The blue curve is the extraction-rate prediction. Note that, on the average, peak oil occurred at about 1995.
L. David Roper
http://arts.bev.net/roperldavid
24-Aug-2011
An interesting analyis of the effect of oil prices on financial markets. This paper inspired me to look at oil prices in a different way: It seems reasonable that the price of a non-renewable mineral will be an inverse power function of the amount left to be extracted (Q). I did such a fit to the price of crude oil in the first week of January since 1978 as shown below.
The amount of crude oil left to be extracted as a function of time, Q, for my best fit to the World extraction data & the discovery rate is given by the red curve here:
The blue curve is the extraction-rate prediction. Note that, on the average, peak oil occurred at about 1995.
The average price data for the first week in January fitted by a inverse power function of Q:
The equation of the curve is P = 11.4 + (3.82x1023)/Q7.39.
The prediction of the inverse-function fit for years up to 2020 is:
I expect that there will be fluctuations around the average curve, especially as panic sets in. For example, the price on 1 Jun 2009 was $126 and later that month it went as high as $140 or so. However, the price on 1 January 2009 was $93, which is the price used in this fit.
The prices fitted (blue dots in data above) are yearly 1 January prices, so the fit only prodicts prices for 1 January. You need to wait until the end of a year to get points to compare to the fit. (Since the price has been level at about $70 for the last several months, I assumed a price for 1 January 2010 of $70. Each year as the 1 January price is known, I can refit the curve to get a better prediction for future years.
Probably when world crude-oil extraction falls to about 1/2 of its peak, it will be realized by the market that we have to wean ourselves from oil. Renewable sources of energy and petroleum-like chemicals will replace oil. A possible scenario might be:
Such damping may also be influenced by the increase of electric transportation.
This curve was obtained by multiplying the function above by [1+tanh({t-2020}/10)]/2. I call this damping of crude-oil prices.
This result can be used to predict the future price of gasoline in the United States; it should be some power function of the price per barrel of crude oil. Here are those two prices:
A fit of the U.S. regular gasoline price (P) to the fit to crude-oil price (O) obtained above yields the power function
P =-0.011 + 0.22 O0.58:
The predicted U.S. regular gasoline price to 2020 is:
As more prices come in for future years, this fit can be done again to increase the accuracy of the predictions.
If the damping of crude-oil prices occurs as in the fourth graph above, the gasoline price might be similarly damped::
See the book $20 Per Gallon: How the Inevitable Rise in the Price of Gasoline Will Change Our Lives for the Better by Christopher Steiner
L. David Roper, http://arts.bev.net/RoperLDavid/; roperld@vt.edu