A new book entitled
Mathematical GeoEnergy: Oil Discovery, Depletion and Renewable Energy Analysis by Paul Pukite, Dennis Coyne, and Dan Challou
will be published late next year by Wiley as part of their AGU Book Series.
We are looking for potential reviewers of the manuscript. As the title implies, the contents are math intensive, and suitable for a college-level science or engineering curriculum. If interested, please send an email to firstname.lastname@example.org .
Table of Contents
Part 1 – Depletion
Chapter 1. Introduction
Why we need to understand oil depletion. Rationale for our analysis and a motivation for analysis beyond oil.
Chapter 2. The Problem
Who has tried to qualitatively model oil depletion? An analysis of how the current models fall short.
Chapter 3. The Premise
What fundamental ideas do we apply? Mathematical groundwork and premise for the analysis.
Chapter 4. The Facts in the Ground and Finding Needles in a Haystack.
Where do we find oil reservoirs? Basics of modeling discovery.
Chapter 5. The Analysis of Growth and the Shock Model.
When does the extraction kick in? Basics of modeling production and depletion.
Chapter 6. Applying Dispersive Discovery and Reserve Growth
How discovery affects production. Combining discovery and production as an integrated model. How estimates of oil evolve.
Chapter 7. The Context of Discovery and Oil Production.
How do we simplify the search model and verify the extraction model? Supplemental analysis for modeling discovery and production.
Chapter 8. The Results.
Which data sets support the model? Lengthy chapter on applying models to regional data.
Chapter 9. The Discussion: Alternate Consensus Approaches and Cornucopian Conundrums
Which conditions can impact the model? Caveats to the analysis with comparison to other models. How do other pessimistic projections fit in? And how do we reconcile against optimistic analyses?
Chapter 10. An Oil Level Check and Diagnosis
While we have gotten this far, what can we conclude? What current situation do we find ourselves in? How do recent and evolving developments figure in?
Chapter 11. The Implications and Prognosis
Why should you believe in scientific models? Addressing concerns over modeling. What can we extrapolate for the future?
Part 2 – Renewal
The second section explains what was learned from the oil age which can be used to create a post-fossil-fuel world. This includes analysis of the most important considerations for renewable energy, alternative energy carriers, and of smart energy conservation.
Chapter 12. Introduction and Energy Transition
Application of stochastic math beyond oil depletion. Projection of future energy demands
Chapter 13. Wind energy
How to characterize the statistics of wind variability.
Chapter 14. Solar energy
Physics of mass-produced photovoltaics.
Chapter 15. Battery technology
Physics of Lithium-ion batteries
Chapter 16. Thermal sources
Transport of heat
Chapter 17. Wave energy
Chapter 18. Climate
Models of climate prediction
Chapter 19. Travel and Terrain
Statistics of travel. Statistics of elevation
Chapter 21. Resilience and Durability
Building things to last, models of failure and corrosion
Chapter 22. Pollution
Dispersion and half-life in the context of nuclear energy and pollutants
Chapter 23. Noise and Uncertainty
How to characterize imperfect information
Chapter 24. Econophysics and Information Science
The statistics of humans in the loop, how disseminate information
Note that this thread will be for Petroleum related comments, any discussion of topics not directly related to oil or natural gas or the book should be in the non-Petroleum thread. Even comments discussing Part 2 of the book would be better to discuss in the Non-Petroleum Thread.