275 comments on Predicting the Past: The Hubbert Linearization
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(GreenMan tiptoes through a minefield in attempting to comment)
If I am understanding your point, you are saying that a stable HL plot is necessary before it has predictive ability?
The Texas HL, as analysed by Robert, did not have predictive ability until well after peak, at which point the HL plot stabilized, and can be used to predict future production and Qt?
Do we have a mathmatical definition of the requisite "stability"? Could we give some metric of "stability quality" to a particular data set as a way of expressing confidence in its predictive ability?
Of the four plots you offered, Texas, KSA, Lower 48, and World, the Texas HL was unstable prior to actual peak, the other three seem to be stable, but the peak of KSA and World are debatable, in fact, the primary topic of debate. That leaves only one data point, Lower 48?
Robert ended his essay saying his next target would be HL plots of KSA. Perhaps we need a similar analysis of Lower 48, since that now seems to be the sole case in which we had both stability prior to peak and clear (in hindsight) peak?
I suppose we could throw the North Sea in there, as well, though you did not mention it in your list. I think we are all comfortable saying that the North Sea is past its peak. Did its HL plot prior to peaking exibit stability? How far in advance?
Is there a suitable data set for Prudhoe Bay? Or is that folded into the data for the rest of the US? Or can it be obtained by subtracting Lower 48 from total?
Is instability in an HL plot solely a factor of having been a swing producer, or are there other factors? For example, could we hope to do a predictive HL analysis on Iraq given its history of war and sanctions?
I guess the point of this is trying to answer the question "for a given data set, how confident can we be in the predictions it makes", and can we come up with a definite mathmatical expression of that confidence?
Do we have a mathmatical definition of the requisite "stability"? Could we give some metric of "stability quality" to a particular data set as a way of expressing confidence in its predictive ability?
Exactly the right question to ask. I think Stuart is looking at this. We have been discussing this essay some via e-mail, and I sent him my Texas data set so he could look into it.
I guess the point of this is trying to answer the question "for a given data set, how confident can we be in the predictions it makes", and can we come up with a definite mathmatical expression of that confidence?
Bingo! Give that man a cookie!
Could you come up with a non-linear, asymptotic formula that would fit better with the observed increase in URR toward the end of the cycle? It's been many years since I saw the inside of a math classroom, so it's just a thought.
It never gets much consideration IMO is the impact of technology. I fully understand the law of diminishing returns but some of the most productive improvements had to come into play at some point.
I don't understand how this would not add both to peak production and URR as what ever the (____)became widely accepted. The increase in production should generate somewhat of a addition to the curve.
I'll venture into hand slapping territory and speak on DelusionaL's point.
If there is a impact of new technology on the HL result for Texas, wouldn't this impact come into play earlier on a Saudi HL and result in an increased stability of the curve compared to the Texas HL? Am I correct in thinking that Saudi oil came 'that much' later in the game?
A kid with a question should also show up with a toy in hand, so hope this at least is new:
http://www.energyandcapital.com/consumption.php
Very cool! Thanks.
Stuart has done some work on stability analysis, but as you can see from the four plots, it's not hard to find the HL plot that was pretty noisy prior to its peak (and again, all four regions are--at present time--showing overall declining crude oil production). So, I wonder why Robert focused on that one plot--especially when Hubbert accurately predicted the approximate time frame for the Lower 48, inclusive of Texas?
The North Sea (EIA, C+C), on my HL plot, started showing a rock solid linear progression in 1988, until it peaked in 1999 (between 48% and 52% of Qt, just like the Lower 48), and production has precisely followed the predicted downward trend. Note that this was empirical. I did not predict a North Sea peak (although Matt Simmons did, using his own data).
According to Matt Simmons, the top oil companies working the North Sea--using the best data and personnel available--were predicting that the North Sea would not peak until after 2009.
All of the following regions have shown peak or plateaus, (with stable HL plots prior to the 50% mark) in close proximity to their respective 50% of Qt marks: Lower 48; Russia; North Sea; Mexico and now, the world.
Remember Khebab's prediction that Mexico would peak in 2006?
The two post-peak cumulative models we did were quite supportive of the method. The post-50% of Qt cumulative Lower 48 production through 2004 was 99% of what the HL model predicted (using only data through the 50% mark) and the post-50% of Qt cumulative Russian production through 2004 was 95% of what the HL model predicted (using only data through the 50% mark).
If our period of stability started in 1988, how much later was that stability evident? Are two years of stable data enough to establish stability? Three? How much is enough to say "we have stable data, now let's make some solid predictions"?
Perhaps another way of asking the same question might be "in what year, using only the data available up to that year, would we have been able to correctly call the peak?", with subsequent production data falling substantially onto the predicted curve.
The North Sea is a nice case to consider since, as far as I know, there were no above ground factors in its development.
As I noted in a separate post to robert, I see mexico as a better example for sa than texas. In addition to what I said there that, to me, shows sa/mexico to be more like each other than texas:
high tech simultaneous secondary and primary production
ultimate resort to high tech horizontals
each country has an old super giant field that dominates, rapid loss of which results in unavoidable peak
there is a further point, also different from texas, that is both are gov run and are, compared with what would have been done had they been exploited by private companies, starved of investment.
For all of these reasons, comparing the HL plots of sa/mexico may be informative. Can you resurrect and post the two?
And, I have a separate question; does the data suggest that the 'dog leg' up following a stable regime is predictive, not of higher Qt but, rather, that peak is nigh?
Thanks
We saw small deflections in the Texas and Lower 48 plots, right before the they peaked, much like the small deflections in the Saudi and world plots, right before they (IMO) peaked.
WT do you have the OIP numbers for Texas and can you give me
the % recovery factors based on the HL analysis ?
Thats the plot we need.
Mike, the problem with using recovery factors based on Texas is that we gutted many of our early-discovered giant fields with overproduction.
Secondary and tertiary production and Maximum Efficient Rate (of recovery) were all invented by my homies in the oil patch around here. As a consequence the is a recovery factor of the oil in place of about 1/3rd, while the mid-east and North Sea are getting about 50% of the original oil in place.
The Bureau of Economic Geology at the University of Texas should have the exzact figures you are looking for.
Right I forgot about this. We really damaged our fields early on. In a sense its a blessing since fixing the damage is probably what keep us going. I don't think Texas by itself is all that useful as a model past a certain point because of this.
For all of these reasons, comparing the HL plots of sa/mexico may be informative. Can you resurrect and post the two?
And, I have a separate question; does the data suggest that the 'dog leg' up following a stable regime is predictive, not of higher Qt but, rather, that peak is nigh?
Mexico did the dogleg up in 1995 resulting in a new stable regime with a Qt roughly twice what the previous data was pointing to, see my post from two month's ago:
http://www.theoildrum.com/node/2149#comment-144998
Thanks for the link. SO, mexico's HL is not a good predictor for sa, or at least not if sa has peaked.
Mexico, sa, kuwait, maybe china remain special cases with a super giant that dominates overall production; for each of these, the question is, when will the super giant go down? HL is probably silent on this issue. Ghawar and cantarell were produced with the latest high tech, meaning that the decline, when it comes, will dominate production and almost certainly signal that peak is here. We know about cantarell and mexico, daqing and china, burghan and, probably, kuwait. Ghawar remains veiled because of sa stonewalling, but precipitous decline would neatly explain sa production profile over the past year.
The early HL plot for Mexico showed a P/Q intercept of about 13%. While it is not impossible, 13% is unlikely.
Compare it to the P/Q intercepts on the four HL plots I have shown above.
Yet another example of a region: (1) Declining and (2) As predicted (by Khebab in this case).
Let's see, what's the score so far?
Notice a developing trend here?
Notice the escalating attacks as the reality of a near term peak becomes more apparent?
Notice the escalating attacks as the reality of a near term peak becomes more apparent?
You are taking this far too personally. I am not attacking you. I am pointing out that in the case of Texas - which you have indicated is reflective of Saudi - the HL performed very poorly at the time of peak. So, I am pointing out that we can't then have much confidence in using the HL to predict Saudi's peak. In turn you have resorted to "Who's right!" Come on.
You would have been right had you predicted Texas peak in 1956. You would have been right for 12 years. But you would have ultimately been wrong because you used a tool that is not very reliable for what you are trying to use it for.
On the other hand I think Stuart's work was very interesting, and this is by no means an answer to his posts. I still don't think the world has peaked, but the HL gives me absolutely no useful information one way or the other. The kind of analysis Stuart did gave me more to think about though.
So, one of us predicts the peak, and he is so far right, but you criticize the work, even as the Lower 48, Saudi Arabia, Mexico and the world are declining as predicted, based on Hubbert/HL models, and as the North Sea is following the HL model.
The other one observes that Saudi Arabia has peaked, and his work is more valid?
(BTW, Stuart posted an article last year, to the effect that we were probably at or past world crude oil production).
Somehow, I get the feeling that you are getting ready for the following admission:
"Saudi Arabia has probably peaked, but by God, Jeffrey's methodology was wrong."
Cut to new Titanic Scene:
Jeffery the problem is everyone that has confidence in HL has paired it with other data to develop that confidence and its not just QT.
In the case of KSA its the fact that
1.) HL is showing a peak about now.
2.) They are out of easy oil look at how they are drilling now and what they are producing.
3.) Ghawar has a rising water cut and is in decline.
They peaked.
You only need HL plus some other information and you can pick the right HL plot with almost 100% confidence.
I assert you need no more information.
WT
I'm just curious why the vehement tone in the responses to RR? It is possible to come up with the right answers using a wrong methodology. I keep reading the exchange between you and RR and I really don't get the impression that he thinks your answer is either right or wrong, but rather he has taken you to task about the path you took to arrive at your conclusion.
Ultimately you can argue that you are right in that dependence on fossil fuels needs to end ASAP, and the difference between now or 5 years from now or 50 years from now will in the grand scheme of things be a trivial detail.
Given the evidence I too think we are pass/at peak, but I understand from an academic point of view why models should be tested, analyzed and refined, and from what I read that is what RR appears to be doing.
You however seem fixated on being right, just for the sake of being right. Perhaps it is just a personal thing, but I like to be right including as to why I was right. And in RRs case I think he wants to be right down to the details in his methodology because he has the fear that crying wolf too early could cause resistance to a Peak Oil warning if this turns out to be a false Peak.
The media constantly bombards those "Peak Oil Nuts" as being whacks because from the beginning of oil there have been those claiming it will end tomorrow. Given the climate surrounding Oil and the competiveness surrounding this commodity today, this type of debtate takes on even more importance. RR has stated previously that his big fear is in crying Peak too early and giving ammunition to the opposing side which will in turn make it that much harder to convince people when the real peak will occur.
I can understand RRs hesitation and from a academic standpoint admire his humility and skeptism used in his efforts to forcast oil related events. RR has the mark of a true researcher, one who does not rest on his laurels claiming he has found the answer, instead he takes what he thinks is right, and subjects to even further scrutiny. Its an excercise I think is well worth doing, because if it turns out that this is a false peak, this community had best have moral fortitude and academic honesty to go back and admit they were wrong and review WHY they were wrong. During that process, it will mean that methodologies will need to be picked apart.
Amen
I totally agree - Robert's approach is IMO entirely correct, and he is to be highly commended in taking the line he has.
Beautifully put.
:)
That is funny....
Robert: "We sank in 2 hours, 23 minutes and twelve seconds and your math was wrong".
The early HL plot for Mexico showed a P/Q intercept of about 13%. While it is not impossible, 13% is unlikely.
Russia's HL also has a P/Q intercept over 10%. Its predicted Qt is also likely to be inaccurate.
Notice a developing trend here?
The trend I've been noticing is the tendency for HL to produce false alarms 10-15 years before peak.
Dream on while you still can.
As I stated before if production was with 5-10% of peak 10-15 years before peak its not a false alarm. Its a good prediction.
The fact that we feel 20 or more years at peak is a long time is simply applying how we feel about time to a process.
Put it this way a mountain say spends say 30% of its lifetime within 10% of its maximum height this could be millions of years. But I think mountain weathering and HL are closely correlated and behave the same way. Other factors have to be taken into account to do a better prediction of when a mountain will reach its peak these are the filters I speak of.
But its the same problem and you can see HL is not something you discard.
Its not a personal attack. Stay focused.
I guess what I am trying to express is the contribution of "above ground factors" to noise in the production data.
For example, was Prudhoe Bay production ever limited by the throughput of the Trans-Alaska Pipeline? For how many years? By how much? Would that have contributed to false predictions from the HL plot? Or is it small enough that we would get good predictions anyway?
Would we get better results if we simply discard data points during points which are strongly impacted by above ground factors, such as for Iranian production during the Iran-Iraq war?
While not a mathmatical process, it could be documented. "I started with data set A, removed data points B2, B7, B8 due to clear above ground factors, and did my HL on the remaining points. The data points C1 through C12 exhibited stability quality XYZ, and I have used them to make the following predictions". Something like that.
Well, let's consider the two most stable cases, with essentially no material restrictions on drilling or constraints on production (other than as noted below): the US Lower 48 and the North Sea.
Both regions peaked in close proximity to their respective 50% marks, after showing solid linear progressions on their HL plots.
Within the Lower 48, Texas produced at less than capacity, i.e., it was the swing producer. This was the basis for using Texas and the Lower 48 as a model for Saudi Arabia and the world. Not to belabor a point, but Saudi Arabia and the world are declining as predicted (EIA, C+C).
Because of political problems, there have of course been huge swings in production, e.g., the Iranian revolution and the collapse of the Soviet Union.
But again, consider the Lower 48 and North Sea--developed by private companies, vastly different producing regions--yet they are both following the predicted downward production curve after peaking in close proximity to the 50% of Qt mark.
So, absent political/technical problems, IMO, large producing regions tend to show linear HL patterns and to peak and then decline in proximity to the 50% of Qt mark.