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.