Data Driven Optimized Cluster Placement
Deployed in over one hundred US Land wells, the optimized placement has shown increased production, smoother frac jobs, and lower overall completion costs.
Optimized Frac Designs
Using the primary logs from QLog, additional properties including Poisson’s Ratio, Young’s Modulus, Brittleness, and Minimum Horizontal Stress can be derived. These properties can be used to derive vertical and horizontal stress profiles, model frac treatments and optimize the placement of perforation clusters and plugs to correspond to changes in rock characteristics.
Data Science Meets Geomechanics - Optimized Frac Design
The goal of hydraulic fracturing has always been to maximize the stimulated rock volume (SRV) and enhance permeability in tight unconventional reservoirs. QFrac helps maximize your SRV by optimizing cluster locations so that fractures can grow freely by limiting the effects of in-situ stress differentials.
Quantico case studies have shown that equalizing stress across stages and clusters yields higher production and smoother frac jobs.
Reduce the odds of frac hits and preserve the stimulated rock volume of your stimulated wells.
Shorten the time to reach design rate. More frac jobs can be completed with the same equipment.
Completely data driven approach eliminates human subjectivity and bias from frac design.
Optimization of Well Completions in the Bakken Formation
In 2018, Quantico published a paper alongside Sinclair Oil Cor., Drilling Info, and NuTech Energy Alliance. This included an in-depth analysis of general hydraulic fracture design and how QFrac aids in optimizing cluster spacing to achieve higher oil production.
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