136 comments on Application of the Dispersive Discovery Model
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136 comments on Application of the Dispersive Discovery Model
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Maths vs Politics
I'll repeat a statement made a few times before. If you want to use maths to predict/understand oil production/discoveries etc. then you need to explicitly 'reverse out' the impact of political and economic decisions.
Its no good trying to model areas such as new discoveries if you haven't taken into account the times when countries and oil companies "couldn't be bothered" to search exhaustively since they already had more reserves than they knew what to do with.
Equally if there is a recession and share price is troubled, oil companies will reduce the cost base and limit their exploration.
And then there are the technology shocks which introduce step changes into the system.
Trying to match maths to this noisy data with all these effects still in place artificially limits what you can understand. We KNOW when the recessions were, when the shocks occurred, etc. - so its possible to make allowance for them. Model on the cleaned up data, then add back in the real world effects and you can generate a tool that you can use to predict the 'perfect' world performance, and then add in your expected or observed real world events as they happen - essentially playing 'what if' scenarios.
Frankly, I look a little askew at a model that claims to accurately model the real world data without the taking account of the real world noise. It doesn't pass the sniff test.
Is it really that important?
We are talking an approximation here.
Let's assume the real world shocks are roughly evenly spread out in time, then the noise stays there, but does not affect the overall conclusion that much.
Also, whether the shocks have a relative big enough scale to matter, remains to me at least unproven.
I think the model has a lot of potential and cleaning the real world data would also have it's consequences, just as WHT points out. There have already been other methods using various ways of trying to average out the noise, perhaps introducing additional skew to the data for future extrapolation.
Modelling it with noise intact at least starts with a different premise and the results are encouraging.
However, in an ideal scenario, I think your point about trying to achieve 'perfect world' scenario is a good one.
BTW, great work WHT. Even a person like me who's getting back to physics/maths after at 15+ hiatus could follow the main gist of the article much of the time. That is quite remarkable communication and explanation powers you have!
Well, if you take the global oil production curve and work out the offsets, translations and stretching necessary to turn that shape into a smooth bell curve unconstrained consumption theory predicts - you can readily see how the effects I describe can have a key impact on production data. Its not a big step to suggest the effect is equivalent or greater in other areas.
So yes, I'd say its important.
Your points may have validity which might be checked by doing a sensitivity analysis, but one needs to start with a model, and the simplier the better. With a model in hand, one can introduce factors as you mention, and see how the model results deviate from the data. You can't reject the model as insignificant when you don't know how it responds to the input you suggest.
My suggestion is rather the reverse.
Take out of the base data the effect of known factors, then model the now simpler data. No mathematical equation will match the discontinuous actions of politics and economics - but take them out and you have a chance.
Once you have the model, add the effects back in.
I understand your point. The step changes I think are very deterministic and happen at the last stage of the process, which is why I call them shocks. Everything else about the model is stochastic (one could argue about the power-law growth term, but everything has to have a driving force). So if I could divine what the extractive step changes are, preferably from some real world source, like corporate records or OPEC dictates, I certainly would be more satisfied. Apart from that, having a reasonable set of dimensional parameters that derive from some simple physical models helps to fill in the rest of the puzzle.
But surely you first need to know what will happen if politics is ignored? In this case the politics is a response to the inexorable mathematics of the situation, so you need to establish the mathematically "perfect" situation first.
The politics then changes the situation, but to understand what the politics will do, we need to first understand what happens without politics.
And don't forget that it's possible to go back to mature fields and use techniques like streamline simulation to figure out where to drill production and injection wells to recover more oil... Prof. Akhil Datta-Gupta of Texas A&M University predicts that using this method there are 200 billion barrels that are economically recoverable from mature fields in the Continental US alone. He's recently published a book which includes a CDROM with streamline simulation software (and perhaps source code...):
(from http://www.rigzone.com/store/product.asp?p_id=1842)
Streamline Simulation
Author: Akhil Datta-Gupta and Michael J. King
Format: Softcover
Pages: 394
ISBN: 978-1-55563-111-6
Publisher: Society of Petroleum Engineers
Year Published: 2007
Item Number: 100-1842
Availability: In Stock $149.00
Streamline Simulation: Theory and Practice provides a systematic exposition of current streamline simulation technology—its foundations, historical precedents, applications, field studies, and limitations. This textbook emphasizes the unique features of streamline technology that in many ways complement conventional finite-difference simulation. The book should appeal to a broad audience in petroleum engineering and hydrogeology; it has been designed for use by undergraduate and graduate students, current practitioners, educators, and researchers. Included in the book is a CD with a working streamline simulator and exercises to provide the reader with hands-on experience with the technology.
Contents: Introduction and Overview • Basic Governing Equations • Streamlines, Streamtubes, Streamfunctions, and Simulation • Applications: Field Studies and Case Histories • Transport Along Streamlines • Spatial Discretization and Material Balance • Timestepping and Transverse Fluxes • Streamline Tracing in Complex Cell Geometries • Advanced Topics: Fluid Flow in Fractured Reservoirs and Compositional Simulation • Streamline-Based History Matching and the Integration of Production Data
"...so you need to establish the mathematically "perfect" situation first."
“Poli” a Latin word meaning “many”.
Politics is the lubrication of the "maths" model.
Nothing happens w/o politics.
To take politics out is to say "why do we need algebra. We'll never use it."
garyp, This is a great argument you make.
Yet I think you forget that any lapses in exhaustive searches by well-fed companies are more than taken up by hungry newcomers on the scene. Where there is money to be made, people will contribute to the gold rush. And greed is the essential driving force, which has to first-order never been known to abate in the history of mankind. Even at the lowest point in the value of oil, it would still be worth a fortune for the fortunate prospector.
I also think I have taken into account noise and uncertainty by the dispersive model itself. And the oil shock model adds another level of uncertainty, up to the point that shocks are used to model the step changes you talk about.
So it is in fact a bottom-up stochastic model, but then perturbed by top-down deterministic considerations.
OK.
The word "noise" is being thrown around here.
Noise IS Chaos Theory.
Data Mining using Fractals and Power Laws.
The model, therefore, only mimics power law behavior.
"...we do know that, overall, it will fit within the mathematical pattern of the power law distribution.
The interesting thing is that this mathematical relationship is found in many other seemingly unrelated parts of our world. For example, internet use has been found to fit power law distributions. There is a small number of websites that attract an extremely large number of hits (e.g. Microsoft, Google, eBay). Next there is a medium number of websites with a medium level of hits and finally, literally many millions of sites, like my own, that only attract a few hits.
The number of species and how abundant each one is in a given area of land also fits a power law. There will be a few species that are very abundant, a medium sized number of medium abundance and many species that are not very abundant."
http://complexity.orcon.net.nz/powerlaw.html
In other words, we know the largest fields have been found.
There are no others that can be accessed.
http://www.cis.fiu.edu/events/lecture55.php
The link above to:
Data Mining using Fractals and Power Laws.
"This supports the old adage that money makes money and the rich grow richer, and the poor grow poorer. The longer the interactions continue and the more people who join in, the more striking will be the difference between rich and poor. This also links to the principle of Chaos Theory, that such systems are very dependent on initial conditions. A small advantage at the beginning is far more likely to result in a high ranking than a small advantage later on, when other agents have already gained significant advantages.
Same with oil fields.