GEODynamics® has introduced its new StageCoach™ data analytics modeling solution. The field-proven StageCoach model accurately predicts how proppant and fluid will flow through wells to measurably improve well productivity by 10-15% and is included with GEODynamics’ perforating solutions.
Historical assumptions in the industry have held that proppant and fluid flow uniformly through wells, however GEODynamics’ primary research utilising surface tests with six US-based operators demonstrates this is untrue and can negatively impact well stimulation. The StageCoach solution addresses this challenge by accurately modelling proppant transport, distribution and erosion across clusters. This allows operators to be more deliberate when selecting hole size and/or charge type, enabling them to achieve the assumed distribution without cost variances. It also empowers operators with the foresight to know when and where to invest to maximise returns.
The StageCoach analytics package integrates computational fluid dynamics modeling of proppant slurry movement with full-scale proppant transport surface test results into an engineering model that optimises job parameters to ensure more uniform proppant distribution from cluster to cluster. As the model provides accurate data rooted in facts rather than interpretation, frac designs are more robust and reliable, preventing the superclusters that can cause well-to-well contact.
“We have gained compelling insights through the direct research and application of the StageCoach model which have the potential to dramatically improve overall frac design and well productivity,” said Steve Baumgartner, Senior Technical Advisor. “The StageCoach™ model not only accounts for a host of factors such as pump schedules, proppant loading, charge selection, perf spacing and phasing, and stress shadowing, but also provides access to our strategic projects team of leading industry technical advisors with more than 150 years of perforation and frac design experience combined to coach companies to achieve optimal stage design.”
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