Bravo !
Correct and further more even the best data we have has errors far greater than the reported error ranges. The number of times its adjusted should indicate how poor we know our own oil production. My rule of thumb is we basically lose the entire production of Iran in the world totals. This sounds like a lot but its only a few percent plus or minus.

I'd love to see some of the number crunchers on the site extract a plausible error term for some of the numbers we rely on. Next I agree with Robert that these intrinsic errors cause the HL methods to themselves have a confidence range it would be nice to get a handle on what this is.

Overall it would be beneficial for everyone to understand what we know and don't know. Statistical error analysis is sorely needed.

Next looking at the size of the problem we face which was shown recently as a cube of oil measuring over a mile points out that the time of peak oil is not that important if its 30 years away all the better for us.
In hindsight we should have moved away from oil when production in the US peaked in the 70 and Europe should have done a far better job managing production from the North Sea.

Africa and the Middle East would have been far saner places if oil was viewed as a national resource to help create a real economy. The same for Russia. But as the saying goes don't cry over spilled milk. Recognize that we have had ample time to address this issue and valid and compelling reasons have existed for 30 years. Even now we can see that the failure of Jimmy Carters initiatives has resulted in a world thats not a happy place.

The possibility that we may have already peaked and the number of scenarios that point to a peak in the near future should only spur us to act on converting our economies from oil. The chance of a peak now or in the near future should not be required for us to act.

To compare to another overriding issue facing us. It looks like we may be too late on global warming lets not do the same for oil. We as a world are facing a increasing number of major worldwide problems if we continue to fail to act on some of them doomsday scenarios have a much higher probability of becoming reality. I'd be happy to see the world proactively do one thing right in my lifetime. Here is a list.

1.) Global Warming
2.) Population
3.) Water
4.) Food
5.) Other resources depletion ( oil water etc)
6.) Efficient cheap housing/transport
7.) Globalization and economic equality.

And more these are in order of relative importance notice that oil is not our biggest problem but they are not unrelated since all our other problems result in our inability to solve the Global Warming one.

WRT your comments on the degree of accuracy, i was shocked when i received some model data for the TrendLines Scenarios that was six decimal places. With their time range of 150 years, i usually round to the nearest mbd whether its Peak Rate or Exhaustion.

On RR's point on dates, some modelers are still using up to a ten year range. This commenced with Colin Campbell in 1991, but the practice is no longer the norm. Most nail a particular year.

Visitors to my site over the last know that since 2004 i have used the ASPO data to define a month and year for Peak Conventional Oil (April 2005) and Peak All Liquids (October 2012) for the half-way crossover of consumption (not supply). Each month, we analyse new data on past consumption and URR to refine these dates, but our experience has been that both dates move thru a 36-month range. Using season or Year would be more appropriate but is not as sexy.

URR Estimates are usually quoted as low as three decimal places (3.003-Tb or 1 billion barrels). This is somewhat reasonable as the scenario applications require accuracy to 25 billion barrels over the 150 year parameter.

Monthly and quarterly reporting revisions moves thru about a +/- range up to 1-mbd, hence the three decimal reporting seems ludicrous; and is more a reflection of reporting from small production nations.

Jean Laherrere has been a practioner of HL for two decades. Anyone following his work would have to agree that the above comments that it is accurate to only a +/- of five years is fair.

Form a practical standpoint any series of measurements is only as accurate as the least accurate individual measurements. That is if you have a measurement of a rectangle with one pair of sides at 10.05 and the other at 6, your answer can only be 60. If the first measurement is 6.0 your answer is 60.3, never 60.30. In the real world any thing that is being measured by inference, more than three significant figures is a opium dream.

The number of significant figures that are appropriate should depend on the margin of error of whatever the analysis is. With a very tight margin of error I could see four or five significant figures or even more. Obviously, not the situation in the crude oil production world. Might have relevance in the spectrographic analysis world or the electron microscopy world.

Trouble is, when looking up data, this information is almost never reported with the data, so we are left to guess, and guessing on the fuzzy side is usually the best policy.