Q: What are stress barriers and how do you find them?
A: Dr. Brendon Hall, VP of Geoscience and Kyle LaMotta, VP of Analytics share their thoughts on the stress barrier structure in the shale subsurface which can affect the economic impact of drilling a well with the presence of that stress barrier or the downside if the stress barrier isn’t there.
“A big part of what makes Petro.ai special,” Hall begins, “is the fact that we take account of stress changes in the earth very explicitly. We quantify so that your decisions can be certain.
“Methods like type curves are a data driven approach that predict the production time series from wells by grouping and binning them together. But they don’t explicitly account for stress changes in the earth or how wells that are next to each other are interacting.
“We drill these wells in the earth and then we complete them with high pressure water creating hydraulic fractures which directly manipulates the stress field. The interaction creates fractures that propagate out until they experience a region where stress is higher, regions which effectively push the rock back together and those are known as stress barriers. Stress barriers are regions of increased stress that slow down or even stop hydraulic fractures.
“What causes those stress barriers? Carbonates are a common cause, ancient reefs that have been deposited by organic secretions which have different lithologic properties than the rocks around them and can cause a stress difference. If they’re very stiff the stress can be higher. It’s situationally dependent.
“With Dr. Mark Zoback, Professor of Geoscience at Stanford University, we’re publishing an extension of his Viscoplastic Stress Relaxation Theory. This theory states that layers of rock with a lot of compliant, ductile material like clay and carbon have a plasticity to them so that over time these materials relax under the extreme stress loading in the subsurface, reconfiguring their stresses. That relaxation can cause the minimum horizontal stress, which is the stress experienced by horizontal fractures, to increase relative to the layers around it causing these ductile layers to become stress barriers as well.”
“That stress is important,” LaMotta adds.“ The way Petro.ai models the stress is going to help determine the frac geometries that we’re predicting which ties directly to the drainage or productivity of the rock. There are different data types that we can use to determine what the stress should be. It’s not a direct measure but there are lots of different diagnostics that we can use to help determine what that stress is.
“Some of the more common data types include direct measurements of stress called DFIT, the diagnostic fracture injection test. DFITs provide a good estimation of SHmin but are expensive and only test a point along the well bore, one data point for one physical location. You can take lots of DFITs and understand how the stress is changing vertically and spatially. Frequently those are not very high frequency data points.
“Petro.ai uses other data points like ISIPs, the instantaneous shut-in pressure measured during the frac job. These are noisier but can be calibrated with the DFITs. We can use the shape of the ISIPs which companies have more of and then use the DFITs as a calibration point to help interpret what that stress log should be. What Petro.ai ends up using is a log which is measurements along a depth for a given well.
“The key take away for Petro.ai is that the stress is going to be impactful for the frac geometry and that correlates directly to the well spacing. If there’s a stress barrier containing the frac, say, in an upward direction then you can put two wells close together vertically because you’re confident that those are not going to communicate. But you might not be able to place two wells with the stress barrier above it very close together horizontally because the energy is not being directed upward but outward so those fracs are going to propagate horizontally.