Tetris in the third dimension: object-based modeling

Luke is back at the Cognitive Whiteboard to take a look at how object-based modeling is a lot like playing your old Gameboy favourite in 3D. 

Click on the image below for a detailed view.



Tetris in the third dimension: object-based modeling

Hello, and welcome back to The Cognitive Whiteboard. My name's Luke, and today we're playing Tetris in 3D.

GEOLOGICAL MODEL from A different perspective 

I want to talk today about how I like to use object-based modeling for some of the more complex facies environments that I encounter. I'm going to use that as an example; this complex fluvial system that Boyan, from the Wave Consortium, recently highlighted on a fantastic LinkedIn post, where he really showed how you can use Google Earth to understand the true complexity that can occur on a geocellular scale for a geological model.

The original article by Boyan is  here

The original article by Boyan is here

So, this trace of his study through here has got 50 by 50 meter grid cells overlaying on it - a typical size, perhaps, for a geological model. What we can see, when we look at it, is that each individual cell within this system has got radically different potential permeability relationships. We might have systems that are mostly sand, but with a mud plug along one edge, would have no permeability in an east-west direction. Likewise, it could be the north-south orientation that gets destroyed by a mud plug. What it means is that when we try to represent the facies inside this system, it's not suitable just to think about rock types at one point, and then continuous properties in isolation: we need to pay attention to the relationships of both the facies and the continuous properties of those facies in 3D.

And so, with object-based modeling we can do this but, importantly, before we get in there, you can't model this system with one of these. So, the fluvial environment models that you see in object-based modeling typically look like these channel systems; often just a simple sinusoid with some levee banks. I can't see that anywhere here. I don't ever see that. In fact, what I usually see in these kinds of systems are things that look more like an aeolian dune or an oxbow lake. So my recommendation: usually I'm using things like the aeolian dunes, one after the other, to represent the development of those point bars that come across these systems.


Connecting the pieces: object-based rather than pixel-based modeling

We do have levees. We do have overflow banks. But by and far the dominant systems are those depositional environments that are occurring because of channel migration - so we want to represent that in our geology. So, how could we then use a shape like this and still get that kind of behavior in the permeability vector? So, what we can do with object-based modeling that's somewhat unique to object methods - as opposed to pixel-based methods - is that you can preserve individual orientation attributes of each one of the objects. In particular, directional trends, depth trends, and distance and curvature are properties that you can represent out of any one of your objects, and you can use this when you come to do your correlations for porosity and permeability now.

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So, how could I represent, perhaps, this feature here using those outputs? Well, if I knew that I had an oxbow lake coming around the edge, then I could preserve that permeability in the direction of the object. It's high, but counter to it is low. Likewise, I might want to say that these point bar systems have got coarser sediment at the base of them, and they're fining upwards across them, so that depth trend could come in very, very handy. It's very difficult, when you're doing your data analysis, to have hard data to correlate this against so you're gonna have to model that based upon your understanding of geology. But this method, together with that kind of third dimension in the context, is really the only way that I've ever seen that works to deliver the relationship between rock types and continuous properties - except for one other method that is developing that I've seen out there, coming out of Geneva. A method where you use multi-point statistics. They simultaneously simulate rock types and continuous properties, but as far as I know, that's not particularly commercially available yet. Anyway, I hope you enjoyed this. Thanks very much, and I'll see you again at The Cognitive Whiteboard next time.