[savethehumans]

Deffeyes was Hubbert's protege. Maybe HE knows something? Anyone know how this guy could get ahold of him?

[tita]

Maybe a paper from Laherre presented at the last ASPO conference in Lisbon

ttp://www.cge.uevora.pt/aspo2005/abscom ... errere.pdf

[peaknik]

This is what you are looking for:

Our Petroleum Predicament

Originally a special editorial feature by GEORGE PAZIK Editor & Publisher, Fishing Facts, November 1976.

Very interesting read!

[2007]

The website 'oilcrisis' also has some links to Hubbert papers.

http://www.oilcrisis.com/hubbert/

[WebHubbleTelescope]

Transcribed article from mid-70's on Hubbert:
http://mobjectivist.blogspot.com/2005/0 ... ament.html

[rowante]

Thanks, peaknik and WHT that was it!

[rowante]

It really blows my mind that that article was published the year I was born.

Web Hubble Telescope, did you get in contact with the author, is he still around?

[WebHubbleTelescope]

It really blows my mind that that article was published the year I was born.

Web Hubble Telescope, did you get in contact with the author, is he still around?

As a matter of fact, I did have a short correspondence over a year ago with a fellow who posted to an outdoor sports bulletin board. I told him to pass on how much I appreciated Mr. Pazik's work and advocacy.

Name: Denny Payton
E-Mail:
Date/Time: 3/30/2004 1:06 PM
Message:

When George Pazik’s name came up recently, a couple fellows shared their appreciation for him. I had the opportunity to meet him over the phone yesterday, and was saddened to discover a weak 83-year-old man who was unable to put into words, everything he wanted to say. He’s had a long struggle with medical problems, and spent four years in a nursing home, I think just getting out recently. He said there’d been a period of time when he couldn’t walk, but that he can now, with the assistance of a walker. When I told him he was the one who introduced me to Buck Perry by an article in Fishing Facts, I could see that it really encouraged him.

Anyways, I have his mailing address, so if anyone would like to send him a note of encouragement or appreciation, please email me [email protected] and I’ll give it to you. I don’t think I should post it here. He could sure use it.

Thanks,

Denny Payton
Auburn, IN

I also corresponded with Prof. Al Bartlett at U. of Colorado and he said he remembers talking with Mr. Pazik very fondly.

I don't know what Mr. Pazik's current health status is but I wish him very well.

http://mobjectivist.blogspot.com/2004/0 ... facts.html

[chrispi]

I have found that using the Hubbert distribution to find the future price of oil yields three possibilities, if both human demand and oil supply follow Hubbert's distribution:

• The rate of population growth is equal to the rate of oil extraction. Then the price of oil follows an S shaped curve bounded above and below by finite limits, with the inflection point right around Peak Oil.
• The rate of population growth is greater than the rate of oil extraction. Then the price of oil follows a bell curve, getting ever more expensive until after Peak Oil, then getting cheaper again.
• The rate of population growth is less than the rate of oil extraction. Then the price of oil will fall exponentially until we reach Peak Oil, whereupon the price will rise exponentially.

I used the Mathematica program and its statistical packages. What do you think?

[EnergySpin]

I have found that using the Hubbert distribution to find the future price of oil yields three possibilities, if both human demand and oil supply follow Hubbert's distribution:

• The rate of population growth is equal to the rate of oil extraction. Then the price of oil follows an S shaped curve bounded above and below by finite limits, with the inflection point right around Peak Oil.
• The rate of population growth is greater than the rate of oil extraction. Then the price of oil follows a bell curve, getting ever more expensive until after Peak Oil, then getting cheaper again.
• The rate of population growth is less than the rate of oil extraction. Then the price of oil will fall exponentially until we reach Peak Oil, whereupon the price will rise exponentially.

I used the Mathematica program and its statistical packages. What do you think?

First of all you used the ONLY reliable piece of mathematical software on this planet.
The logistic curve is a well known population modeling tool.
If you search the pop bio literature you will see that it does not cupture the complexity of human population modelling (in particular the negaitve term might be realistic). And the relation between oil and population is really complex ... but then again I'm a moderate

[chrispi]

It's a simple model, I know, but sometimes simplicity is best when capturing the essence of price behavior.

If you look at the historical chart for oil prices you'll find that they went down exponentially for most of the twentieth century, ignoring price spikes like the Iran Crisis and the like. This agrees with the last model, where pop growth < oil extraction, which suggests that the price of oil will skyrocket in the coming decades, ignoring price spikes and collapses, of course.

[EnergySpin]

It's a simple model, I know, but sometimes simplicity is best when capturing the essence of price behavior.

If you look at the historical chart for oil prices you'll find that they went down exponentially for most of the twentieth century, ignoring price spikes like the Iran Crisis and the like. This agrees with the last model, where pop growth < oil extraction, which suggests that the price of oil will skyrocket in the coming decades, ignoring price spikes and collapses, of course.

Check the Verhulst thread .. we have done the exercise
How did you do the fitting with Mathematica?
I used Mathematica for the same application (- humans) ... hope you understand Nonlinear regression

[chrispi]

It's a simple model, I know, but sometimes simplicity is best when capturing the essence of price behavior.

If you look at the historical chart for oil prices you'll find that they went down exponentially for most of the twentieth century, ignoring price spikes like the Iran Crisis and the like. This agrees with the last model, where pop growth < oil extraction, which suggests that the price of oil will skyrocket in the coming decades, ignoring price spikes and collapses, of course.

Check the Verhulst thread .. we have done the exercise
How did you do the fitting with Mathematica?
I used Mathematica for the same application (- humans) ... hope you understand Nonlinear regression

Yeah Mathematica is awesome wrt statistical curve fitting. I used it on historical prices to find the correct logistic model (exponential decline followed by skyrocketing prices) which I obtained by graphing a simple division:

Plot[PDF[LogisticDistribution[humanpeak,humancoeff],t]/PDF[LogisticDistribution[oilpeak,oilcoeff],t],{t,tmin,tmax}]

The humanpeak, humancoeff, oilpeak, oilcoeff parameters were found using a nonlinear fit on historical data. The tmin and tmax parameters are of your choosing. Happy datamining!

[EnergySpin]

It's a simple model, I know, but sometimes simplicity is best when capturing the essence of price behavior.

If you look at the historical chart for oil prices you'll find that they went down exponentially for most of the twentieth century, ignoring price spikes like the Iran Crisis and the like. This agrees with the last model, where pop growth < oil extraction, which suggests that the price of oil will skyrocket in the coming decades, ignoring price spikes and collapses, of course.

Check the Verhulst thread .. we have done the exercise
How did you do the fitting with Mathematica?
I used Mathematica for the same application (- humans) ... hope you understand Nonlinear regression

Yeah Mathematica is awesome wrt statistical curve fitting. I used it on historical prices to find the correct logistic model (exponential decline followed by skyrocketing prices) which I obtained by graphing a simple division:

Plot[PDF[LogisticDistribution[humanpeak,humancoeff],t]/PDF[LogisticDistribution[oilpeak,oilcoeff],t],{t,tmin,tmax}]

The humanpeak, humancoeff, oilpeak, oilcoeff parameters were found using a nonlinear fit on historical data. The tmin and tmax parameters are of your choosing. Happy datamining!

Be careful with the Levenberg Marquadt and check the curvature measures of nonlinearity. Curve fitting these equations can be bitch

[chrispi]

It's a simple model, I know, but sometimes simplicity is best when capturing the essence of price behavior.

If you look at the historical chart for oil prices you'll find that they went down exponentially for most of the twentieth century, ignoring price spikes like the Iran Crisis and the like. This agrees with the last model, where pop growth < oil extraction, which suggests that the price of oil will skyrocket in the coming decades, ignoring price spikes and collapses, of course.

Check the Verhulst thread .. we have done the exercise
How did you do the fitting with Mathematica?
I used Mathematica for the same application (- humans) ... hope you understand Nonlinear regression

Yeah Mathematica is awesome wrt statistical curve fitting. I used it on historical prices to find the correct logistic model (exponential decline followed by skyrocketing prices) which I obtained by graphing a simple division:

Plot[PDF[LogisticDistribution[humanpeak,humancoeff],t]/PDF[LogisticDistribution[oilpeak,oilcoeff],t],{t,tmin,tmax}]

The humanpeak, humancoeff, oilpeak, oilcoeff parameters were found using a nonlinear fit on historical data. The tmin and tmax parameters are of your choosing. Happy datamining!

Be careful with the Levenberg Marquadt and check the curvature measures of nonlinearity. Curve fitting these equations can be bitch

Are you talking about skewness? (∫(x-m)^3 f(x)dx)

[EnergySpin]

It's a simple model, I know, but sometimes simplicity is best when capturing the essence of price behavior.

If you look at the historical chart for oil prices you'll find that they went down exponentially for most of the twentieth century, ignoring price spikes like the Iran Crisis and the like. This agrees with the last model, where pop growth < oil extraction, which suggests that the price of oil will skyrocket in the coming decades, ignoring price spikes and collapses, of course.

Check the Verhulst thread .. we have done the exercise
How did you do the fitting with Mathematica?
I used Mathematica for the same application (- humans) ... hope you understand Nonlinear regression

Yeah Mathematica is awesome wrt statistical curve fitting. I used it on historical prices to find the correct logistic model (exponential decline followed by skyrocketing prices) which I obtained by graphing a simple division:

Plot[PDF[LogisticDistribution[humanpeak,humancoeff],t]/PDF[LogisticDistribution[oilpeak,oilcoeff],t],{t,tmin,tmax}]

The humanpeak, humancoeff, oilpeak, oilcoeff parameters were found using a nonlinear fit on historical data. The tmin and tmax parameters are of your choosing. Happy datamining!

Be careful with the Levenberg Marquadt and check the curvature measures of nonlinearity. Curve fitting these equations can be bitch

Are you talking about skewness? (∫(x-m)^3 f(x)dx)

Nope ... the Verhulst or logistic growth equation estimation problem is extremely difficult if one does not have data after or at least after the peak. I'm not talking about the moment of the distribution, but about the subtleties of fitting nastily behaved curves ...
Link to curtosis (the measure suggested by Ratwovski is http://old-www.math.luc.edu/~tobrien/research/HOC.pdf)

[doufus]

What data? What source? What reliability? What effect does changing
technology have in the data? Can that even be modelled?

[EnergySpin]

What data? What source? What reliability? What effect does changing
technology have in the data? Can that even be modelled?

Data = crap
Source = sucks
Which means one has to rely on smoothing (at least that's what I did) of the production from BP review.
Changing technology is very interesting ... if one believes Simmons, it will not alter the URR . At first approximation (a very first approx) one may use the logistic growth understanding that the extraction rate will be an average.
But even when one uses simulated dataset, depletion of a resource following the curve is an absolute nightmare. Hence the various contradictory claims. Let the algorithm run one extra iteration and a whone new universe is revelaed before your eyes. So the solution is to assume that peak is about to happen and change lifestyle at the individual / societal level. With any luck the real peak will be in 2013 (as the French suggest) and not in 2006.
For the record I believe the peak will be between 2007-20010

[nero]

It sounds like you're curve fitting, not modeling. If you were proposing a model then you would be discussing the complex interactions between the price of oil, supply, demand and the economy.

Since extrapolating without a sound understanding of the underlying mechanisms is an inherently dangerous thing to do I rather think the curve fitting exercise is pretty bogus. Just my opinion, but go ahead have fun.

[jimmydean]

Interesting, hats off to you for attempting some mathematical model.

At this point though I do not think population is a key factor pre peak for determining oil price. Consumption rate per capita is the key one. Rate of growth of consumption by nation could be calculated from the EIA spreadsheets. For pre-peak make an assumption that supply has peaked or has 1-2Mbbl more capacity.

Post peak there just isn't enough data to predict price. Also there are so many geopolitical and economic factors that will come into play that it will be just a guess.

i.e. Consumption approx numbers based on EIA spreadsheets (2005 Q1 numbers)
China - 1 bbl of oil services 150 people/day
UK - 1 bbl of oil services 44 people/day
U.S. - 1 bbl of oil services 15 people/day

My non-mathematical take...

Pre-peak prediction:
If demand ~ supply before peak oil... assuming supply does not drop of a cliff due to extraction or refining issues or peak oil realization...
1. Oil price will steadily rise as demand ~ supply. (here now)
2.There will be price spikes due to supply issues (refining or extraction) that will force short-term conservation. (yet to experience conservation)
3. After enough price spikes consumption rates will adjust as people/governments react with longer term conservation strategies; personel conservation, government rationing (in some nations).
4. Wealthier nations will still be able to maintain consumption rates (albeit less than Q1 2005 type numbers) iff global economy remains robust. i.e. will the stock market fall off a cliff? will the U.S. dollar dive?

Post Peak Realization
Peak oil realization is a recognition that pure production is shrinking. Pre-peak conservation may ease the coming oil price spike but there will be a spike here. This is the point of global economic woes.
- Massive potential drop in demand may be offset by massive panic to secure remaining oil OR drop in demand brings prices down temporarily thereby giving us a temporal pre-peak feeling for nations that can afford the new price levels.
- global economic fallout is eventual