I will believe the Saudis don't see any upcoming problems with Ghawar when they cancel one of their projects due to low oil prices. If they continue to be full steam ahead with increasing their capacity then I think they are aware that Ghawar may not be as robust in 5 years time as they would like us to believe.
Posted: Thu Jun 16, 2005 7:39 am Post subject: Updated Verhulst model
With the arrival of the new BP data, we can update the Verhulst model we did last year. Maybe someone friendly with a website can graph this for us (I am still too thrifty).
Since we are a lot smarter than we were a year ago, I have put in the following changes: The historical data is extended back to 1900, and the little forecast we calculated yesterday for 2005 through 2008 are included (since we are better able to adjust the current data for changes based on current news stories ex: Iraq not able to grow, etc. etc.). Also, I now have MS-Solver available, so as to take a little of the subjectivity out of the estimates. I have constrained the model so that the cumulative production equals the actual production for 1900-2008, and the 2008 forecast and model values are equal. I have let the variables k, n, T-50 and Q-inf float so as to minimize the standard error.
Commentary:
1. Based on this model, Q-inf, the “Original Oil in Place” value is 2,461 gb. This is a little bigger than the estimates we had last year. Cumulative production (1900-2008) is 1,273 gb, which leaves the BP estimate of 1,188 gb remaining. The historical data therefore suggests that we are past the 50% depletion midpoint.
2. This new model predicts a peak of 32.6 gb in 2014. This is about 91 mbo/d, which, as we discussed yesterday, is about what the “demand” is forecast to already be in 2007, therefore the world will be in the position in which oil usage will be geologically constrained, really, from now on.
3. The 2030 value (28 gby) will be just about what the 1996 value was. In the world of 2030, according to our population estimate from last year, there will be about 9.3 billion people, compared to 5.7 billion, therefore, somebody is going to have to do without oil, or else we are going to have to share.
4. The really steep part of the decline curve is between 2030 and 2050. If this form of modeling is correct, there will be a 2/3 decrease in supply during that time. Between now and then it will be a nuisance, but probably liveable.
5. What could change that would affect this model? Well, the assumptions we made yesterday are key, namely that Russia, Iraq and Saudi are not able to grow over and above what they are now producing for the next 3-4 years, but everybody else is able to increase or deplete at the same rate as they did in 2004. Also, any new countries that go into depletion (such as Iran, Mexico or Venezuela) may change the short-term forecast, which would in turn change the model a lot. Also, any discoveries that radically change the estimate of Q-inf would be important, and also, any economic screwup, such as we had in the early 80’s that killed demand prematurely would be important and extend the nominal peak some distance into the future.
Here is the data:
n 0.149454128
qinf 2,461.82
t(1/2) 106.8467633
k 0.039628337
Joined: May 02, 2005 Posts: 3524 Location: Oh really?
Posted: Thu Jun 16, 2005 7:49 am Post subject:
What are the assumptions for Saudi Arabia through 2015? Flat at 9mbd? Increasing to 15mbd as they promise? Depleting to 6mpd as feared by some?
What about the rest of OPEC and their suspicious reporting?
I guess I am really asking about the entire model as I wasn't here last year _________________ "It's still all about energy!"
The assumptions we made yesterday were constant production of 10.5 mbd through 2008. After 2008, the model is "global", that is to say, not broken out by individual countries. Also, I assumed that the production for Iraq was what the BP review said it was, which was 2 mbd. Both of these numbers might be "generous".
ASPO's model might or might not be better in this respect since it is the sum of individual models for each of the producing countries. If I get crazy later on, I may do a similar model/forecast on this basis, so we can break out some individual countries and note any important differences.
The weaknesses of this forecasting method (mathematical modeling) are discussed at length by Lahererre in one of the papers on the dieoff.org website. This stuff is still kind of fun, though, and should be looked at as one more data point, among many, in the study of this issue.
Excellent work. But I share the concerns of Simmons and MD. Most of these models assume well managed fields ~Prudhoe Bay. There seems to be more potential for downside surprises from abused fields collapsing than upside surprises from new techniques for quaternary recovery increasing URR. _________________ "The world is changed... I feel it in the water... I feel it in the earth... I smell it in the air... Much that once was, is lost..." - Galadriel
Joined: May 02, 2005 Posts: 3524 Location: Oh really?
Posted: Thu Jun 16, 2005 1:32 pm Post subject:
THE WORLD PETROLEUM LIFE-CYCLE
Richard C. Duncan and Walter Youngquist
does anyone know what happened to thsi series of studies? The last one I found was from 2000 and they had mentioned continuing. Has the program continued to anyones knowledge? _________________ "It's still all about energy!"
is Q-inf the “Original Oil in Place” or the "Ultimate Resource Recoverable"? because the curve is about production, the area under the curve should converge toward the URR. am I wrong? _________________ ______________________________________
http://GraphOilogy.blogspot.com
You are quite right. The area under the curve should be Q-inf. I am no longer capable of doing it myself, but if you go back to the original Verhulst equation in the paper by Roper, and solve for y, you might be able to calculate the integral and arrive at an approximation of Q-inf, and also, by setting the first derivative to zero, you should be able to arrive at the peak.
The value of Q-inf is critical to the calculation of the curve. If the Q-inf value above were greatly higher or lower, the shape of the curve, and therefore the peak prediction, would be completely different.
When we did the exercises a year ago, in the "peak mart" thread, we ran through a lot of calculations, and did some "blind" tests where softlanding gave us some partial curves, and we tried to predict the peak, and what we found out was that we needed to be at least in the ballpark on Q-inf in order to be close to the correct curve shape. What we also found out is that there is an "inflexion point" on the curve, which is about 2/3 of the way up on the left side of the curve. This is the point at which the "tangent line" slope, if you will, goes to infinity. If you have data past that, it is also helpful.
So the ramifications of this, as it applies to us, is that the value of remaining reserves needs to be pretty well known in order to do a good job on peak prediction. Therefore this whole issue of "reserves transparency" is critical to being able to make this type of model. Also, if you think you are "close to the peak", you can do a pretty good job of fitting the curve to the existing data.
After that, it becomes an issue of resolution, that is, to what level of accuracy are you satisified that you have made an accurate prediction of the peak? If you have a hundred years of data, and you can predict the peak within 5 years, is your methodology good enough? We were never really able to answer that question to any degree of satisfaction.
This applies directly to the work of Hubbert himself, plus Lahererre and others. If you have data of a given quality, and they predict a peak value of 2000, or 2009, or whatever, is there enough accuracy in this methodology to be able to make plans and/or policy decisions on that basis?
So, I think the real answer is to use many sources of data, and also refine the predictions when new data comes in, to see whether or not the world is going to end, and not take any one prediction too seriously (including those of ASPO and others, and especially, the amateur pup55).
This is annoying to people who do not understand this type of modeling, because they expect some kind of easy-to-digest number. This is the very thing that Michael Lynch criticizes Campbell for all the time, because as new data comes in, you have to recalculate everything again, and this results in a change in the peak prediction, and so the less-enlightened people consider this "waffling" or whatever. Deffeyes has solved the problem by picking a peak date kind of tongue-in-cheek, but he freely admits that this is just a guess, and also, he has been around long enough and does it with enough of a sense of humor that he does not aggravate people and they kind of accept it.
Sorry to have gotten longwinded on this, but some background is in order for those who joined us recently and are reading up on this. For further edification, feel free to go back to the "peak mart" thread and read up on what we did a year ago. Also, the links to the original equations are in there for those calculus-proficient to go back and view.
Also, I am still happy to have an ongoing test of this curve-fitting ability. Anybody who wants to can submit some partial production curves for any country, and I will calculate the curve using this method, and predict the peak. Then, easy to compare with the actual peak and see if I predicted the peak accurately. That way, you can test our proficiency.
Thank you for your response, I'm going to read the thread "peak mart" to get more info.
Question:
What kind of software are you using for your simulation (Excel, Matlab)?
I was thinking about putting together a little open source Matlab package on the different curve models and estimation techniques so that people can play with it and eventually improved the models.
pup55 wrote:
So the ramifications of this, as it applies to us, is that the value of remaining reserves needs to be pretty well known in order to do a good job on peak prediction. Therefore this whole issue of "reserves transparency" is critical to being able to make this type of model. Also, if you think you are "close to the peak", you can do a pretty good job of fitting the curve to the existing data.
Usually in Physics, we perform sensitivity or error analysis on the model in order to evaluate the impact of the different parameters on the outcome. For instance, if you put an error interval on Q-inf you get an interval on the PO data. I was wondering if you have already performed such an analysis. It's also a question of intelectual honesty to put a confidence interval on your predictions. That fact always bothered me about the ASPO estimation.
pup55 wrote:
This is annoying to people who do not understand this type of modeling, because they expect some kind of easy-to-digest number. This is the very thing that Michael Lynch criticizes Campbell for all the time, because as new data comes in, you have to recalculate everything again, and this results in a change in the peak prediction, and so the less-enlightened people consider this "waffling" or whatever.
This technique of curve fitting reminds me a little bit of tracking techniques (ex: Kalman filter) were you track a target based on a model but where the estimate is always recalculated each time a new observation comes in. _________________ ______________________________________
http://GraphOilogy.blogspot.com
What kind of software are you using for your simulation
MS-excel. I will send you the spreadsheet if you want. PM your email address and I will send it off to you.
Quote:
I was wondering if you have already performed such an analysis. It's also a question of intelectual honesty to put a confidence interval on your predictions
.
This is a good idea. I will tinker with it and post the results.
Edit: added the last sentence. I hit the "submit" button too soon.
The USGS is the USGS estimate of estimated 3000 gbo remaining, rosy scenario, Q-inf=4173 gb. The peak is 2024. The "max" is a 20% increase in Q-inf (2953 gb) and "min" is a 20% decrease in Q-inf (1968 gb). The peak estimates are 2011 and 2017 respectively.
You do not want to be in the 20% decrease scenario, because the curve, in this case, really is like a cliff.
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