Hubbert Linearization

Hubbert Linearization

The Hubbert Linearization is a way to plot production data in order to estimate two important parameters of a Hubbert curve; the logistic growth rate and the quantity of the resource that will be ultimately recovered. The Hubbert curve is the first derivative of a Logistic function, which has been used in modeling depletion of crude oil, predicting the Hubbert peak, population growth predictionscite web | url = http://arts.bev.net/roperldavid/WorldPop.htm | title = Projection of World Population | first = David | last = Roper] and the depletion of finite mineral resourcescite web | url = http://www.roperld.com/minerals/metalgon.pdf | title = Where Have All the Metals Gone? | first = David | last = Roper|format=PDF] . The technique was introduced by Marion King Hubbert in his 1982 review paper "Techniques of Prediction as Applied to the Production of Oil and Gas", in the collection Oil and Gas Supply Modeling, edited by Saul I. Gass (published as NBS Special Publication 631)] . The geologist Kenneth S. Deffeyes has recently applied this technique in order to make a prediction about the peak production of conventional oil cite book |last= Deffeyes |first= Kenneth |authorlink=http://www.princeton.edu/hubbert/index.html |coauthors= |title=Beyond Oil - The view from Hubbert's peak |date= February 24, 2005|publisher= Hill and Wang|location= |isbn=978-0809029563 ] .

Principle

The first step of the Hubbert linearization consists of plotting the production data (P) as a fraction of the cumulative production (Q) on the vertical axis and the cumulative production on the horizontal axis. This representation exploits the linear property of the logistic differential equation:

: frac{dQ}{dt}=P=KQleft(1 - frac{Q}{URR} ight) qquad mbox{(1)} !

where "K" and "URR" are the logistic growth rate and the Ultimate Recoverable Resource respectively. We can rewrite (1) as the following:

: frac{P}{Q}=Kleft(1 - frac{Q}{URR} ight) qquad mbox{(2)} !

The above relation is a line equation in the "P/Q" versus "Q" plane. Consequently, a linear regression on the data points gives us an estimate of the slope and intercept from which we can derive the Hubbert curve parameters:
* the "K" parameter is the interecpt with the vertical axis.
* the line slope is equal to "-K/URR from which we derive the URR" value.

Examples

US Oil Production

The chart on the right gives an example of the application of the Hubbert Linearization technique in the case of the US Lower-48 oil production. The fit of a line using the data points from 1956 to 2005 (in green) gives a URR of 199 Gb and a logistic growth rate of 6%.

World Population


Criticisms

Alternative Techniques

econd Hubbert Linearization

The Hubbert linearization principle can be extended to the second derivativescite web | author=Khebab | title=A Different Way to Perform the Hubbert Linearization | publisher=The Oil Drum | date=2006-08-18 | work= | url=http://www.theoildrum.com/story/2006/8/16/102942/337 | accessdate= ] by computing the derivative of (2):

: frac{dP}{dt}frac{1}{P}=Kleft(1 - 2frac{Q}{URR} ight) qquad mbox{(3)} !

the left term is often called the decline rate.

The Hubbert Parabola

This representation was proposed by Roberto Canogarcite web | author=Canogar, Roberto | title= The Hubbert Parabola | publisher=GraphOilogy | date=2006-09-06 | work= | url=http://graphoilogy.blogspot.com/2006/09/hubbert-parabola.html | accessdate= ] and applied to the oil depletion problem:

: P=KQ-frac{K}{URR}Q^2 qquad mbox{(4)} !

See also

References

External links

* [http://www.theoildrum.com/node/2389 Does the Hubbert Linearization Ever Work?] - The Oil Drum


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