How do I architect my Elasticsearch indexes for rapidly changing data?

I have two models in my MySQL database: Users and Posts

users have geolocation attributes (lat/long)

posts simply have a body of text.

I want to use Elasticsearch to find all posts that match a string of text plus use the user's location as a filter. The problem is -- the user's location always changes (as people walk around the city). I will be frequently updating the lat/long of each user.

This is my current solution:

Index the posts and have a geolocation attribute in each document. When a user changes location, run an elasticsearch batch update on all that user's posts, and modify the geolocation attribute on those documents.

Obviously this is not a scalable solution -- what if the user has 2000 posts and walks around the city? I'd have to update 2000 documents every minute.

Is there a way to "relationally map" the posts to the user's object and use it as a filter, so that when the location changes, I only need to update that user's object instead of all his posts?