The R/P metric and "pragmathematics"
A guest TOD post by Dudley Stark called The limit of the statistic R/P in models of oil discovery and production contains some very interesting ways at looking at the Reserve/Production (R/P) oil depletion metric.
Check out the comments as they also contain a high signal to noise ratio of interesting points and mathematical pragmatism, what I call "pragmathematics".
Use of a gaussian predictor to estimate reserves for USA.
I think DaveR on TOD is Prof. Dave Rutledge from CalTech. Kudos to guys like Rutledge who apply some of their engineering knowledge outside of their field of academic expertise. It really benefits us all.
posted by @whut at January 24, 2008
2 Comments:
It's an interesting discussion.
Curve fitting in the cumulative production domain give the illusion to be more stable (mainly because production noise has been strongly reduced by the integration step) however if you estimate a confidence interval of the URR, it will be quite large. In addition, the choice of the right model (Gaussian, logistic, etc.) will increase the uncertainty interval.
P.S.: check you email (around January 18).
integration is like a filter yes, and the initial cumulative is shaky because of poor data early on.
Thanks to Rembrandt for the data.
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