42 comments on The limit of the statistic R/P in models of oil discovery and production
Comments can no longer be added to this story.
Blogroll
- ASPO The official site of the Association for the Study of Peak Oil & Gas.
- Energy Bulletin Clearing house for news regarding the peak in global energy supply.
- PowerSwitch Dedicated to raising awareness & discussion of the impending & permanent decline of cheap oil & gas supply.
- ODAC Oil Depletion Analysis Centre working to raise awareness and promote better understanding of the world's oil-depletion problem.
- Global Public Media Public service broadcasting for a post carbon world.
- Post Carbon Institute Learning to live in a low energy world.
- PeakOil.com US site and forum to educate and promote awareness of global hydrocarbon depletion.
- FEASTA The Foundation for the Economics of Sustainability
- Tradable Energy Quotas (TEQs) This website describes an effective and fair response both to climate change and oil/gas depletion
Other Blogs
User login
Personnel
Editors
Contributors
Peak Oil Primers
Archives
- August 2008
- July 2008
- June 2008
- May 2008
- April 2008
- March 2008
- February 2008
- January 2008
- December 2007
- November 2007
- October 2007
- September 2007
- August 2007
- July 2007
- June 2007
- May 2007
- April 2007
- March 2007
- February 2007
- January 2007
- December 2006
- November 2006
- October 2006
- September 2006
- August 2006
- July 2006
- June 2006
- May 2006
- April 2006
- March 2006
Vital Trivia
License
This work is licensed under a Creative Commons Attribution-Share Alike 3.0 United States License.
GAIA Host Collective
Interesting that applying the shock model to a Kroneker delta function for a single discovery would add a fixed width production so the scaling on width does not really jive with that model.
In some sense R/P=constant is a pure Markovian rate formulation. The amount of extraction is always proportional to the amount of perceived reserve available. And the reason it starts out high and then damps is because of the transient lags for the shock model phases (decision, plan, build) before the production hits that long-term steady state.
I hazard a guess that this will play out a bit differently using the HSM (Hybrid Shock Model) because the extraction rate builds up with cumulative discovery in HSM. It would be interesting to make the comparison.
Otherwise good use of pragmathematics. Using L'Hopital's rule is indeed clever.
Yes, the scaling on width wouldn't work for a delta function but it could work on a pulse function approximating a delta. The scaling is more about the time delay between discovery and production. It sounds like the Shock model models that time delay in a more elaborate way and is probably more accurate.
The delay and width scaling comes about from convolutions in the shock model. Even taking the Lorentzian example and the Gaussian examples, you get summed (not multiplied) scalings if convolution is at the root. Two infinite Gaussians convoluted together give a new width that is sqrt(w12+w22) and two infinite Lorentzians convoluted together goes as w1+w2. That's at least what I think is at the root of the scalings.