I'm actually a physicist, and I agree with your requirement of defensible reason being more important than quantitative, but there is, as a physicist, some wriggle room. It depends on the quality of the data and the stage of development of the theory. For example, in Verhulst's time, there was no data with which one could do a reliable study of the effect of starvation alone, as opposed to starvation and disease, or starvation and war, etc. So Verhulst chose to simply posit that population tended toward a saturation number that was a new parameter in the Malthus model. In the absense of any real data, this was little more than an intellectual place holder for the idea that this model can't possibly be complete.

Then a century later Hubbert needs a simple formula for a time dependent quantity that starts very small, grows to a peak and then declines, ultimately to zero. He sees that Verhulst equation meets his criteria and uses it.

The Gauss normal curve also meets these theoretical criteria. I tried Gauss curve when first learning about PO. It leads to very messy algebra. There was no theory that supported using Gauss in this situation. The central limit theorem applies to large numbers of statistically independent events. Since I didn't want to use Gauss because the algebra was messy, it was easy for me to convince myself that there were surely not a large number of independent events in this situation.

He, like a physicist, doesn't have to justify trying it. Using it only needs justification if it works, and then the justification is more a discussion of what work needs to be done to develop a proper theory. Among other things, one needs to develop a good procedure for selecting data.

Elsewhere in the discussion I've posted a comment about how troubling it is that Hubbert linearization requires that the Hubbert peak be symmetric.

I think that we may very well witness the post peak decline in real life before we have a adequate theory of how to predict it. What we have now is good enough for economic hand waving, but as soon as decline is real there will be rapid changes that will lead to big forced changes in human behavior.

The Gauss Normal curve only kicks in when you apply the Shock Model to the discovery curve. The shock model places convolutions of slight production shifts corresponding to the fallow, construction, maturation, and extraction phases after the initial discovery (i.e. a sequence of statistically independent events). This trends the production curve to look more Gaussian.

You should look at this post http://mobjectivist.blogspot.com/2008/03/street-lamp-understanding-of-sh... to see how this all works in the context of the Oil Shock model. Convolutions of gaussians result in gaussians and all curves trend toward this property as a consequence of the CLT:

The only minor issue I have is this statement of yours:
"He, like a physicist, doesn't have to justify trying it. Using it only needs justification if it works, and then the justification is more a discussion of what work needs to be done to develop a proper theory. Among other things, one needs to develop a good procedure for selecting data."
Without the theory, this becomes the definition of a heuristic and it prevents us from making as fast a headway as possible. Can you imagine how slowly we would have advanced technologically if everything was based on heuristics instead of fundamental explainable laws such as Maxwell-Boltzmann and Fermi-Dirac statistics? If it wasn't for F-D in particular, we would still be wondering why a semiconductor transistor works at all!!

Otherwise I agree with everything you say and consider Verhulst's approach a deterministic trajectory and not the stochastic trajectory that we really should be using, ala the Dispersive Discovery model.