Oil prices have fallen back to a level they were at nearly four years ago. They’re about 1/3 the level they were at this summer.
So does this mean Peak Oil and the idea that we’re running out of petroleum was just so much hype and hand-wringing?
Probably not. It’s much like Global Warming. The fact that the Earth’s average temperature is being seen to rise doesn’t mean that every temperature on earth is automatically bumped up a couple of degrees with local highs a bit higher and local lows also a bit lower. Global warming drives global climate change. And global climate change is change – in some places things get much warmer, in other places things get colder. That’s because the connection between global warming and local climate is not linear, it’s non-linear. And non-linear relationships don’t have easy solutions. They strongly tend to the chaotic, which means you are very limited in being able to predict the localized behavior in a global system.
The wild price swings in Peak Oil appear to be a sign that our Oil supply has stopped being “smooth” or laminar i.e. linear. It’s become turbulent, chaotic or “non-linear”. Or, in the language I prefer, the petroleum economy has become brittle. It can no longer smoothly respond to inputs – small perturbations in the chain create large responses.
There’s an article up on the Oil Drum that points out the similarity between oil prices and queueing theory:
“One of my first dives into the Peak Oil world was with Kenneth Deffeyes’ book Beyond Oil. In it, the Princeton Professor explains how resources’ prices go through chaotic periods in face of scarce supply. Without knowing it, he derived an expression to explain movements like spot Natural Gas prices in the US after 2002, that was equivalent to Queueing Theory. This made immediate sense to me, after studying this theory in my formative years at the University.
Let me try to explain briefly what this theory is. Imagine a supermarket with a certain number of points-of-sale (POS), to which a certain number of costumers arrive per hour. Queueing Theory allows one to derive information like the average queue length at each POS and the average waiting time each costumer spends in the queue. This information is not only useful for supermarket managers but also in other fields like transport and tele-communications.
Queueing Theory shows also provides another important result: if the load on the system goes above a certain threshold, it becomes impossible to predict queue lengths or waiting times, and the system goes into chaos. Going back to the supermarket, imagine that for some reason the flow of costumers increases several-fold over its normal rhythm (e.g. Black Friday in the US). At first, lengthy queues form at each POS, waiting periods then go beyond costumers’ patience, and they simply start quitting the queue and leaving the supermarket without shopping. The dissatisfaction is such that costumers quit entering the supermarket altogether and the manager is eventually forced to close down some POS. But this is Black Friday, the avalanche of costumers eventually returns and it starts all over again. During this chaotic period a random sample of queue length at any given POS can result in any possible number and becomes effectively impossible to predict.”
Read the full article here.
A smooth and gradual drop in prices would have indicated that Peak Oil was still far in our future. But this rapid deflation of prices probably signifies something much more ominous.
I’m glad the new President and the new Vice-President like trains.