The hybrid expanding liner system and machine learning (ML)-powered analytics help operators maximize productivity through to completion.
When it comes to re-fracturing, neither the Bullhead nor the liner system may be optimal, Kevin Aichinger, senior completions engineer at BKV, said during a June 17 panel on “New Technologies and AI in Reservoir Modeling, Drilling and Completions” at the Unconventional Resources Technology Conference (URTeC) in Houston.
Wells are candidates for refracking because of wide cluster spacing and poorly drained sections, abandoned drilling at the base of the well, and other reasons. Wells that are candidates for refracking typically have “multiple deficiencies stacked on top of each other,” he said. “The more deficient the original completion was, the better the chances are when it's time to refracking.”
At that point, he said, operators typically choose between the bullhead refracking method or installing a liner, which he said is more expensive but offers higher recovery rates than the bullhead option.
“If you spend more you get more, and if you spend less you get some but not much,” he said. “We wanted the best of both worlds.”
BKV has developed a hybrid expandable liner system with an expandable patch that it has used in wells in the Fort Worth Basin, he said. In the hybrid approach, only a portion of the well is lined, leaving the tip side of the well as the bullhead stage, and the remainder of the well is treated as a plug-and-perf stage.
Eichinger noted that the initial deployment in the BKV well in the Fort Worth Basin produced eight additional stages by lining 8 percent of the well, with the bullhead stage adding a total of a ninth stage within an existing lateral.
“This outperformed the entire field of fully lined wells,” he said, noting that this wasn't just a matter of luck or hitting a natural fracture.
The tracers revealed that the well's performance would have been significantly reduced if bullhead fracturing had been carried out, he added.
“Refracking with oil slicks really unlocks the well,” he said. “Everybody's saying the shale is going to slope off the cliff so steeply that maybe we just need to keep refracking with oil slicks.”
Go and enter the curve
Naviel Eldam, staff reservoir modeler and geologist at Encino Energy, said private oil and gas producers are using ML-based approaches to evaluate completion optimization potential for unconventional assets.
“At Encino, we don't use type curves, we only emulate,” he said of the Encino multivariate analysis technique, which uses geology, reservoir engineering and production data.
Whereas Type Curve runs a single binary decision tree regression on geographic location and completion vintage variables, Encino’s ML-based approach runs over 500 unique binary decision tree regressions on 20-30 variables before returning the most economical results for an optimized completion design.
“This allows us to take all the data, be consistent, be completely honest with ourselves and be data-driven,” Eldam said.
He says this approach typically tells operators which direction to go, and once tested in the field, it becomes a data point that is integrated into the next iteration of the program.
“The more data the better,” he said. “It works well in the U.S. unconventional oil fields, where there's a lot of well data.”
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URTeC 3855094 Hybrid Expandable Liner System: A Performance-Improved, Cost-Effective Alternative to Bullhead Refracturing
Kevin Eichinger, Sam French, Ken Day, Jared Brady, Ryan Epperson (BKV Corp.), and Richard Leonard and Brad Leonard (ProTechnics, Core Laboratories).
