The integration gap

Agile teams have lots of ways to be integrated. They need to be socially integrated: they need to talk to each other, know what team-mates are working on, and have lots of connections to other agile teams and individuals. They need to be actively integrated: their workflows must complement one another's. If the geologist is working on new bulk density curves, the geophysicist uses those curves for the synthetic seismograms; if the geophysicist tweaks the seismic inversion result, the geomodeller uses that volume for the porosity distribution.

But the agile team also needs to be empirically integrated: the various datasets need to overlap somehow so they can be mutually calibrated and correlated. But if we think about the resolution of subsurface data, both spatially, in the (x,y) plane, and vertically, on the z axis, we reveal a problem—the integration gap.

This picks up again on scale (see previous post). Geophysical data is relatively low-resolution: we can learn all about large, thick features. But we know nothing about small things, about a metre in size, say. Conversely, well-based data can tell us lots about small things, even very small things indeed. A vertical well can tell us about thick things, but not spatially extensive things. A horizontal well can tell us a bit more about spatially large things, but not about thick things. And in between this small-scale well data and the large-scale seismic data? A gap. 

This little gap is responsible for much of the uncertainty we encounter in the subsurface. It is where the all-important well-tie lives. It leads to silos, un-integrated behaviour, and dysfunctional teams. And it's where all the fun is!

I've never thought about it before, but there doesn't seem to be an adjectival form of the word 'data'.