World Oil Depletion: Diffusion Models, Price Effects, Strategic and Technological Interventions

1
World Oil Depletion Diffusion Models, Price
Effects, Strategic and Technological Interventions
5-th International ASPO Conference, San Rossore,
18-19 July 2006, Italy
Renato Guseo
Department of Statistical Sciences
University of Padova, Italy
2
World Crude Oil Production
Thousand barrels daily
Global
OPEC
FSU
CSI
USA (NGL)
3
World Production and Prices
Fonte BP Statistical Review of World Energy, 2004
Produzione e prezzi del petrolio
4
Growth and Development after World War II
-1-

• Cohen, J.E. (2003) Human Population The next
  Half Century, Science, 203, 1172-1175
• Exceptional demographic expansion
• Rural population peak in rich countries 1950
• Increse of world average life 30 years in 1900
  and 65 years in 2000
• Population 6.3 billion in 2004 United Nations
  Population Division 8.9 billion in 2050 (ex
  medium variant scenario forecasting)
• Regional population contraction in 2050
  Japan -24 Italy -22 FSU -29

5
Growth and Development after World War II
-2-

• USA dominance in oil estraction and refining
  shock 1918 (positive with local memory)
• Decisive military advantage. Competitive
  advantage after World War II
• American way of life
• Energetic Surplus based on cheap crude oil
• Structural change in sustainable economic
  evolution based on non-renewable resources

6
Growth and Development after World War II
-3-

• Today risk physical restrictions towards
  expansion in oil production due to emergent
  demand by China and India
• Risk of a late migration towards renewable
  energetic resources
• Emerging technologies are not completely
  sustainable and efficient (fuel-cells, hydrogen,
  photovoltaic systems, solar thermal systems,
  eolic systems, etc.).

7
Recent strategic researches

• Morse, E.L. e Jaffe, A.M. (2001). Strategic
  Energy Policy Challenges for the 21st Century
  (2000 - aprile 2001) James A. Baker III
  Institute for Public Policy of Rice University,
  Texas Council of Foreign Relations of USA
• National Energy Policy Development Group, (2001,
  Task Force supervised by D. Cheney).
• USA energetic policy since 1940 security -
• Global Economic growth based on a production
  surplus with cheap prices
• New emerging world oil demand
• Supply dependence (Midle East).

8
Non-Renewable Resources Depletion Hubbert and
recent developtments

• Hubbert, M.K. (1949). Energy from fossil fuels,
  Science, 4, 103-109.
• In 1956 Hubbert forecasts the peak of annual
  production within 48-lower states in USA by
  year 1970
• Campbell, C. e Laherrère, J. (1998). The End of
  Cheap Oil, Scientific American, March 1998.
• Laherrère, J. (2003). Modelling future oil
  production, population and the economy, ASPO 2nd
  international workshop on oil and gas, Paris,
  26-27.
• ASPO (Association for the Study of Peak Oil and
  Gas)

9
Economic and financial estimation of oil
reserves inflated figures

• Warranties on international long-term loans
• Investments on production plants
• OPEC restrictions overcoming export is
  proportional to the declared reserves.

10
Ultimate Recoverable Resouce URR

• URR total amount of a finite resource obtainable
  at the end of extraction process
• Geologic estimates of Oil URR during the life-
  cycle of resource extraction
• Production to date. Oil heterogeneity. (weight
  100)
• Proven reserves. Ex-post recovery factor 35 is
  a median and todays variability is very large.
  Revision principles and reserves growth (USGS)
  enlarge uncertainties
• Probable and possible reserves undiscoverd
  petroleum based on subjective assessments
  (probability, e.g. 5).

• Could we do a simple weighted sum of such
  components?
• Probably not

11
Recent statistical modeling

• Guseo, R. (2004) Interventi strategici e aspetti
  competitivi nel ciclo di vita di innovazioni,
  Working Paper Series, 11, Department of
  Statistical Sciences, University of Padua.
• Guidolin, M. (2004) Cicli energetici e diffusione
  delle innovazioni. Il ruolo dei modelli di
  Marchetti e di Bass, Thesis, University of Padua.
• Guseo, R and Dalla Valle, A. (2005) Oil and Gas
  Depletion Diffusion Models and Forecasting under
  Strategic Intervention, Statistical Methods and
  Applications, 14(3), 375-387
• Guseo, R., Dalla Valle, A. and Guidolin, M.
  (2006) World Oil Depletion Models Price effects
  compared with strategic or technological
  interventions, Technological Forecasting and
  Social Change (in press)
• Guseo, R. (2006) Bass-let Detection of Automobile
  Successive Generations Evidence from the Italian
  Case (submitted).

12
Crude Oil Production Diffusion of an Innovation

• Oil production is modulated by the dynamics of
  international demand
• Oil demand is a function of the diffusion
  processes related to basical technologies
  (transport, chemical industries, heating, etc.)
• Diffusion of technological innovations is
  conditioned by social communication structure
  innovators and imitators (word-of-mouth)

13
Bass Equation BM

• z(t) mf(t) mpqF(t)1-F(t) or
• z(t) pm(q-p)z(t) - (q/m) z(t)2 (Riccati)
• z(t)mf(t) (instantaneous adoptions)
  
• f(t)F(t)
• z(t)m F(t) (cumulative adoptions)
  F(t)z(t)/m
• f(t)/1-F(t)pqF(t) Bass Hazard rate
• mpotential market carrying capacity URR
• pinnovation coefficient, pgt0
• qimitation coefficient, qgt0

14
Normalized Bass models BM and GBM

• BM f(t)/1-F(t)pqF(t)
  Standard
• GBM f(t)/1-F(t)pqF(t) x(t)
  GBM
• x(t) is a quite general intervention function
  integrable, positive and centered around
  unitary neutral pole 1.
• Representation of temporal price variations, of
  advertising pressure, of political, strategic,
  legal, environmental interventions.

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Equation Solution GBM
Exp. shocks
Rect. shocks
Mixed shocks
16
Great Britain GBM, 2 mixed sh.
Estimation method Marquardt Estimation stopped
after maximum iterations reached. Number of
iterations 31 Number of function calls
330 Estimation Results
Asymptotic 95,0
Asymptotic
Confidence Interval Parameter
Estimate Standard Error Lower
Upper --------------------------------------------
-------------------------------- m
4513,39 154,806 4196,77
4830,0 p 0,0000708436
0,0000324773 0,00000441993 0,000137267 q
0,111872 0,00516425
0,10131 0,122434 c1
8,54019 1,02935 6,43493
10,6454 b1 -0,250721
0,0114596 -0,274159 -0,227284 a1
10,7677 0,458356
9,83028 11,7052 c2
-0,331417 0,0175489 -0,367309
-0,295526 a2 23,4341
0,190843 23,0438 23,8245 b2
28,6819 0,164258 28,3459
29,0178 ------------------------------------
---------------------------------------- Analysis
of Variance Source Sum of Squares
Df Mean Square Model
6,52091E7 9 7,24545E6 Residual
657,546 29 22,674 ----------------
------------------------------------- Total
6,52097E7 38 Total (Corr.)
3,31712E7 37 R-Squared 99,998
percent R-Squared (adjusted for d.f.) 99,9975
percent Standard Error of Est. 4,76172 Mean
absolute error 3,10566 Durbin-Watson statistic
0,889298
Positive Shock with local memory
17
Great Britain analysis

• The saddle 1987-1991-1999 is perfectly absorbed
  by a rectangular shock
• a) Petroleum Reven Tax modification
• b) pipelines restructuring 1986-1991 symmetric
  behaviour confirms ordinary regime
• c) partial production stall due to the reduction
  of new discoveries.

18
USA 48 lower States and Alaska,one exponential
shock
Estimation Results -------------------------------
---------------------------------------------

Asymptotic 95,0
Asymptotic Confidence
Interval Parameter Estimate
Standard Error Lower
Upper --------------------------------------------
-------------------------------- m
224,885 0,784401 223,328
226,442 p 0,000445866
0,0000177788 0,000410571 0,000481162 q
0,0571941 0,000403937
0,0563922 0,057996 c1
0,682617 0,0735348 0,536632
0,828602 b1 -0,0852885
0,00948373 -0,104116 -0,0664609 a1
18,0477 0,981086
16,1 19,9954 -------------------------------
---------------------------------------------   An
alysis of Variance -------------------------------
---------------------- Source Sum of
Squares Df Mean Square ------------------
----------------------------------- Model
735809,0 6 122635,0 Residual
7,39124 95
0,0778026 ----------------------------------------
------------- Total 735817,0
101 Total (Corr.) 352880,0
100   R-Squared 99,9979 percent R-Squared
(adjusted for d.f.) 99,9978 percent Standard
Error of Est. 0,278931 Mean absolute error
0,207909 Durbin-Watson statistic 0,173839
Positive shock with local memory
19
USA 48 lower States and Alaska, ARMAX(4,0,2)
sharpening
Forecasting - barili Analysis Summary Data
variable barili Number of observations
101 Start index 1,0 Sampling interval
1,0   Forecast Summary ---------------- Forecast
model selected ARIMA(4,0,2) 1 regressor Number
of forecasts generated 40 Number of periods
withheld for validation 0    
ARIMA Model Summary Parameter
Estimate Stnd. Error t
P-value ------------------------------------------
---------------------------------- AR(1)
1,21416 0,691695 1,75534
0,082426 AR(2) -0,140994
1,11031 -0,126986 0,899220 AR(3)
-0,146337 0,49692
-0,294488 0,769028 AR(4)
-0,132467 0,0891259 -1,48629
0,140514 MA(1) 0,591549
0,68527 0,863235 0,390183 MA(2)
0,299352 0,650254
0,460362 0,646308 DIFF(PREDbe1)
0,20426 0,0890786 2,29303
0,024052 -----------------------------------------
----------------------------------- Backforecastin
g yes Estimated white noise variance
0,00495321 with 95 degrees of freedom Estimated
white noise standard deviation 0,0703791 Number
of iterations 17
Shock 1918
20
Alaska ARMAX(2,0,1) sharpening
ARIMA Model
Summary Parameter Estimate Stnd.
Error t P-value ----------------
--------------------------------------------------
---------- AR(1) 0,323713
0,100318 3,22686 0,002667 AR(2)
-0,172177 0,054492
-3,15967 0,003195 MA(1)
-0,818595 0,102552 -7,98224
0,000000 PREDbme1 0,847508
0,0501864 16,8872 0,000000 Mean
-0,0143829 0,0282678
-0,508809 0,613990 Constant
-0,0122034 ---------------------------------
------------------------------------------- Backfo
recasting yes Estimated white noise variance
0,00281514 with 36 degrees of freedom Estimated
white noise standard deviation 0,0530579 Number
of iterations 20
21
World Oil dataDaily Production
Sources

• Industriedatenbank 2001 (1900 1986)
• BP Statistical Review of World Energy (1987-
  2002)

22
GBM x(t) pure prices control
23
GBM exp shocks price effect
24
Guidolin (2004) GBM, 2 exp shocks
25
GBM 3 exp shocks (memory persistence)
26
GBM 3 exp shocks estimates(memory persistence)
q/p 608 ? Qp1
27
World Oil Depletion GBM with three shocks vs
Hubbert-Bass
Oil Peak 2007
URR1524 Gbo
Depletion time 95 2023
Depletion time 90 2019
28
Oil market Operators prices growth

• Demand and supply self-control similar to 1973
  and 1979-83 behaviour. Extension of crude oil
  economic life cycle
• Limited techonological efficiency margins due to
  the improvementes of 70s , 80s and 90s
• Savings through life styles modification this
  is the central dilemma in industrialized
  countries
• Sluggishness of middle class whose life style is
  based on an expected irreversible and indefinite
  growth and development.

29
New Emergent Economies

• Increase in crude oil requirements by recent
  emergent economies China, India, and other
  Asiatic countries
• US EIA (Energy Information Administration)
  forecasts a world oil demand of 40 Gbo/year
  (or 109.6 milion daily barrels) in 2020
• Guseo, Dalla Valle, Guidolin (2006) and Bakhtiari
  (2004) forecast, in 2019-20, only 55 milion daily
  barrels.

30
Crude Oil Area consumption
31
Outlook

• Nuclear fission perspective is probably a tardy
  strategy with known collateral externalities. A
  new plant in Italy can be launched after 13-15
  years
• Technological, political and economic efforts
  must be distributed in different areas
  photovoltaic, solar thermal, bio-fuel, biomass,
  eolic, hydrogen, etc.
• Electric sector distributed investments
  (photovoltaic, micro-cogeneration, etc.).
• Individual and collective mobility.

32
World Oil Depletion GBM with three shocks vs
Hubbert-Bass vs five shocks scenario
33
World Oil Depletion GBM with three shocks vs
five shocks vs four shocks scenarios
Shock 2008 (sim. 1951)
Depletion time 90 2017