But no-one's going to pay much attention to you unless you can show your model actually does a good job for some reasonable class of production regions. The reason Hubbert's model is famous is precisely because it has that property.

It obviously doesn't do a good job for the world as a whole -- as demonstrated by Colin Campbell's failed predictions.

The only value which the linearization method might have is its ability to predict peak oil. Now, IIRC, Deffeyes predicts peak oil for Thanksgiving Day 2005 based on the linearization method, so that's the reality check.

Also, the method isn't objective until you specify an objective algorithm for selecting the line, and apply it uniformly in all cases. Otherwise, it's just subjective voodoo.

Actually, Campbell wasn't using the linearization method I don't think - I believe he was sticking in an explicit URR and constraining his fit to that. I wouldn't do that since our knowledge of reserves sucks. Our knowledge of production is imperfect (the different authorities differ as to the production numbers- maybe the Joint Oil Data Initiative is going to help here), but it's better than reserves.

I agree with you that the predictions of the world peak are a good check. However, Deffeyes used a particular oil data series (and I don't actually know which one!), and it's only fair to do comparison to whatever series he was fitting too. Also, obviously there's significant noise, so it could well be off by a few years either way (as it was for the US). But I don't believe it's going to be decades off. We need to get to some error analysis here soon to tighten that up (but one thing at a time).