Very rough toy example.

Say I've started a project which I can definitely see 5 days worth of work. I estimate there'll be some unexpected work in there somewhere, maybe another day, so I estimate 6 days.

I complete day one but have found another day's work. When should I estimate completion now ? Taking the outside view, finishing in 6 days (on day 7) is too optimistic.

Implicit in my original estimate was a "rate of finding new work" of about 0.2 days per day. But, now I have more data on that, so I should update the 0.2 figure. Let's see, 0.2 is my prior, I should build a model for "rate of finding new work" and figure out what the correct Bayesian update is ... screw it, let's assume I won't find any more work today and estimate the rate by Laplace's rule of succession. My updated rate of finding new work is 0.5. Hmmm that's pretty high, the new work I find is itself going to generate new work, better sum the geometric series ... 5 known days work plus 5 more unknown, so I should finish in 10 days (ie day 11).

I complete day 2 and find another day's work ! Crank the handle around, should finish in 15 days (ie day 17).

... etc ...

If this state of affairs continues, my expected total amount of work grows really fast, and it won't be very long before it becomes clear that it is not profitable.

Contrast this with: I can see 5 days of work, but experience tells me that the total work is about 15 days. The first couple of days I turn up additional work, but I don't start to get worried until around day 3.

All in all, if you still believe the cost/benefit ratio is favorable, you should continue.

Assume it is. You continue, and your situation continues to get worse. Now what?