The Oil Shock model at its core consists of a time-stochastic phasing from discovery of oil regions to their maturation. For example, the Shaybah field in Saudi Arabia, though discovered in 1968 only come on line in 1998 and hasn't matured yet. Located in the "Empty Quarter", a particularly desolate and imposing place, this field provides a typical example of how the latency of each of the stages adds up to explain the shift of the discovery curve to the production curve. Although we can't say exactly how long the field remained fallow, or how long it took to construct the rigs, or how long the maturation process took, or even estimate the extraction rate, a global model would require a spread of these values representing the uncertainty/variability of these numbers from location to location and economy to economy. A good conservative estimator of the phases would lead one to guess at a mean with a standard deviation equal to the mean -- this becomes a decaying exponential distribution of latencies. The convolution of this set of exponentials generates the shifted and spread production curve originating from the tighter discovery profile.
The Law of Large Numbers
The Oil Shock model represents an entry from the law of large numbers argument. Given the fact that enough wells exist, I assert the model reflects reality.
For an example of someone trying to look at every deterministic bump, check out Stuart Staniford's analysis of recent Saudi production. This looks like tricky stuff; I might touch it with a 10-foot pole but wouldn't defend any trend it produced. I might have better success predicting the next location of a water strider. In other words, a sure trend could turn into the equivalent of Brownian motion.