Long term forecasts for oil prices: a review of oil supply ...€¦ · Societal Tradeoffs in 21st...
Transcript of Long term forecasts for oil prices: a review of oil supply ...€¦ · Societal Tradeoffs in 21st...
Long term forecasts for oil prices: a review of oil supply, energy market
models, and the range of future trajectories for oil price.
Adrian R.H. Wiegman ([email protected])
J.W. Day, C.F. D’Elia, C.A.S. Hall, D.J. Murphy, J.S. Rutherford, R.R. Lane
Louisiana State University
Biophysical Economics (BPE) Conference Washington D.C. June 28, 2016
Preview
Societal Tradeoffs in 21st CenturyReview
EROI Model: Cycles of EROI and Oil Prices Energy Market Model Assumptions
Demand: GDP and Population Growth Climate Policy & Producer Behavior
Long Term Forecasts for Oil PriceApplication of Forecast
Simulating Costs as a Function of Oil PricesConclusions and Future Work
Biophysical Model Capable of Simulating Price
Motivation: Decision Support & BPEAdapting to 21st century megatrends requires large investments and long term planning…• Mitigating harmful effects of climate change • Feeding and caring for a growing, aging population• Replacing an aging stock of infrastructure• Mitigating waste and pollution• Building a new renewable energy systemWe know that success/failure will be impacted by net energy and fossil fuels, But…• How do we use BPE to inform assessment of tradeoffs?• We need to speak in a language people understand…
($$) • Therefore we ought to model price.
Why Forecast the Price of Oil?
• Oil is a direct input to many processes, thus has measurable effect on the cost of an activity.
• Indirect effects on prices are evident in the relations to commodity prices and GDP growth.
• Energy Prices Follow Oil Prices (Tverberg, Shafie& Topal 2010)
• Commodity Prices Follow Energy Prices, Especially Oil (Ji & Fan 2012, Sadorski 2014)
Source: Heun & De Wit 2012, (Also see King & Hall 2011, King et al. 2015a)
Relation Between Price and EROI
Price Cycles Drive Investment and EROI (Murphy & Hall 2011)
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($2010 b
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1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016
Cru
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oil
P
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(kb
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)
Year
A. Price Signal
B. Industry Response
C. Net Effect on Supply
Oil Price
Investment
Production
Time Delay
Demand
Conventional EMM
(EIA, IEA, McGlade)
(Data: EIA 2016)
Oil Price
Investment
Production
Demand
Biophysical(e.g. Murphy & Hall 2011)
Energy Market Models Calculate Price, Investment, and Production Based on Supply & Demand Equilibrium
McGlade 2014
Note: These prices are probably a bit inflated, given the strengthening of the U.S. dollar
Oil Price (SDEQ)
Demand at $
ENERGY MARKET MODEL
Supply at $
2:1 (Brandt et al. 2013)5:1
~1.5:1?
12-30:1
~8-30:1 (Hall et al. 2014)
(Brandt et al. 2015)
Supply Curve of the Types of Oil and EROI Estimates
5:1
>30:1
Supply Database
(see figure)
GDPPOP
Oil
Ind
ust
ry Investment at $
(NPV > 0)
Climate Policy (Demand) is an Important Driver
McGlade 2014, Model Outputs
• GDP & Pop. are forcings that grow exponentially…• Exp. grwth. outways negative feedback of high price…• Demand grows despite increasing prices, causing price
to sky rocket…such a result is not likely valid• Barring incredible efficiency gains, GDP must be
impacted by energy price!
Prices Diverge
Price Shock!
Oil Price (SDEQ)
Demand at $
ENERGY MARKET MODEL
Supply at $
Supply Database
(see figure)
Market Based Climate Policy
GDPPOP
Oil
Ind
ust
ry Investment at $
(NPV > 0)
The Industry behavior (and financing) fluctuates over time and exerts a major influence on price.
McGlade 2014, Low Carbon Scenario
a. Producers hesitant to take on risk, increasediscount rate of NPV.
b. Dissolution of OPEC,members act as indvls.
Prior to 2008 a but not b, In 2015 we saw b but not a, In 2016, the world is seeing a and b
Oil Price (SDEQ)
Demand at $
ENERGY MARKET MODEL
Investment at $(NPV > 0)
Supply at $
Supply Database
(see figure)
Market Based Climate Policy
Dyn
amic
Oil
Ind
ust
ry
GDPPOP
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2010 2015 2020 2025 2030 2035 2040 2045 2050
Re
al P
ric
e o
f C
rud
e O
il (
20
10
$/b
l)LCS_Institutions NPS_Libya NPS_OPEC NPS_InstitutionsEIA_REF LCS_Libya Heun & De Wit Fit1 EIA_LOWIEA_NPS IEA_CPS LCS_OPEC Heun & De Wit Fit2EIA_HIGH IEA_LowPrice IEA_450ppm
IEA and EIA Start
Projections in 2013
McGlade and
Heun & de Wit
Start Projections
in 2010
Summary of Models
• McGlade’s model has shorter time step & simulates price volatility, but lack of negative forcing on GDP leads to instability (exponential price increase).
• All assume GDP and Population growth rates are exogenous forcings… in other words there are no recessions.
• All assume high prices unlock new expensive substitutes, such as low EROI synfuels, to maintain supply indefinitely… likely a violation of first principles.
I Capped Prices @ $350
After 2035
Extapolation w. 5% decay in rate
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2010 2020 2030 2040 2050
Real P
rice o
f C
rud
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il
(2010$/b
l)Central AVG
Low AVG
High_$350cap
GOEMETRIC MEAN
High_Unconstrained
Low Demand:Stringent Climate Policy (CO2 tax)
High Demand:No Climate Policy
There Will Be A Crash… But When??
Price (+/- 0.5 SD) and Estimated % GDP allocated to Energy Expenditure (Following King et al. 2015)
Low Central High
Year Avg. $/bl %GDP on E Avg. $/bl %GDP on E Avg. $/bl %GDP on E
2025 73(+/-7) 6-8% 99(+/-6) 7-10% 134(+/-20) 10-14%
2035 73(+/-6) 7-9% 124(+/-7) 7-12% 251(+/-44) 16-27%
Results
Producer BehaviorUp to +/- $30bl
Composite Forecast of Oil Prices Applied
$-
$10,000.00
$20,000.00
$30,000.00
$40,000.00
$50,000.00
$60,000.00
$70,000.00
$80,000.00
$90,000.00
No Change ($50/bl) LOW CENTRAL HIGH
Co
st o
f Su
stai
nin
g W
etla
nd
s w
ith
Dre
dgi
ng
(20
10
$/a
cre
)
(Wiegman et al. in prep)
Estimated Cost to Restore & Sustain 1 Acre of Louisiana Marsh Above Sea Level for 50 Years, with Sea Level Rise of 0.7m (Preliminary Results, Not an NPV, No Discount
Rate Applied, Dredging data from Lacoast.gov, email me for Methods)
Conclusions and Future Work• Oil prices will be impacted by industry behavior, and
climate policy.• Producers respond to price, this influences investment
and EROI, resulting in price cycles. • Current EMMs, do not Include net energy related
feedbacks to GDP… which is a problem.• Models of EROI (e.g. Dale 2012, Energies), should be
added to supply databases of EMM’s so that net energy and GDP related feedbacks can be included in global oil models.
• For questions and potential collaboration email me: [email protected]
Oil Price (SDEQ)
Demand at $
ConventionalENERGY MARKET MODEL
Investment at $
Supply at $
Supply Database
Market Based Climate Policy
Oil Price (SDEQ)
Demand at $
Proposed BPE BasedENERGY MARKET MODEL
Investment at $
Supply at $
Climate Policy
Supply Database w/
EROI Data
Dyn
amic
Oil
Ind
ust
ry
Dyn
amic
Oil
Ind
ust
ry
Net EnergyModule
GDP functionOr EnergyConsumingCapital Stocks
GDPPOP
Co
nsu
me
r Econ
om
y
LogicalAssumptions
MarketSignals
PolicyDriver
Energy &Material
4. Consumer Economy (Population, GDP and End
Use Consumption)
5. E&M Production (Well Level Drilling Activity
and Production)
6. Market (Transactions
& Price SettingSDEQ)
2. Reserves & Resource
Stock
3. Policy Drivers
New Market Price (t)
1. Capital Stock &
Technology
Price (EROI) GDP Feedback: If Price*Quantity > %5.5 of GDP, then debt cycle slows, capital investment decreases
Rational Producer Behavior: If NPV(t) of Field is > 0, Then Drill
Discretionary & Maintenance Investments
Energy Investments
Products(Efficiency)
Raw Energy
Incentives
Commands
Commands
$$
$$
$$
Dat
abas
eD
atab
ase
Global Biophysical Model of Energy Markets withHypotheses for future of the energy transition
a. Central Price Scenario –Moderate Transition
b. Low Price Scenario -Successful Climate Policy Rapid Transition
c. High Price Scenario -Unsuccessful Climate Policy Slow Transition
1. Seasonal & IntermittantSolar Flux
2. Total and Discretionary Portion of GDP
3. Fossil Fuel (or Oil) Supply
4. Price of Energy $ EJ
5. Biophysical Systems –Provide Food and Assimilate Wastes
6. WASP – Wind and Solar Power
References• Energy Information Administration. 2015. Annual Energy Outlook.
• Hamilton, J. D. (2012). Oil prices, exhaustible resources, and economic growth (No. w17759). National Bureau of Economic Research.
• IEA (International Energy Agency). 2015. World Energy Outlook 2015. Paris: International Energy Agency
• Heun, M. K., & de Wit, M. 2012. Energy return on (energy) invested (EROI), oil prices, and energy transitions. Energy Policy, 40, 147-158.
• Ji, Q. and Fan, Y., 2012. How does oil price volatility affect non-energy commodity markets?. Applied Energy, 89(1), pp.273-280.
• King, C. W., & Hall, C. A. (2011). Relating financial and energy return on investment. Sustainability, 3(10), 1810-1832.
• King, C. W., Maxwell, J. P., & Donovan, A. (2015a). Comparing world economic and net energy metrics, Part 1: Single Technology and Commodity Perspective. Energies, 8(11), 12949-12974.
• King, C. W., Maxwell, J. P., & Donovan, A. (2015b). Comparing World Economic and Net Energy Metrics, Part 2: Total Economy Expenditure Perspective. Energies, 8(11), 12975-12996.
• Lacoast. 2015. Projects Lists. Coastal Wetlands Planning Protection Restoration Act. Available online: http://lacoast.gov/new/Projects/List.aspx accessed: Nov, 1, 2015
• Loulou, R. and Labriet, M. (2008). ETSAP-TIAM: the TIMES integrated assessment model. Part I: Model Structure. Computational Management Science, Special issue "Managing Energy and the Environment", Vol. 5, Issue 1, pp.7-40.
• Loulou, R. (2008). ETSAP-TIAM: the TIMES integrated assessment model. Part II: Mathematical formulation. Computational Management Science, Special issue "Managing Energy and the Environment", Vol. 5, Issue 1, pp.41-66.
• McGlade, C. E. 2014. Uncertainties in the outlook for oil and gas (Doctoral dissertation, UCL (University College London)).
• McGlade, C., & Ekins, P. (2015). The geographical distribution of fossil fuels unused when limiting global warming to 2 [deg] C. Nature, 517(7533), 187-190.
• Murphy, D.J., and Hall C.A.S. 2011. Adjusting the economy to the new energy realities of the second half of the age of oil. Ecological Modeling. DOI:10.1016/j.ecolmodel.2011.06.022
• World Bank. 2015. Commodities Price Forecast. Released October 20, 2015.