The comment was too short, so I am posting this as an answer.
Well, clustering is a tough nut to crack, but there are some approximate ways. Let $b_n = a_{n+1}-a_{n}$, then any function that measures closeness of $(b_n)$ to zero would be more or less what you are looking for. For example take a histogram $(c_n)$ of $(b_n)$ and calculate $\sum_k \frac{c_k}{2^k}$ (it is easy to create different but similar formulas, you should pick one yourself that suits your sequences the best).
For another example take variance: for two sequences ($b_n$s, sequences of differences) with the same mean, low variance would mean constant, steady grow (no clustering) and high variance would mean necessarily some clustering. Also, you might want to look at higher moments, e.g. kurtosis, but I have no idea if that will be relevant to sequences you consider.
Finally, you could calculate the probability of your sequence in some probability space. For example you could assume some distribution with mean value being the mean of your sequence with condensation around it reflecting your idea of clusters.
I know that what I wrote is very vague, but I hope that it will give you some ideas. Cheers!