What do you mean by “fairly”?   Clearly, in order for a pruned bert-large to be effective, you need to prune those heads that are least useful.   There isn’t really anything “fair” about that.
What do you mean by “the weight distribution matches that of bert-base”?   I shouldn’t think that to be possible.   To start with, I’m pretty sure you will need to keep at least one head per layer, so that the data can flow through the model, and bert-large has 24 layers to bert-base’s 12.   Which weights are you hoping to match?   Furthermore, there’s no reason to suppose that the way the weights develop in bert-large will be similar to the way the weights develop in bert-base.
Are you investigating this purely for the interest of it, or because you want to use the result?