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Blade Energy Uses @RISK to Save on Drilling

Nov. 28, 2021
Lumivero
Published: Nov. 28, 2021

Blade Energy developed a statistical analysis tool that can estimate productivity improvements for underbalanced drilling. This tool is an Excel based application program that uses @RISK’s probability distributions and Monte Carlo simulation capability as its prediction/estimation engine.

Historic images of gushers make oil drilling look easy. But in today’s industry getting oil and gas safely and efficiently to the surface is a significant challenge. Rock formations can make drilling difficult, and oil seldom flows as expected.

Advanced drilling and extraction techniques are sometimes needed to optimize well efficiency. Drilling companies need to decide when and where to use these techniques.

Blade Energy in Frisco, TX, has developed a statistical analysis tool called “Under Balanced Drilling Productivity Improvement Estimator” (UBD PIE) that can estimate productivity improvements for underbalanced drilling. This tool uses data collected over years and a Bayesian algorithm to forecast the benefits of advanced techniques. UBD PIE is an Excel based application program that uses @RISK’s probability distributions and Monte Carlo simulation capability as its prediction/estimation engine.

“Our clients see the value of underbalanced drilling not only in productivity improvement but also in reservoir characterization”, says Shaikh Rahman of Blade Energy. He adds, “@RISK’s strong statistical capability has made UBD PIE robust.”

Blade Energy Partners was founded on a shared vision to provide the highest quality engineering solutions to complex problems in the energy industry. The company focuses on resolving challenging projects in a safe and cost-effective manner through intelligent application of innovative technologies. Specialties include UBD feasibilities, UBD design and implementation, and Critical Well Design.

"Our clients see the value of underbalanced drilling not only in productivity improvement but also in reservoir characterization. @RISK’s strong statistical capability has made UBD PIE robust."Shaikh Rahman
Blade Energy

Blade Energy developed a statistical analysis tool that can estimate productivity improvements for underbalanced drilling. This tool is an Excel based application program that uses @RISK’s probability distributions and Monte Carlo simulation capability as its prediction/estimation engine.

Historic images of gushers make oil drilling look easy. But in today’s industry getting oil and gas safely and efficiently to the surface is a significant challenge. Rock formations can make drilling difficult, and oil seldom flows as expected.

Advanced drilling and extraction techniques are sometimes needed to optimize well efficiency. Drilling companies need to decide when and where to use these techniques.

Blade Energy in Frisco, TX, has developed a statistical analysis tool called “Under Balanced Drilling Productivity Improvement Estimator” (UBD PIE) that can estimate productivity improvements for underbalanced drilling. This tool uses data collected over years and a Bayesian algorithm to forecast the benefits of advanced techniques. UBD PIE is an Excel based application program that uses @RISK’s probability distributions and Monte Carlo simulation capability as its prediction/estimation engine.

“Our clients see the value of underbalanced drilling not only in productivity improvement but also in reservoir characterization”, says Shaikh Rahman of Blade Energy. He adds, “@RISK’s strong statistical capability has made UBD PIE robust.”

Blade Energy Partners was founded on a shared vision to provide the highest quality engineering solutions to complex problems in the energy industry. The company focuses on resolving challenging projects in a safe and cost-effective manner through intelligent application of innovative technologies. Specialties include UBD feasibilities, UBD design and implementation, and Critical Well Design.

"Our clients see the value of underbalanced drilling not only in productivity improvement but also in reservoir characterization. @RISK’s strong statistical capability has made UBD PIE robust."Shaikh Rahman
Blade Energy

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