The Oil Drum: Australia/New Zealand

This is a guest post by James Ward. James has a background in science and engineering and is ASPO-Adelaide coordinator for ASPO-Australia. This post appeared previously on Energy Bulletin.

Abstract
By fitting a bell curve to historical phosphate production data, the best fit is obtained by assuming an ultimate recoverable resource of approximately 9 billion tonnes (of which about 6.3 billion tonnes have already been mined). This yields a peak in around 1990. Of course, the USGS claims an ultimate recoverable resource of some 24.3 billion tonnes (i.e. 18 billion remaining); however using this value yields a bell curve that is an inferior match to the historical data. A hypothesis is thus presented whereby phosphorus is considered in two broad forms: “easy” which is able to be mined quickly, but already peaked in 1990, and “hard” which has large remaining reserves and is yet to peak, but cannot be mined as quickly. (In reality there are probably many different forms ranging from very easy to very hard.) Just as with oil, estimates that lump all types of reserve in together will yield a theoretical peak that is high and distant, however the true system may involve periods of decline after exhausting easy-to-get reserves before other supplies come online to replace them. Ultimately we must develop a recyclable phosphorus supply if humans are to continue living on this planet.

There has been some discussion about how to apply the Hubbert Linearization (HL) to Saudi historical production in recent weeks at TOD. Trying not to fall into redundancy, let me have some loose thoughts on these models:

Three alternative Logistic models for Saudi production. Click for large version.

This post examines the impact of delaying oil field developments and producing at below capacity upon reserves estimates made using Hubbert Linearisation. Robert Rapier had a similar post some months back using synthetic data. This post uses real data from Norway and three different story lines are described and analysed.

1. Norway
2. Fjordland – same as Norway but with 4 fields allowed to lie fallow and 20% of production withheld from 1981 to the present day
3. Fjelland – same as Fjordland but with the 4 fallow fields developed in 2001-2004 and full production reinstated from 2002.

The significance for predicting national and global oil reserves and peak oil are discussed.

An empirical study of the impact producing at below capacity has on the Qt intercept of a Hubbert Linearisation (HL) shows exact proportionality. If a country produces at 90% of capacity, the Qt intercept is 90% of actual URR (ultimate recoverable reserves) and so forth.

On this basis the following methodology for applying HL is proposed.

Peak oil has made us aware that many of the resources on which civilization depends are limited.

M. King Hubbert, a geophysicist for Shell Oil, found that oil production over time followed a curve that was roughly bell-shaped. He correctly predicted that oil production in the lower 48 states would peak in 1970. Other analysts following Hubbert's methods are predicting a peak in oil production early this century.

The depletion analysis pioneered by Hubbert can be applied to other non-renewable resources. Analysts have looked at peak production for resouces such as natural gas, coal and uranium.

In this paper, Patrick Déry applies Hubbert's methods to a very special non-renewable resource - phosphorus - a nutrient essential for agriculture.

This a post by Jeffrey J. Brown (westexas)

Part II: The Titanic, Oilsville, and Saudi Arabia

In Part I, we examined the evolving Hubbert Linearization (HL) of Texas oil production, and found that the predictive precision of the technique was quite poor. The error range was on the order of 3 decades. However, some have suggested that the trends just need to stabilize, and then we can be more confident in the predictions. Others offered rationalizations for why Texas behaved as it did, and suggested that the HL is still a useful predictive tool provided we somehow filter the data. Still others suggested that it is futile to attempt to linearize non-linear data. In this essay, we will push this issue further. I will examine more cases that cast grave doubts in my mind that the HL can accurately predict anything.

But first, does this debate even matter?

Part I- Texas Myths

Like Cindy Crawford, I have done quite a bit of modeling in my career. However, mine has been in front of a computer. There are various types of models. They can be empirical, such that you curve fit data without having a clear explanation of the underlying mechanisms. Or they can be theoretical, in which the system is modeled according to the governing scientific principles and mathematical equations.

However, one thing is critical to keep in mind. If you are going to use the model for forecasting, the model must be tested. Testing the model is called “validation”, or sometimes “back-casting.” This involves feeding the model real data, and observing how well the predictions match up with the observations. If the predictions match up on a consistent basis, and any large variations are explainable, you have the makings of a predictive model. If you have not validated your model, or if you have attempted to validate it and found that the predictions were inconsistent, the model should be used with caution (if at all). In this essay I have done some back-casts on the Hubbert Linearization (HL) model and attempted to use it to make predictions using historical data.

Resolved: World Net Oil Export Capacity is Now Declining Because of Involuntary Reductions in Production and/or Because of Increases in Domestic Consumption in Major Oil Exporting Countries

Robert Rapier suggested that we debate this topic, and I agreed. In reality, there are only shades of gray difference between us regarding the timing of Peak Oil and Peak Exports. I believe that the crisis has hit, while Robert believes that the worst won't be upon us until some time shortly after 2010. Robert will file his rejoinder about a week from today.