I will run that when I get a chance. My feeling is that it does converge, and the ideal production case will be a good test case.

Robert, a good article that points up some of my own misgivings about the reliance on HL. The wise words "don't use models the way a drunk uses a lamppost - use them for illumination, not support" comes back to me. The moment you rely without thinking and questioning is the moment you make that BIG mistake.

To me the whole thing is very much a case of 'the central limit theorum' - if you know nothing more then you can assume that the combination of independent distributions tends to a normal distribution (eg 'Peak Oil'). However we DO know something more - production is NOT independent and production levels/demand are significantly influenced by politics, prices, technology, social events, etc. Although to a first order it will be OK, we know the model cannot be taken beyond that because of all the influences upon it.

Does that mean peak oil is a joke (hello CERA)? No, the basics are still there. Oil is a finite resource and production will increase with increased usage, and decline with increase problems of production (smaller, harder wells). However to get to a useful prediction of reserves, dates, and most importantly, decline rates, we need a much better model - particularly since we have to make up for hidden data.

Some try to consider fields individually, summing the resultant predictions to arrive at a global production forecast, bottom up. Some also try to capture planned developments (megaprojects) to predict future production. Neither really deal with the key issues the confuse our view of production/reserves and thus forecast - the human dimension.

It seems to me the only way to try and apply a model to the data to make predictions is to 'reverse out' the effect of the human dimension on production figures - constructing an idealised production history from the raw data by removing the human perturbations (from history, which we DO know accurately). From there we can use three more pieces of information; which fields the oil is coming from, the fact that any country/company will produce its 'easiest' oil first, and the fact that companies will produce oil so as to maximise their discounted return on investment.

Putting that together, it should be possible to arrive at an alternative history of production which would then be amenable to improved mathematical modeling to determine what was under the ground. We could then take real production to yield real world predictions of future production capability.

I'd suggest that a fuzzy systems dynamics model is the first approach to performing this 'reversing out' - constructing a model that predicts out history supply record with the known history, and then reversing the effects of the elements to arrive at the inputs. It sounds as if this should work, being based on the data we do know accurately (production totals, history, driving behaviours), rather than the data we don't (URR, etc.)

Your thoughts?

The wise words "don't use models the way a drunk uses a lamppost...

Shouldn't that be "the way a dog uses a lamppost.." :)

I just used the non-dog variation on the Logistic model:
http://mobjectivist.blogspot.com/2007/03/derivation-of-logistic-growth-v...

This is the "drunk looking for his car-keys under the lamp-post" problem. Somebody asks the drunk why he chose to look under the lamp-post. "Of course, that's where the light is".

But the dog variation is actually more funny and perhaps more telling.

WHT

Perhaps you could post an article here describing your Shock Model. In particular I would appreciate your view of recent Saudi production with regard to your model, assuming that they are pumping to the capacity of refiners to accept their crude oil.

The only reason I'm not convinced the shock model is right is I'm not sure we have enough data to support it. I think it is probably a better model but on the same hand given the data a simple analytic model suffices. I think you could drop even drop the
logistic curve and simply use parabolas. It would be nice if you picked a simple model of your choosing that you did like so we could see how the shock model varied against that.

Here you basically do that.

http://mobjectivist.blogspot.com/2007/02/quardratic-linearization.html

And here you compare to a Gaussian. Isn't a Gaussian good enough for our purposes ?

http://mobjectivist.blogspot.com/2007/01/missing-link.html

Next you added in discovery for the US but KSA for example has had many fields that were discovered yet not produced because of technical problems.

Again in general your right and I agree its just hard to see
if your model has to many parameters.

I actually favor a Gaussian because it fits what I know about movement of molecules through a matrix so it scales nicely a sample of the matrix all the way up to the field.
So you don't have to change equations. Because of the noise in the data I did not see that the choice makes a lot of difference.

I'd say the best approach is a Gaussian first approximation then move to something like the shock model for more complex cases. In general the only reason to model is when your within 20% of peak on the front side as say 10% on the backside. So I'm not sure we needs a super good model.

With that said I'd love to see you model Russia.
Thats one that HL basically fails on and probably any other simple analytical model. And if you do what I said and pick a simple model this would be a good way to show when it fails.

The only reason I'm not convinced the shock model is right is I'm not sure we have enough data to support it.

Yet you latched on to the HL and continue to insist that it has value, even as case after case falls upon scrutiny. Now, scanning down the responses I can see that you have been reduced to aspersion casting. You still haven’t produced a case that works, but insist that I have demonstrated nothing. It is like someone who insists there are pink unicorns living in their house. I go from room to room, and I find no pink unicorn. But you insist that the burden of proof is on me to show that the unicorn is not there. Actually, the burden of proof is on you. Show me the unicorn.

Thats one that HL basically fails on…

Show me one that it didn’t basically fail on.

Robert its a model. In this post you already showed it works for KSA in your examples of how it does not work.

The 2000 production data gave a good fit and when you went to 2006 the fit was worse and the URR changed but the model indicated that it had more noise. The good thing about HL is its noise or error term is realistic.

So you already posted a great example of HL working if you understand modeling.

So what is the model hinting at after 2000 ? Its says that a lot of "new" production was brought online but yet KSA did not
find some large new field during this time period.

So what happened ?

They had spare capacity in 2000 by 2006 this was gone either it was rotated out or depletion is catching up since prices are still high depletion is a good possibility.

HL cannot predict when someone changes the extraction pattern abruptly but it does show in the data and the fit as noise. Its also giving us a estimate on how much spare capacity the used to have. And we have confirming statement from KSA that say they where pumping at capacity in 2005.
If you had bothered to read on the noise distribution in HL you would have realized that a increase in the noise itself
means something disrupted the model since the noise goes to zero. And your using the URR estimate without a error term
if you showed the real error in URR you would see that most of what happened through 2006 was simply to increase the error in the estimate the error terms probably still overlap.

I'm comfortable with your KSA plots and believe since KSA was a confirmed swing producer and the model shows that they have brought all their excess capacity online they have already peaked from the HL data.

This post is junk science at its worst.

Its a different metaphor. One is about using the lamp post as a tool to help, rather than trusting it to do all the work - the other is about looking to find answers only where you have the data.

Lots of lamp post metaphors.

Ahh well, looks like nobody is going to come back on the meat of the suggestion. Pity really, I think systems dynamics and working from the data we really do have is a promising approach. Maybe I'll have to do it myself one day.

Whats your rate of production in each case ?
If your assuming the same rate of production then your right
but thats a incorrect you of the model.

If you have such a large urr your production rate should be much higher then in the examples your giving.

I don't yet think you have proved anything. To be honest.
The production rate should depend on the total URR thats
the reason why it should work. The production rate is a non-linear function of remaining URR. Even your simple case of increasing by 5% per year then decreasing by 5% is wrong
although closer too reality and in this case HL is giving results inline with the real answer.

If your going to test the model this way we need the real production non-linear function. A Gaussian should be right. Or you can use a square wave as the first approximation.

So far I don't agree with your production models.
It would be easier if you also posted the production profile you assumptions are making.

I actually think this is a better analysis then what you just presented.

http://mobjectivist.blogspot.com/2005/12/hubbert-linearization.html
And more in line with what I've said.

Lets keep looking at this before we throw HL out.

I don't yet think you have proved anything. To be honest.

I have shown case after case, real and hypothetical based on rising production, flat production, rising and then falling production - and it has never worked. So do you think it would be too much to ask - given that you think the model has some merit - that I ask you to do some plotting and show me a case in which it worked, or would have worked? It's not like I went looking for cases to disprove it. It was wrong in ever case I looked at. So I ask you to show me a case in which it worked.

So far I don't agree with your production models.

Well, see the challenge at the end of my essay. Provide your own. Show a case that works. Stop saying it works if you can't show a case in which it worked.

It would be easier if you also posted the production profile you assumptions are making.

I told you exactly what my assumptions were. You could generate it in 3 minutes in Excel. Otherwise, I am going to post a hundred lines of numbers here.

Robert the function that ties production rate to URR is a unknown non-linear function. HL is a way to guess the answer without knowing this function. Thats why its empirical.

The one example you gave that was even close to reality was giving HL answers that were not too bad.

What you have just wrote says nothing about HL it's basically garbage.

If you come up with something close to right its worth arguing about. Your so hell bent on proving HL wrong your not even trying to understand it.

You can keep being unreasonable or start thinking.

I gave you a hint the shape of the function is not that critical. It can be a Gaussian or a square wave.
And I told you the reason HL works is regardless of the shape of the curve the peak time and total URR are basically constants thats why HL works. The model HL uses is the Logistic curve.

http://mobjectivist.blogspot.com/2005/12/hubbert-linearization.html

Most analysts use the logistic curve or Verhulst equation to "prove" this limiting behavior. Whereas, in practice, any peak will do.

He is basically right. We just happen to know the logistic curve seems to give the best fit for a simple analysis.
It seems that these unkown non-linear functions that relate production to URR can be mapped to a logistic curve. Of course the probably map to others. I'm not convinced logistic is the best but I think the error in the data is high enough it does not matter.

So again go back and pick any non-linear function that maps production rate to URR use that to generate your production data then run HL on the results. I'd like to see the graph
of the production profile so I can visualize the function.
The 5% per year one is basically I triangle if I understood
what your saying.

Then and only then can we discuss HL.
If at this point you have some valid arguments I'm interested. I know I'm being a bit harsh but this is bogus
and its public.

One more time.

Its too early to throw out HL.

Memmel,
Robert has an interesting point though. As he accurately describes a situation (Oilsville) with a flat production rate, what happens is that the width of the upside down parabola begins to increase; i.e. the second derivative of the production profile starts shrinking.

This kicks the y-intercept further and further into the future. Which you can mathematically see in that blog post of mine that you referenced.

Actually in the case you mentioned HL still works since the
peak comes down as the curve flattens. So as long as its a parabola your ok.

Generally flat production happens on the backside when production is constrained the case I use is a well that 90% watered out and the rate of production is constrained by how much water you can handle.
HL is not a good method once your constrained by above ground factors. Remember there is still a lot of oil left behind even after a well has watered out so its being produced at a low production rate basically forever for all intents and purposes. But where it fails your way past peak production anyway so whats the point ?

You can also of course come up with a number of contrived cases where a field is not reasonably exploited and these would show a flat production at the beginning. I don't know of a real world case that fits this.

One we have is Russia which collapsed where production collapsed for several years then rebounded slowly. And this one is problematic.

I might add there is a chance here to have a good discussion on HL and it needs to be examined but lets at the minimum start the discussion with the right baseline in place.
I have not varied all the constant volume parabolas to see if you can introduce some numerical instability into the procedure but mathematically all your doing is a trick integration of the parabola so all true parabolas with the same area give the same answer.

The real important piece that gets dropped on the floor it seems like is Hubbert is assuming a parabola or Gaussian shaped distribution the area under the curve is a constant
this makes the "date" of peak a constant just the shape of the curve is changing so what really changes is the amount produced at peak but this is not so important. If you have enough points on the curve then you can get both. I don't understand the choice of the logistic function over others but as I've said a few times I don't think it matters to much given the quality of the data. HL has real issues that should be addressed. They have not so far.
In any case you have to use curves the might is well be parabolas since you taylor expand with constant volume/URR
and linearize those the get the numerical instability.
Other curves i.e Gaussian are interesting but this is secondary. What Robert has shown so far is not that interesting.

Btw I'd be happy to talk with WebHubbleTelescope on the issue.

He at least seems to understands the problem.
He rejected HL and generally I AGREE WITH HIM.
Sorry for the caps but your not listening.
Someone has already done a fantastic job of questioning HL
and he used the correct production profile.

Until you integrate his work I'm not sure what the heck your doing.

http://mobjectivist.blogspot.com/2005/12/hubbert-linearization.html

One more quote from his blog.

I checked the math on this, and it really gets you thinking about what data visualization expert Tufte says about graphing data in a biased fashion. That convergence on a continuously shrinking error acts like a laser beam and gives people the impression of an excellent fit that may have dubious value at best.

So a good well reasoned rebuke of HL already exists.
And I'll say one more time generally I agree with him.
But its not clear that he can come up with a better model given the data we have. Not that he can't create a better model or a better model is possible simply do we have enough
data to support a better model.

So again does HL have problems yes here is the link that points out its flaws.

My answer as to why it works is simple.

Although the function changes that describes the actual production profile HL implicitly assumes that the rate of production is related to the overall URR via the logistic curve. Since we know from theoretical plate models that the time of elution or peak is related to the interaction of the
material with environment with a given geology if you steadily pump a field the time of peak does not change.
This means you can change the shape of the curve but your not actually able to change URR or the date of peak by much
without massive changes in the way the field is pumped.

In the case of chromatography they use Guassians and derive the interaction numbers i.e theoretical plates.
Now using a model that is well understood and tested the Theoretical Plate model and applying it to a oil field its says the following. If I drill a well into a porous geologic formation and a few wells around it. And first I pump some oil down it then start pumping water. The wells in a circle around the pumped well will get the oil in a Gaussian profile. The main body of the oil has a interaction with its it surroundings thats FIXED!
In the case of a field full of oil this block of oil is moving through a system that has immobile oil as part of its
environment but the behavior is no different. As you begin to produce a field the main driving force is oil pushing oil. Later its water pushing oil but the little Gaussian regions can't move till the ones behind them move.

This is my interpretation of what Fractional_Flow says and he
is also correct its the field geology that determines the peak.
http://europe.theoildrum.com/node/2372#comment-170481

Hubbert chose the logistic and uses the rate to guess the URR. The choice of logistic is interesting and its not clear
in the least its the best and again its not clear that a better one exists given the data we have. Given that we are just doing a taylor expansion the exact shape of the curve are not important whats important or interesting is that HL works when the production is assumed to be a curve.
The examples you have given don't even behave correctly to the first taylor expansion term no wonder they blow up.

I'm only saying you need to use a production profile that can be taylor series expanded about its center point i.e it needs to look like a parabola to apply HL otherwise its junk. I don't need to do anything the work is already done and has been done for some time. You simply need to use a production profile thats reasonably close to what HL assumes.

Next since your generating data if you pick parabolas which are simple you can find one that gives a perfect match then vary the parabolas away from the perfect keeping the area under the curve or URR constant. one to see how much HL varies. Actually you can use any series of parameterized curves. The only restriction is they all have to have the same URR.

Your current work is not even close to being the right way to critique HL.

Until you integrate his work I'm not sure what the heck your doing.

What I am doing is showing case after case in which the HL failed. Do you think it might be too much to ask – given that you continue to insist that it works – for you to show me a case in which it would have worked? Thanks.

Your current work is not even close to being the right way to critique HL.

Show me the “right way.” I don’t really think that’s too much to ask. Show some cases. Plot them. Tell me the parameters that would indicate a peak to you. Don’t keep asking me to show you cases and then denigrate what you are given. Produce something yourself.

HL is reasonable if you produce max possible with regards to your URR, right?
Thats the assumption you childischly refuse to mention.
Your oilsville produces 10/5000 per year (was it?). Thats too low. Max would be 4/400 (or maybe 200 like Saudi, sounds familiar?). This is the most simple way I can put it. Change that in your spreadsheet and tell us what happens?

You sound slightly too closed to allowing other comments into your worldview at the moment. Are you always like that? Hard on debating? Do you ever yield a mm?

HL is reasonable if you produce max possible with regards to your URR, right?
Thats the assumption you childischly refuse to mention.

So, this is your response to "Show me"? You can't show me either. All of these insults and cast aspersions, and nobody can show me a case where the HL would have worked. Why is that?

Your oilsville produces 10/5000 per year (was it?). Thats too low.

How do you know what is too low? You are making unwarranted assumptions. Besides that, this wasn't the only case I modeled. What the case shows is that a flat production case - as Saudi has been for many years - will underpredict URR if production is constrained. Or do you believe that Saudi has been producing flat out for all those years?

You sound slightly too closed to allowing other comments into your worldview at the moment. Are you always like that?

Given that nobody is giving me an counter-examples to show when the HL would have worked and how you would have determined that, right now I have no reason to question my worldview. Show me a case and make me question it. I am quite open-minded, as some posters on the board who actually know me can verify.

Even though I make no claim to following the math, what I've been gleaning from this whole series of exchanges is that Hubbert noticed that the way in which oil fields were drilled and developed in an unconstrained market tended to follow a familiar pattern. He didn't know the URR, but he had enough experience to make an educated guess. That pattern has seemed to fit in other unconstrained markets.

As I see it, we don't have the info to have as good a feel for the URR of KSA, so we've seen modelers fitting the curves as if KSA is unconstrained and choosing from a fairly wide range of possible URRs.

It seems to me what Robert is doing is significantly constraining Oilsville production and then saying that because HL doesn't work in unconstrained markets, it doesn't work at all.

I have not been following this closely so forgive me if someone has already beaten this to death, but the only cases where HL should work, conceptually, are where production is only constrained by physical geology. Where the field or province operators are producing as fast as they can, or responding to smoothly rising demand (the curve shape is supposed to model the reservoir dynamics). We know this is not the case for Texas/lower 48, Saudi Arabia and Russia so I do not see why we should expect it to work there. That's why it also should not work for your thought experiments (above). If world demand rose smoothly and no one withheld production to control prices (or for whatever), we might expect it to work in the aggregate. It is not surprising that such a simple model does not work for such a complex system.

The one example you gave that was even close to reality was giving HL answers that were not too bad.

Define “not too bad.” What you will find is that once again, “not too bad” will span a huge error range.

What you have just wrote says nothing about HL it's basically garbage.

Read what WHT wrote below. He actually understood the point that I am making. Cases, hypothetical or otherwise, can show you how the HL would behave. The flat production case – hypothetical or not – shows how the HL will behave in ANY relatively flat production case (like Saudi). The rising production case shows that it can’t call peak. The rate of rise doesn’t matter. If you did some modeling yourself, you would see that. But you are still insisting that the pink unicorn is there somewhere, while saying I have do “basically garbage” in showing that it doesn’t exist.

If at this point you have some valid arguments I'm interested. I know I'm being a bit harsh but this is bogus and its public.

It’s amazing to me, then, that you won’t produce a case in which it worked. Some recognize modeling for what it is. Some know how to test a model. I do. Show me that you know how, instead of doing all the aspersion casting. Support your own argument. Look again at the last section of the essay.

RR, I think HL only works when the producer is always producing flat out. Since this never happens in real life I guess you are correct that HL can't be used to predict when peak production will occur. I think you have already proved your point.

A simluated version of world production with steady growth (exponential) of 1.5% per year since 1982:

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The last 25 years looks quite close to linear. and is a close match of Khebab's HL:

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