Peak Oil Update - July 2009: Production Forecasts and EIA Oil Production Numbers
Posted by Sam Foucher on July 7, 2009 - 10:05am
Topic: Supply/Production
Tags: ali morteza samsam bakhtiari, bp, chris skrebowski, eia, logistic, loglets, m. king hubbert, oil, original, rembrandt koppelaar, robelius, update [list all tags]
An update on the latest production numbers from the EIA along with graphs/charts of different oil production forecasts.

World oil production (EIA Monthly) for crude oil + NGL. The median forecast is calculated from 15 models that are predicting a peak before 2020 (Bakhtiari, Smith, Staniford, Loglets, Shock model, GBM, ASPO-[70,58,45], Robelius Low/High, HSM,Duncan&Youngquist). 95% of the predictions sees a production peak between 2008 and 2010 at 77.5 - 85.0 mbpd (The 95% forecast variability area in yellow is computed using a bootstrap technique). The magenta area is the 95% confidence interval for the population-based model. Click to Enlarge.
Notations:
- mbpd= Million of barrels per day
- Gb= Billion of barrels (109)
- Tb= Trillion of barrels (1012)
- NGPL= Natural Gas Plant Liquids
- CO= Crude Oil + lease condensate
- NGL= Natural Gas Liquids (lease condensate + NGPL)
- URR= Ultimate Recoverable Resource
EIA Last Update (March)
Data sources for the production numbers:
- Production data from BP Statistical Review of World Energy (Crude oil + NGL).
- EIA data (monthly and annual productions up to March 2009) for crude oil and lease condensate (noted CO) on which I added the NGPL production (noted CO+NGL).
The all liquid peak is now July 2008 at 86.65 mbpd, the year to date average production value in 2009 (3 months) is down from 2008 for all the categories. The peak date for Crude Oil + Cond. is also July 2008 at 74.80 mbpd (see Table I below).

Fig 1.- World production (EIA data). Blue lines and pentagrams are indicating monthly maximum. Monthly data for CO from the EIA. Annual data for NGPL and Other Liquids from 1980 to 2001 have been upsampled to get monthly estimates.
| Category | MAR 2009 | MAR 2008 | MAR 2007 | 12 MA1 | 2009 (3 Months) | 2008 (3 Months) | 2007 (3 Months) | Share | Peak Date | Peak Value |
|---|---|---|---|---|---|---|---|---|---|---|
| All Liquids | 83.75 | 85.98 | 84.25 | 84.93 | 83.60 | 85.48 | 84.42 | 100.00% | 2008-07 | 86.65 |
| Crude Oil + NGL | 79.97 | 82.35 | 80.92 | 81.14 | 79.79 | 81.73 | 80.96 | 95.49% | 2008-07 | 82.88 |
| Other Liquids | 3.78 | 3.63 | 3.33 | 3.79 | 3.81 | 3.75 | 3.45 | 4.51% | 2008-11 | 3.89 |
| NGPL | 7.97 | 8.06 | 7.95 | 7.89 | 7.86 | 7.93 | 7.96 | 9.52% | 2008-07 | 8.08 |
| Crude Oil + Condensate | 72.00 | 74.29 | 72.97 | 73.25 | 71.93 | 73.80 | 73.01 | 85.97% | 2008-07 | 74.80 |
| Canadian Tar Sands | 1.26 | 1.19 | 1.26 | 1.22 | 1.24 | 1.20 | 1.19 | 1.50% | 2007-08 | 1.35 |
Table I -
Production
estimate
(in millions of barrels per day (mbpd)) up to March 2009 taken from
the EIA website (International
Petroleum Monthly). 1Average
on the last 12 months. Canadian tar sands production numbers are from
the NEB and includes updagraded and
non-upgraded bitumen.
Business as Usual
- EIA's International Energy Outlook 2006, reference case (Table E4, World Oil Production by Region and Country, Reference Case).
- IEA total liquid demand forecast for 2006 and 2007 (Table1.xls).
- IEA World Energy Outlook 2008, see post here for details.
- IEA World Energy Outlook 2006 : forecasts for All liquids, CO+NGL and Crude Oil (Table 3.2, p. 94).
- IEA World Energy Outlook 2005 : forecast for All liquids (Table 3.5).
- IEA World Energy Outlook 2004 : forecast for All liquids (Table 2.4).
- A simple demographic model based on the observation that the oil produced per capita has been roughly constant for the last 26 years around 4.4496 barrels/capita/year (Crude Oil + NGL). The world population forecast employed is the UN 2004 Revision Population Database (medium variant).
- CERA forecasts for conventional oil (Crude Oil + Condensate?) and all liquids, believed to be productive capacities (i.e. actual production + spare capacity). The numbers have been derived from Figure 1 in Dave's response to CERA.

Fig 4.- Production forecasts assuming no visible peak.
PeakOilers: Bottom-Up Analysis
- Chris Skrebowski's megaprojects database (see discussion here).
- The ASPO forecast from April newsletter (#76): I took the production numbers for 2000, 2005, 2010, 2015 and 2050 and then interpolated the data (spline) for the missing years. I added the previous forecast issued one year and two years ago (newsletter #58 and #46 respectively).
- Rembrandt H. E. M. Koppelaar (Oil Supply Analysis 2006 - 2007): "Between 2006 and 2010 nearly 25 mbpd of new production is expected to come on-stream leading to a production (all liquids) level of 93-94 mbpd (91 mbpd for CO+NGL) in 2010 with the incorporation of a decline rate of 4% over present day production".
- Koppelaar Oil Production Outlook 2005-2040 - Foundation Peak Oil Netherlands (November 2005 Edition).
- The WOCAP model from Samsam Bakhtiari (2003). The forecast is for crude oil plus NGL.
- Forecast by Michael Smith (was at the Energy Institute, now works for EnergyFiles) for CO+NGL, the data have been taken from this chart in this presentation (The Future for Global Oil Supply (1641Kb), November 2006.).
- PhD thesis of Frederik Robelius (2007): Giant Oil Fields - The Highway to Oil: Giant Oil Fields and their Importance for Future Oil Production. The forecasts (low and high) are derived from this chart.
- Forecast by TOD's contributor Ace, details can be found in this post.
- The forecast by Duncan and Youngquist made in 1999, see also this post by Euan Mearns.

Fig 5.- Forecasts by PeakOilers based on bottom-up methodologies.
PeakOilers: Curve Fitting
The following results are based on a linear or non-linear fit of a parametric curve (most often a Logistic curve) directly on the observed production profile:- Professor Kenneth S. Deffeyes forecast (Beyond Oil: The View From Hubbert's Peak): Logistic curve fit applied on crude oil only (plus condensate and probably excluding tar sand production) with URR= 2013 Gb and peak date around November 24th, 2005.
- Jean Lahèrrere (2005): Peak oil and other peaks, presentation to the CERN meeting, 2005.
- Jean Lahèrrere (2006): When will oil production decline significantly? European Geosciences Union, Vienna, 2006.
- Logistic curves derived from the application of Hubbert Linearization technique by Stuart Staniford (see this post for details).
- Results of the Loglet analysis.
- The Generalized Bass Model (GBM) proposed by Prof. Renato Guseo, I used his most recent paper (GUSEO, R. et al. (2006). World Oil Depletion Models: Price Effects Compared with Strategic or Technological Interventions ; Technological Forecasting and Social Change, (in press).). The GBM is a beautiful model that has been applied in finance and marketing science (see here for some background). The estimation in Guseo's article was based on BP data from 2004 (CO+NGL).
- The so-called shock model proposed by TOD's poster WebHubbleTelescope . You can find a description of his approach on his blog here as well as a review on TOD. The current estimate was done in 2005 based on BP's data (CO+NGL).
- The Hybrid Shock Model is a variant of the shock model described here. The forecast is based on EIA data (up to 2006) for crude oil + condensate, the ASPO backdated disovery curve and assumes no reserve growth and declining new discoveries.

Fig 6.- Forecasts by PeakOilers using curve fitting methodologies.
Forecast Performance
It is difficult to compare forecasts because they deal with different liquid category and have different baseline. The forecasts were evaluated using the Mean Asolute Scaled Error (MASE) proposed by Hyndman and Koehler [1]. A good forecast will have a MASE value less than 1 (i.e. better performance than a simple naive forecast). We can notice than some MASE curves are decreasing with time indicating that their predicted values are getting more accurate further in time.


Fig. 7. - MASE values as a function of the forecast horizon.
| Forecast | Date | 2006 | 2008 | 2009 | 2010 | 2015 | MASE2 | Peak Date | Peak Value |
|---|---|---|---|---|---|---|---|---|---|
| All Liquids | |||||||||
| Observed (All Liquids) | 84.54 | 85.48 | 83.60 | NA | NA | 2008-07 | 86.65 | ||
| IEA (WEO) | 2004 | 83.74 | 87.08 | 88.74 | 90.40 | 98.69 | 0.39 | 2030 | 121.30 |
| IEA (WEO) | 2005 | 85.85 | 89.35 | 90.98 | 92.50 | 99.11 | 0.64 | 2030 | 115.40 |
| Koppelaar | 2005 | 85.78 | 87.60 | 88.33 | 89.21 | 87.98 | 0.42 | 2011 | 89.58 |
| Lahèrrere | 2005 | 84.47 | 85.87 | 86.46 | 86.96 | 87.77 | 0.20 | 2014 | 87.84 |
| EIA (IEO) | 2006 | 84.50 | 88.23 | 90.00 | 91.60 | 98.30 | 0.65 | 2030 | 118.00 |
| IEA (WEO) | 2006 | 85.10 | 88.17 | 89.73 | 91.30 | 99.30 | 0.68 | 2030 | 116.30 |
| CERA1 | 2006 | 89.52 | 93.75 | 95.34 | 97.24 | 104.54 | 1.89 | 2035 | 130.00 |
| Lahèrrere | 2006 | 84.82 | 87.02 | 87.99 | 88.93 | 92.27 | 0.46 | 2018 | 92.99 |
| Smith | 2006 | 87.77 | 94.38 | 96.98 | 98.94 | 98.56 | 0.39 | 2012-05 | 99.83 |
| IEA (WEO) | 2008 | 83.15 | 85.51 | 86.80 | 88.15 | 94.40 | 0.63 | 2030 | 106.40 |
| Crude Oil + NGL | |||||||||
| Observed (EIA) | 81.25 | 81.73 | 79.79 | NA | NA | 2008-07 | 82.88 | ||
| Duncan & Youngquist | 1999 | 83.93 | 83.55 | 82.90 | 81.65 | 73.47 | 0.11 | 2007-01 | 83.95 |
| Population based | 2004 | 79.73 | 81.58 | 82.50 | 83.42 | 88.01 | 0.33 | 2050 | 110.64 |
| GBM | 2003 | 76.27 | 76.20 | 75.87 | 75.30 | 67.79 | 0.17 | 2007-05 | 76.34 |
| Bakhtiari | 2003 | 80.89 | 80.24 | 78.94 | 77.64 | 69.51 | 0.17 | 2006 | 80.89 |
| ASPO-46 | 2004 | 80.95 | 80.59 | 80.31 | 80.00 | 73.77 | 0.12 | 2005 | 81.00 |
| ASPO-58 | 2005 | 82.03 | 84.05 | 84.74 | 85.00 | 79.18 | 0.53 | 2010 | 85.00 |
| Staniford (High) | 2005 | 77.92 | 78.63 | 78.86 | 79.01 | 78.51 | 0.18 | 2011-10 | 79.08 |
| Staniford (Med) | 2005 | 75.94 | 75.91 | 75.76 | 75.52 | 73.00 | 0.30 | 2007-05 | 75.98 |
| Staniford (Low) | 2005 | 70.13 | 69.20 | 68.60 | 67.92 | 63.40 | 0.64 | 2002-07 | 70.88 |
| IEA (WEO) | 2006 | 81.38 | 83.96 | 85.24 | 86.50 | 92.50 | 0.72 | 2030 | 104.90 |
| Koppelaar | 2006 | 82.31 | 85.60 | 88.03 | 91.00 | NA | 1.20 | 2010 | 91.00 |
| Skrebowski | 2006 | 81.97 | 85.14 | 86.76 | 87.95 | NA | 1.01 | 2010 | 87.95 |
| Smith | 2006 | 82.81 | 88.27 | 90.58 | 91.95 | 88.60 | 0.34 | 2011-02 | 92.31 |
| Loglets | 2006 | 82.14 | 83.74 | 84.29 | 84.65 | 83.26 | 0.14 | 2012-01 | 84.80 |
| ASPO-76 | 2006 | 79.00 | 85.06 | 88.49 | 90.00 | 85.00 | 1.11 | 2010 | 90.00 |
| Robelius Low | 2006 | 82.19 | 82.35 | 81.92 | 81.84 | 72.26 | 0.39 | 2007 | 82.50 |
| Robelius High | 2006 | 84.19 | 89.27 | 91.65 | 93.40 | 92.40 | 2.11 | 2012 | 94.54 |
| Shock Model | 2006 | 80.43 | 79.51 | 78.93 | 78.27 | 73.74 | 0.37 | 2003 | 81.17 |
| EWG | 2007 | 81.00 | 79.79 | 79.00 | 78.06 | 69.21 | 0.41 | 2005 | 81.39 |
| IEA (WEO) | 2008 | 79.80 | 81.59 | 82.49 | 83.40 | 87.40 | 0.71 | 2030 | 95.00 |
| Crude Oil + Lease Condensate | |||||||||
| Observed (EIA) | 73.46 | 73.80 | 71.93 | NA | NA | 2008-07 | 74.80 | ||
| ASPO-46 | 2004 | 72.56 | 71.89 | 71.47 | 71.00 | 63.55 | 0.20 | 2005 | 72.80 |
| Deffeyes | 2004 | 69.92 | 69.64 | 69.37 | 69.01 | 65.98 | 0.17 | 2005-12 | 69.94 |
| ASPO-58 | 2005 | 73.80 | 75.39 | 75.89 | 76.00 | 69.50 | 0.44 | 2010 | 76.00 |
| IEA (WEO) | 2006 | 71.78 | 73.76 | 74.74 | 75.70 | 80.30 | 0.38 | 2030 | 89.10 |
| CERA1 | 2006 | 76.89 | 80.35 | 81.58 | 82.29 | 83.83 | 2.00 | 2038 | 97.58 |
| ASPO-76 | 2006 | 72.10 | 75.74 | 77.47 | 78.00 | 72.00 | 0.75 | 2010 | 78.00 |
| HSM | 2007 | 73.56 | 73.40 | 73.16 | 72.82 | 69.53 | 0.28 | 2006 | 73.56 |
| Ace | 2007 | 73.48 | 72.18 | 69.77 | 66.96 | 58.47 | 0.12 | 2006-01 | 73.55 |
| IEA (WEO) | 2008 | 69.73 | 70.64 | 71.06 | 71.46 | 73.00 | 1.07 | 2030 | 75.20 |
Are We There Yet?
We can consider two competitive models for the crude oil + NGL production:
- M0: The oil production will continue to grow with the world population at a constant rate of 4.3 barrels per capita.
- M1: The production will fall according to the average peak oil forecast.

Fig. 8 - Likelihood ratio (M1/M0) at the left and Statistical significance of observed production levels according to M0 (the red circle is March 2009).
Previous Update:
August 2008[1] Rob J. Hyndman, Anne B. Koehler, Another look at measures of forecast accuracy, International Journal of Forecasting, Volume 22, Issue 4, October-December 2006, Pages 679-688. pdf available here.




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