A Nice Counterexample

Nick Rouse kindly provided me with an Excel spreadsheet with a Hubbert linearization of UK oil production (the only thing I added was the yellow line). As you can see, there was a long period when the curve looked linear and yet it would have totally misled you had you simply extrapolated it to the axis. You would have thought there was going to be about 11gb, but now it's headed for 28gb. So, things are more complex, and we must see if we can come up with some principle for dividing the Romanias (where this method seems to have worked with amazing success), from the UKs (where it would have been very misleading) before we can feel any confidence in our extrapolation of the Saudi graph or the world graph. More below the fold.

This is intriguing - generally the UK is the poster child for the scariness of peak oil because it has had such high depletion rates recently. But just when we were getting used to it as a reliable method of scaring disobedient children into compliance, here it is messing up our nice simple-minded Hubbert theory. The basic problem becomes quickly clear when we look at the production versus time curve here:

This is referenced from here. Clearly, production initially looks like a nice Hubbertian single peak, but then, whoops, a bunch more oil from somewhere is produced. And the initial (pink) straight line above only knows about the first peak, so when we get this second, superimposed peak it is not accounted for. However, we do go linear again, just with a different (yellow) line going to a much higher URR (28gb versus 11gb).

Clearly, we are likely to run into the same general kind of problem with Russian production, where James Williams shows:

So now we need to know why did production not follow the same kind of general pattern that has worked so well for Texas, the US, or Romania? In the Russian case, it's reasonably clear what happened: society collapsed. Douglas Reynolds has argued, fairly plausibly, that the collapse was caused by the beginning of depletion in Russian oil production, but even if so, the decline would certainly have been greatly exacerbated by the resulting societal collapse. A lot of industry ground to a total halt, GDP was halved, life expectancy was sharply reduced, and the population declined. The subsequent partial recovery in production just goes to show that a societal collapse can actually cause oil production to drop even faster than geology alone dictates. At least, this is clearly so for communist economies: whether the lesson extends to capitalist economies could probably be (fiercely) argued both ways.

In the UK case, economists will quickly be tempted by the idea that oil prices had something to do with it, since the second peak starts to go up again in 1993, a couple of years after the price spikes of the first gulf war. However, it's pretty clear that price does not cause too much deviation from the basic Hubbert model in the US or Romanian case, so we would be left trying to explain why price matters greatly in some places but not in others (especially challenging in the US, center of the free market religion). So this explanation doesn't seem too tempting to me (price seems to explain some of the noise about the basic Hubbert curve, but not the gross features of the shape of the curve).

Nick notes that Jean Laharrere has considered the possibility of discovery as an explanation. Here's Laharrere's figure plotting UK backdated discovery and production:

Clearly, we can see that this bimodal discovery curve looks like a good explanation of the bimodal peak in production. A lot of discovery initially occurs in the late sixties and seventies, and this powers production in the late seventies and eighties. But there's a second wave of discovery beginning after 1980, and this powers the second peak. There's not much of a third wave of discovery, so there seems limited prospect for much relief in UK depletion rates soon.

It's interesting to contrast the situation with that in the US. Laharrere again:

This time we have cumulative production plotted versus time. Pretty clearly, the nice sigmoidal logistic discovery gives a sigmoidal production curve 30 year later. What's different in the North Sea is that production comes on stream much faster - production is following discovery by only a decade or so, rather than three decades. Clearly the world was in rather a hurry to get that oil by this point in history (after the oil shocks of the seventies).

So, here's a new tentative working hypothesis:

Hubbert linearization is a decent approximate model for oil production unless production is interrupted by a societal collapse, or production is very closely following on the tails of a very noisy discovery curve.
Clearly, further investigation is needed to support or refute this working hypothesis. In particular, if anyone knows or discovers other countries where linearization works well, or where it fails for different reasons, I'd love to hear about it. Hopefully our resident sceptics will go do some work and come up with some more evidence. But my final thought for tonight is just to look again at the Saudi situation.

Now the discovery picture there is somewhat unclear since we have wildly conflicting information about what their reserves really are. But Laharrere plots a variety of opinions:

Everyone agrees that all the discovery happened a long time ago - 90% of it was before 1970, and two thirds of it was before 1960. So it seems to me that our tentative hypothesis would suggest that linearization should work decently for Saudi Arabia (unless they were to collapse - never to be ruled out in the Middle East). The implications of linearization being pretty much true for Saudi Arabia again:

180gb of URR with 110gb produced already!

Stuart, thanks for posting this.  Your work has greatly clarified
(at least for me ) the proper role of Hubbert analysis.
That graph is interesting. Unfortunately, it does not account for the huge tax increases on the oil industry introduced by the Chancellor of the Exchequer two or three years ago. With a lingering threat of windfall profits taxes.

Those additional taxes made the UK, already a high priced exploration and production market (due to the environmental and regulatory climate) a difficult place to justify investment dollars. Big oil investment dollars go to the lowest risk/reward regions of the world. That is why offshore West Africa has exploded in production the last 5 years. Biggest bang for the buck.

Norway's depletion can be viewed in the same way. It is by far the most restrictive place to drill on the planet. We know where the oil and gas is. It is currently not economically viable, given the restrictions in Norway, to drill there.

West Africa is one notch short of a war zone. It's a place no rational business person would set up shop without an incredibly good reason. The "risk" part of the "risk/reward" tradeoff is obviously huge (as in Nigeria in the last couple of weeks). So that suggests prospects are worse elsewhere right?
No, it suggests that West Africa is one of the few places where oil hasn't been nationalized.
OK, but why is nationalizing oil a Bad Thing, from this point of view?

If I understand correctly, it's because governments don't invest in enough capacity to get the oil out of the ground fast.

Why not?

  1. Governments are fundamentally corrupt and inefficient.

  2. They know peak oil is coming, so they want to save it for later.

  3. ???
Good point. I personally believe that nationalized oil is a good thing because it leaves oil in the ground for later, causes higher prices, and will make the peak more of a plateau and gentle decline. If the OPEC governments could only be a little more incompetent and inefficient... then I'd be really happy!
I don't doubt depletion but I have a problem with the usefulness of Hubbert linearization. Take an oilfield that produces 1 (mbd) for ever. In a spreadsheet put 1 to 100 in column A. That's cumulative production. In B1 put =1/A1 and expand down to B100. That's annual production over cumulative production.  Now chart it.

What you get is an asymptote that always starts at 1 (first year production/cumulative) and approaches the x axis but never gets there.

The chart for the UK and many others looks more like the chart for a `perpetual' oil field than a straight line. There aren't enough data points to distinguish between them so either could be true.

In your example, you don't get a straight line. It only looks approximately straight because of the large scale caused by the first few points.

So what you've discovered is that not all curves produce a straight line at all. In fact this seems to strengthen, not weaken the theory slightly, since the curve you identified that doesn't produce a straight line is also impossible in real life.

Chris

So fit that to the production curve to the most mature regions we have data for (like the US or Romania). It will suck - they don't look like hyperbolae. In general, for all you guys that want to propose other kinds of model - great, more power to you. But no-one's going to pay much attention to you unless you can show your model actually does a good job for some reasonable class of production regions. The reason Hubbert's model is famous is precisely because it has that property.

But no-one's going to pay much attention to you unless you can show your model actually does a good job for some reasonable class of production regions. The reason Hubbert's model is famous is precisely because it has that property.

It obviously doesn't do a good job for the world as a whole -- as demonstrated by Colin Campbell's failed predictions.

The only value which the linearization method might have is its ability to predict peak oil. Now, IIRC, Deffeyes predicts peak oil for Thanksgiving Day 2005 based on the linearization method, so that's the reality check.

Also, the method isn't objective until you specify an objective algorithm for selecting the line, and apply it uniformly in all cases. Otherwise, it's just subjective voodoo.

Actually, Campbell wasn't using the linearization method I don't think - I believe he was sticking in an explicit URR and constraining his fit to that. I wouldn't do that since our knowledge of reserves sucks. Our knowledge of production is imperfect (the different authorities differ as to the production numbers- maybe the Joint Oil Data Initiative is going to help here), but it's better than reserves.

I agree with you that the predictions of the world peak are a good check. However, Deffeyes used a particular oil data series (and I don't actually know which one!), and it's only fair to do comparison to whatever series he was fitting too. Also, obviously there's significant noise, so it could well be off by a few years either way (as it was for the US). But I don't believe it's going to be decades off. We need to get to some error analysis here soon to tighten that up (but one thing at a time).

I still say that, on a linear scale, aP/CP plotted against CP will naturally follow something more like y=1/x than a line, thus making your predictions of 'zero' a little shy of the mark.
I agree. That UK graph reminds me of half-life decay in radioactive isotopes. I think a non-linear fit might give better predictive value.
But empirically that works very badly for the US, Romania, Norway, etc. So it doesn't seem interesting to push that model further.
I agree with the other commenters, you have to slow way down on this analysis.  I think you are violating Occam's razor by attributing something complicated and not physically possible (i.e. the logistic model) to something that can be explained away much more simply.

The more I look at it, the more I dislike plotting aP/CP against CP. I once was told a story long ago by my father who described going to a talk by another engineer who was very excited about this great correlation he found in his data set.   The data points were very well aligned, all falling along a straight line. Well, as it turned out, the engineer had plotted X against X!  

And that is part of the problem. We ought to not contaminate one already dependent variable onto the axis of the other variable -- unless you are relatively sure that this fits some realistic behavior (c.f. the "drunk looking for his keys under the streetlight" scenario).  And I think the non-linear behavior we consistently see rules out the logistic model.

I have a post up describing the quasi-hyperbolic behavior that likely fits better here:
http://mobjectivist.blogspot.com/2005/09/oil-shock-model.html
and a more recent post showing how the math also describes the behavior of a simple electical RC circuit here:
http://mobjectivist.blogspot.com/2005/09/rc-circuit-analogy.html

But I also have to agree that the extra bump provided by new discoveries in North Sea oil tends to once again flatten out the slope. After all, every earlier discovery accomplished the same thing!

And don't take this criticism wrong. If you tried publishing this in any scientific journal as I and many others are accustomed to, you will have to be prepared to go through the ringer in your analysis. It's just that referees are much less common on the internet than in academic circles, as it doesn't come with the job description and it won't help anybody get tenure.

There's nothing physically impossible about the logistic model. It's obviously a simplification, but any model of an entire civilization is going to be a simplification. My perspective in such a situation is the more parameters we throw at it, the worse our predictions will be. You obviously differ, as you have a perfect right to do. I find your approach less persuasive than Hubbert's. I suggest you try it on partial histories for Romania or the US and see if you would have predicted the rest of the data better than the Hubbert linearization. If you can, that would get me to sit up and pay attention.

I have significant experience getting modeling work published in scientific fora, some of which has been very influential - scholar.google me for details. But these posts are work in progress (as I think should be obvious). No doubt publication will eventually follow when I think I have the story figured out to my own satisfaction.

Er, ok.  Looking at how you have been using the logistic model in the past --as a variant of the "pedator-prey" class of processes-- I think your modeling premise will have greater viability when applied to another pressing issue of today, that of the potential spread of avian flu. That is, if it firmly takes hold as some of the epidemiologists predict.

So is that really how Hubbert, Deffeyes, and others set up the  original peak oil math? By using a "predator-prey" model? Oh my, no wonder that people like Michael Lynch and company are having a field day in dissembling these kinds of models. It's common practice in those circles to simply trash another's model (i.e. policy); Lynch then doesn't even have to come up with his own.  Look at how well this strategy works in today's political circles.

Yes, the logistic equation is used in epidemiology - they call it the SI model (S=susceptible, I=infected). Essentially it is a model which is potentially applicable to any situation in which some initially exponentially growing process uses up some finite resource - whether it's a biological disease infecting a vulnerable population of animals, a computer worm using up a vulnerable population of computers, a new product spreading through a potential market, a new piece of information spreading through a financial market, or a civilization using up a finite pool of oil.

Fundamentally, it is an empirical question whether or not the model applies to oil production. No-one would claim it's going to be a perfect fit (or no-one with any sense, anyway!) but it has done a reasonably decent job in the very mature production areas (but not in the early stages). Stare at Romania again:

But there are certainly regions where it could mislead you without care (eg the UK). I'm engaged in trying to develop insight into where we might expect it to work, and where we might not.

As to Lynch et al. Critics serve a very valuable purpose in noting the holes and driving the improvements that need to be made. However, it's always much easier to criticise than make some constructive proposal oneself. No-one remembers the critics - they remember the people who make developments that actually improve the state of the art. Hubbert will be remembered far longer than Lynch, even though I respect Lynch as Hubbert's best critic: he has done some actual hard work and made critiques that serve a useful purpose.

And again - if you can develop a better model, more power to you. But the proof of that is showing that you can predict forward with smaller residuals for a broader class of situations.

For Romania, say they had a single oil strike some time in the past. Therefore, the forcing function looks like a delta function, and the solution set is just the exponential function if you assume production is proportional to the amount remaining (i.e. the stripper well scenario). Then when you plot dQ/dt/Q vs Q you get exp(-kt)/(1-exp(-kt)) plotted vs (1-exp(-kt)). In the regime where the logistic graph appears linear and it gets close to 90%, so does the exponential. And the match gets better if you put a bit of a spread in the delta function. Therefore you cannot tell the difference and the exponential model wins out because it matches a real physical process.

I don't respect Lynch at all. I agree with many people that think he is intellectually dishonest.

The logistic will start working before peak, the exponential decline will only start working after peak (eventually, they look identical, as you note).
No, the logistic model does not work before the peak. It looks very susceptible to initial conditions. Looking right does not mean it is right.

The exponential model works over every regime. It just needs a  forcing function to create a spread in starting points.

Re: "Yes, the logistic equation is used in epidemiology - they call it the SI model (S=susceptible, I=infected). Essentially it is a model which is potentially applicable to any situation in which some initially exponentially growing process uses up some finite resource..."

VERY interesting.... Write a post about this.

No, you didn't. What I meant was the meaning of the linearization function in different domains (oil production, epidemiology, etc.), the intuitive generalization of the model in different domains. If this model has general applicability, then demonstrate it. Show that future oil production is modeled in the same way as the spread of the 1918 flu virus (in the worse case). What you have never expressed is the intuition behind the model. This is important.
The problem is that there is nothing exponentially growing. There is a cumulatively growing set of tapped reserves, which takes work and time to find. This is offset by a depletion activity which is proportional to the amount of oil in each new reserve tapped. Unfortunately this does not describe the logistic model, which is more suited to the epidemiological and ecological sciences, and also to some fairly arcane chemical growth models that I did my thesis work on in the 80's.  Trust me, no way does this model work for oil depletion. It just happens to give an empirical fit. And people have started building heuristics around this model. Bad idea.

Now knowing what the basis of the logistic model was before today, I keep wanting to imagine little Pac-man oil molecules gobbling each other up.  I will probably have nightmares over this tonight.

There is something (very roughly) exponentially growing - the amount of information, capital, equipment, etc applied to the region - go read the Mineral Economy.. Whether you like it or not, you are modeling a social process interacting with a physical process - both in the finding of the oil, in how quickly people choose to develop it, and in what kind of technology they apply to the extraction process (horizontal wells at the top of the oil layer are not likely to lead to an exponential dropoff, for example). Again, you can complain all you like, but until you show me your lower residual fits to a broad range of situations, you don't have anything. I at least am weary of discussing it with you for now since we do not seem to making any progress. Come back with your superior fits to the data.
In the logistic equation, you use the term "a" and "1-a" to refer to a quantity and its complement. Now you want to use "a" to refer to some some economic scalar that grows exponentially, while "1-a" to refer to the oil reservoir itself. That makes absolutely no sense from a mathematical point of view, as in mixing apples and oranges.  Unless someone establishes a physical relationship between "a" and "1-a", I wouldn't go near solving this equation. And if there were a relationship, it might not be linear.  In that case, the tidyness of the solution evaporates.

In the normal predator-prey relationships, you can get away with this stuff because you are ony dealing with discrete entities that have at least an empirical relationship. For example, it takes N rabbits to sustain a single fox. Or one virus to infect one unprotected computer. Or an anion and a cation to generate a molecule. But where does this relationship come up here?  

I meant to say superior predictions - you can always get superior fits by overfitting - the test is can you predict forward from partial histories with lower residuals.
Great post! thanks! so if I understand correctly, a discovery curve with a heavy tail will probably produce a multi-peak production curve which requires two separate Hubbert models. In the case of SA, there are a lot of very different estimates for the discovery curve. Too bad the graphic on SA shows only cumulative discoveries. It looks like that the UK discovery curve is a mixture of a gaussian centered on 1975 and a uniform distribution modeling the heavy tail.
There is a very simple explanation for the apparent conflict--time.  The other examples--especially Texas, Saudi Arabia and now the world--didn't enter the linear phase until the regions had decades, at least 20 to 30 years, of serious production.  

Note that the initial UK peak was only about 10 years after the onset of serious oil production.  This would be analogous to just looking at Texas data from 1935 to 1945.   If you just focused on 1935 to 1945, the plot of Texas data would have given you a similarly erroneous result.  Hubbert made his Lower 48 prediction about 27 years after the East Texas Field was discovered.

The answer to the apparent conflict is that the initial data points don't provide sufficient data to make an extrapolation.  

Again, in my opinioin this technique works in the real world because--after decades of drilling--the industry has a pretty good idea of where the big fields are.  

Jeffrey J. Brown

I agree completely. The UK North Sea was a very immature oil province. We should not expect another non-linear departure to happen there again. We might expect similar results for Angola (production started in about 1980 and off-shore is now in development). But we'll have to wait some years to see those results. Only recently developed regions will have noisy discovery curves at this point. Sudan is another example.
The drop in UK oil production in 1988 was caused by the Piper Alpha fire. IIRC they delayed further exploration and production for some time aftr that while they dealt with safety and enviromental issues.
The Piper Alpha Fire was in June 1988 by that time
monthly production had already fallen by 25%
over its peak in January 1985.  It undoubtedly
caused a direct loss in production but any losses due
to a reduction in exploration would have shown up
10 years or so later about 1998 when production
was near its second peak
Um, doesn't "near its...peak" imply that losses are showing up?
You could make a case that part of the drop after 2000 was due to the drop in exploration after the Piper Alpha fire in 1988 but Alun was suggesting that the drop in 1988 and immediately after was due to this.

Dave suggested that he would not expect another non-linear deviation but this is not sure.

Contrary to what Mad Oilman suggested, In 2003 the Chancellor of the Exchequer, Gordon Brown announced tax changes in favour of North Sea exploration. See:-
http://www.ukbudget.com/prebudget2003/Prebudget2003_companies.cfm
and this has resulted in a fair boost in exploration. See:-
http://thescotsman.scotsman.com/business.cfm?id=102472005

There are still forecasts that production will rise for a couple of years before starting to decline again although some only hope that it will slow the decline down. Whether this will happen to any large extent is open to doubt. There are some very interesting graphs here:-
http://www.worldoil.com/Magazine/MAGAZINE_DETAIL.asp?ART_ID=2655

Fig 1 shows the modest increase in the number of exploration and appraisal wells that have been dug (not including the expected increase in 2005 given in the Scotsman reference). However fig 3 shows the strong decline in the success rate of exploratory wells dropping from 43% or so for much of the 1980's to 20% in 2004. It would be interesting to see comparable figures for other parts of the world.

The forecast part of the production figures in Fig 3 seems optimistic in the near term as the show a slight increase in 2005 and output has fallen 17.5% in the  first 5 months of this year
 


LE MONDE: the end of oil, a well kept secret

...According to the article, the big players use two main sources to evaluate reserves worldwide: the Oil & Gas Journal, which sends a yearly questionnaire to governments of oil producing countries, and publishes their (unconfirmed) replies, and IHS Energy, a Houston consultancy, which publishes a confidential database - the problem is that it's so confidential that even the price of the information is not public, but is rumored to be more than a million dollars... Total, which has access to the database, notes that the two sources come up with similar overall numbers (OGJ has 1,266 billion barrels of "probable reserves" from 94 countries, and IHS has 1,152 from 114 countries), but that each line (country per country) is pretty different...

...The article states that in a recent meeting with political leaders, Thierry Desmarets, the boss of French major Total, said that peak oil would happen around 2025, provided that there is a demand shock. Which means, obviously, that if we do not curtail our demand, the peak will be much earlier. This is very much compatible with the scenarios drawn by APSO's Jean Laherrère and Saudi Aramco's Al-Hussieni, who both expect that production will plateau very soon, with a bumpy ride on such plateau, marked by various shocks and price volatility. Laherrère expects the final decline by 2015, while Al-Husseini sees it closer to 2030...

Jerome a Paris at

http://www.dailykos.com/story/2005/10/1/81515/3020

Regarding SA. Consider the fact that SA had extra production capacity for many years. They may have kept on discovering new reserves without bothering to invest in the infrastructure to tap the new discoveries. Is this claim possible? What would it do to the linearization if SA suddenly decides to develop those fields and increases their annual output?

I read that actual oil production costs are around $0.50 to $1.50 per barrel. Is this true? If so, then tapping smaller 'more expensive' fields after the giant SA fields begin dwindling would raise the price to what? Even $3 to $8/barrel wouldn't really impact current prices. Am I missing something?

H

While I'm sure there are going to be a lot of great responses that go well beyond what I'm about to say, here are the two biggest concerns I have about SA production.
#1 They have peaked in light sweet production (according to their own journal) which means additional production increases will only come in the form of heavier, sourer grades that are harder to refine, etc.
#2 The infrastructure to drill the wells, build the pipelines, etc. is just not nearly as far along as in the US. If we want to lay down a ton of wells, etc. in a field, there are all sorts of people to do it. For most of SA production history the oil has been flowing from a relatively small number of wells considering the size of the fields.

And I'm also loathe to believe that the recent upward reserve revisions are based in anything remotely approaching reality.