Bound
change (USD/MCF)
(USD/MCF)
in %/yr
Natural Gas
0.50
0.90
1.50%
0.90
1.40
1.50%
1.40
2.30
1.50%
2.30
3.10
1.00%
3.10
3.75
1.00%
Production costs (2030)
Lower Bound Upper Bound
(USD/MCF)
(USD/MCF)
0.35
0.65
1.00
1.85
2.50
0.65
1.00
1.65
2.50
3.00
Source: Aguilera and Ripple (2012), Applied Energy, forthcoming
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GAS QUANTITY DISTRIBUTION: EUROPE
ASSUMED
 CI: 30%
 CII: 47%
 CIII: 15%
 CIV: 5%
 CV: 3%
Source: Aguilera and Ripple (2012), Applied Energy, forthcoming
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GAS SUPPLY COST CURVE: EUROPE
4,00
3,50
US$ (2009) per MCF
3,00
2,50
2,00
1,50
1,00
2009 Technology
0,50
2030 Technology
0,00
Cum. Prod.
(320 TCFG)
BP (2011)
0
400
800
1200
1600
2000
Natural Gas Future Volume (TCF)
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GEA SUPPLY COST CURVES
Oil
Gas
Source: Global Energy Assessment (2012), Cambridge University Press, forthcoming
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FUTURE PRODUCTION COSTS: EXPERIENCE CURVES
United States
Source: Hettinga et al (2009), Energy Policy
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FUTURE PRODUCTION COSTS: EXPERIENCE CURVES
United States
Brazil
Source: Yeh and Rubin (2011), Energy Economics
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DATA SOURCES
Government Agencies
 proved reserves
 production
 undiscovered volumes
 exports, imports
 prices
Industry Journals
 proved reserves
 drilling activity
 prices
Private Companies
 resources (2P)
 production costs
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DATA SOURCES











API (U.S. well completions data)
Baker Hughes (drilling rig count)
BP Statistical Review (reserves, prices, trade,…)
IEA (consumption, imports, exports, stocks)
ODS Petrodata (offshore rig fleet)
O&G Journal (reserves)
OPEC (production, reserves, exports, refining cap.)
US EIA (US and International stats)
World Oil (number of wells drilled by country)
BGR, USGS, IHS, Wood Mackenzie (resource data)
Wood Mackenzie, PIRA, CERA (cost data)
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DATA SOURCES
Sources for daily oil and gas prices:
 Bloomberg.com
 CNN/Money – commodity prices
 NYMEX
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DATA SOURCES
By data type:














Active rigs ‐ Baker Hughes
Wells drilled and depth‐ API, World Oil
Cost of wells ‐ API/Joint Association Survey
Active wells ‐ OGJ, IPAA, IOGCC
Oil and gas reserves ‐ OGJ, EIA
Oil production ‐ EIA, IEA, OGJ
Gas production ‐ EIA, OGJ
Demand/consumption ‐ EIA, IEA, BP
Stocks/inventory ‐ EIA, IEA, API, BP
Imports/exports/crude movements ‐ EIA, IEA, API
Energy demand ‐ BP, EIA
Oil prices ‐ EIA, NYMEX
Production costs ‐ Wood Mackenzie, PIRA, CERA
Resources (2P) ‐ IHS, Wood Mackenzie, BGR, USGS CRICOS Provider Code Curtin 00301J (WA) 02637B (NSW) www.business.curtin.edu.au/creme
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DATA RELIABILITY
Availability:
 Data limitations for regions outside the United States and parts of Europe
 Some data (e.g. 2P resources, production costs) is exceedingly expensive CRICOS Provider Code Curtin 00301J (WA) 02637B (NSW) www.business.curtin.edu.au/creme
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DATA RELIABILITY
Definitions:
 Conventional versus unconventional oil (or commercial vs. uncommercial?)
 Reserves versus resources
 Reserve growth
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DATA RELIABILITY
Reserves and Resources:
 Under‐reporting
definitions (e.g. 1P or 2P reserves)
 Over‐reporting
sudden reserve increases
 Non‐reporting
reserves unchanged year after year
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CONCLUDING THOUGHTS
 Global fossil fuels more abundant and economic than commonly assumed
 Much uncertainty surrounding future fossil fuel use and associated CO2 emissions
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CONCLUSIONS
 Various sophisticated supply modeling methods have emerged; useful as compliments to one another
 Gaps in knowledge come partly from lack of reliable data
 data does not exist
 or only exists in certain regions
 and/or is difficult to obtain
 Detailed fossil fuel production costs are difficult to find and estimate
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Berlin, 22 March 2012
The Availability of Global Fossil Energy: Methods for Reserve, Resource, and Cost Estimation
THANK YOU
r.aguilera@curtin.edu.au