Zoback Introduces Frac Fingerprint and Viscoplastic Stress Relaxation Theory at URTeC 2022

Introducing Frac Fingerprint and Viscoplastic Stress Relaxation (VSR) Theory as deterministic parameters for the shale industry to accurately fix well placement and completions on their Drilling Spacing Units, Dr. Mark Zoback, Petro.ai Science Advisor and Professor of Geoscience at Stanford University, spoke to an overflowing crowd at the recent URTeC conference in Houston, Texas on June 20, 2022.

What do we mean by Frac Fingerprint, an important foundation piece of the Petro.ai Drilling Spacing Unit Design Service? “What we mean,” Zoback defines early in the presentation “is that in the gun barrel view the frac fingerprint refers to the pattern of both upward and lateral propagation that is the direct result of the position of the frac stage reflecting not only the magnitude of the stress but what’s above and below.”

The goal of estimating hydraulic frac propagation growth is to estimate the productivity of a well. That frac growth in both the lateral and horizontal directions is the result of estimating the stress as it changes with the lithography.

“We can model these variations in the least principal stress,” Zoback explains, “as a function of lithology, with depth. The reason that it’s affecting the stress is VSR, another important part of the Petro.ai DSU Design Service. The more clay a layer has the more it creeps. The more creep, the more it makes the stresses the same.

“Creep is a function of time. The clay rich environments mean the stresses become more isotropic. Just varying the position of the stage can give you a completely different outcome in placing a well. The important question is how does this affect production, how does this affect drainage? Where drainage is an important predictor of productivity.

“I began working on VSR a decade ago. Over that period, we’ve been studying in the lab and trying to make it applicable to industry workflows. Along the way we had a case where we had core and at the exact same depth, we had DFITs. We measured the VSR parameters and it fit the data. That’s not very practical. The workflow we finally developed used a few DFIT test calibrations, a suite of logs and that’s all you need. You don’t have to go through the step of predicting the VSR parameters for every layer.”

Pulling together the decades of study by Zoback and his Stanford colleagues, Dr. Troy Ruths, CEO of Petro.ai, and co-author of the URTeC publication, explains how Petro.ai has incorporated these learnings into the DSU Design Service.

“When you think about incorporating the frac fingerprint into your workflow, it gives you an opportunity to reimagine the workflow and provide a Rosetta Stone for your team’s different specialties to come together around their reservoir. The drainage has a signature effect on the well's productivity.”