Feasibility Overview
The feasability assessment I’m attempting works like this:
- Define a likely range for the rate of oil decline (in Giagjoules/person/year)
- Define a likely range for the rate of substitution for potential technology, individually and in aggregate (also in Gigajoules/person/year)
There are 3 possible outcomes:
A. 1 is greater than 2, in which case peak oil can be considered a problem. We can then move discussion to the impacts of peak oil on the economy.
B. 2 is greater than 1, in which case peak oil is not so much of a problem.
C. Something went wrong in the analysis.
The next couple of posts in the feasibility assessment series will look at the likely timing and decline rate of conventional crude oil in order to define (1) above. To do that we need to know the following:
- How is oil discovered? Gotta find it first.
- How is oil extracted? Yep.
- How does reserve growth work? A tricky issue that needs its own post.
- How much oil is there?
Discovery
This post takes a look at oil discovery. I’m going to crib off WebHubbleTelescope (Web, for short) over at mobjectivist (sidebar) whose ‘Shock’ model takes what we know about the 4 points above and applies math. Web points out that the maths isn’t particularly hard, but he probably means ‘not that hard, if you studied maths at university level’, so I’ll break it down with analogies (for my own understanding more than anything else). Below is a chart showing global backdated discovery vs. oil extraction. Notable for the fact that we’re just not discovering like we used to, and we’ve been extracting more than we’ve been discovering:
Readers of mobjectivist will know that an oil discovery model that describes the data can be built from just two moving parts:
- an accelerating and dispersed search for oil.
- dispersed oil fields.
The Search for Oil
1. Why should the search for oil accelerate? Answer: Maximum Power.
Oil is highly useful. It’s liquid which makes it easy to transport. It’s energy dense, which makes it good for powering moving vehicles. When mixed with air it’s explosive which makes it good for releasing a lot of energy very quickly. But perhaps most importantly at least in the early days of oil discovery it had a very high Energy Return on Investment ratio (EROI). For every 1 barrel of oil worth of energy invested into prospecting, and pumping oil, oil companies in the 1930′s could expect to extract 100 barrels of oil ♣. High EROI resources are more likely to be scaled up quickly and gives industrial society the energy equivalent of a sugar rush. Oil extraction delivers much more available energy to society. A small fraction of that can be devoted to acquiring even more energy, accelerating the search. Humans in competitive environments will use energy consumption as their main status proxy. Nate Hagens has blogged extensively on this here. Ayres and Van de Bergh (2005)♥ describe how energy supply and energy demand are in a non-equilibrium feedback loop that drives economic growth (Figure 1. Inside loop). I quote them extensively below:
Figure 1. The feedback loops of economic growth
“This resource-driven feedback mechanism for growth is indicated by loop 1 in Figure 1. It can be described briefly as follows: technological progress has made fossil fuels steadily and dramatically cheaper and more convenient to use since the early 18th century. This, in turn, encouraged the substitution of fossil fuel-derived energy and mechanical power for work by animals and humans…Both cheaper fuels and better metals made it possible to construct better, cheaper, and more efficient machines, including steam engines and machine tools. This, in turn, permitted continuous and drastic further reductions in the cost of mining and transporting coal (later other fuels), and the delivery of mechanical power to users, including the coal mines and the transport systems themselves…
…Conceptually, the cycle consists of two separate elements. First, economic growth since 1800 has been driven, to a large extent, by utilizing machines (steam engines, internal combustion engines, and tractors) powered by fossil fuels as a substitute for, and multiplier of, human and animal labor. Second, the extensive use of fossil fuel-derived chemical fertilizers and pesticides on farms is another, more recent, technique of increasing productivity by using less labor. Naturally, as resource extraction and conversion costs fall due to economies of scale and learning-by-doing, economic growth is stimulated, resulting in a further increase in the overall use of raw materials and fossil fuels (this is the so-called ‘rebound effect’ writ large). In other words, a positive feedback mechanism is operative…
…It is important to emphasize that this feedback cycle is not merely a particular form of learning-by-doing, nor is it fundamentally attributable to scale economies, although both learning and scale are obviously involved and can reinforce it. One of the two key elements of the cycle is the availability, at ever-lower costs, of fossil fuels, initially coal, and subsequently petroleum and natural gas or nuclear energy. These are, of course, material resources. But they differ from other resources, such as construction materials, in that they are not embodied in products (except for plastics and synthetic fibers). They are entirely consumed for the purpose of generating heat, mechanical power, or electric power.”
A positive feedback loop between energy demand and supply is the essence of Maximum Power and stimulates an accelerating search for oil. As more people find oil useful, more knowledge is accumulated on how to find it, and more people get into the oil game. In some countries the search proceeds quickly (USA), while others take their time (Iraq), leading to varying rates of search.
Dispersion
2. What does dispersion mean and why are oil fields dispersed?
Take a look at the satellite photo below. It shows a lake prone region of Ontario, Canada. What do you see?
If you answered “lots of little lakes, a couple of mid-size lakes and 1 big lake (Trout lake) you’re on the right track. Lake size distribution is dispersed and you find the same thing with oil fields. Most oil comes from a few supergiant fields but most fields are much smaller. Web has plotted field sizes vs. field rank in the logarithmic chart below. The vertical axis is in logarithmic million barrels. From the chart we can see that the top 10 oil fields in the world are all over 20 Billion barrels in size. The next 90 largest fields are between about 20 billion and 2 billion barrels etc.
Combining the 2…
So when you have an accelerating searches (of variable rates), for fields of dispersed size, the discovery rate over time will look something the orange curve below:
I’ve taken the curve that Web describes here as an integration of all of the above and fitted it to backdated discovery data from here [xls]. Backdated discovery is really two processes (the initial discovery plus subsequent reserve growth backdated to the date of the initial discovery) so we can’t use this model for predicting future discovery. But we can see how this parsimonious model fits the data quite well. There’s a lot of noise, but that’s as we’d expect with such a large variation in field size.
An alternative?…
Its hard to find any correlation between price and discovery rates, so arguments that we will discover enough oil to prevent peaking as the price goes up are not reflected in the data (NB: to significantly delay peaking we would need to discover more than we consume, something that hasn’t consistently occurred for 30 years). The alternative explanation for the recent falling discovery is that OPEC and nationalised oil companies restricted discovery from the 1970′s onwards. In this narrative, without the discipline of competing in a free market nationalised oil companies have complacently allowed their exploration programs to go to pot. If only these countries would open up to the liberation of the free market, then the glory days of oil discovery will begin anew! I’ll chew over that one over the summer break, and get back to you in the new year…
♣ Hall, Powers and Schoenberg (2008) Peak Oil, EROI, Investments and the Economy in an Uncertain Future. Biofuels, Solar and Wind as Renewable Energy Systems
♥ Ayres and Van de Bergh (2005) A theory of economic growth with material/energy resources and dematerialization: Interaction of three growth mechanisms. Ecological Economics. Vol 55, Iss 1. http://dx.doi.org/10.1016/j.ecolecon.2004.07.023
