Case Study: Blade Energy achieves underbalanced drilling productivity gains and cost savings with Palisade's @RISK

Blade Energy Uses @RISK to Save on Drilling

Blade Energy, an engineering firm in Frisco, TX, needed a reliable way to estimate productivity gains and decide when to deploy advanced underbalanced drilling techniques to improve well efficiency and reservoir characterization. To tackle this challenge they turned to Palisade and its @RISK product as the statistical engine for their analysis.

Blade Energy built the Excel-based Under Balanced Drilling Productivity Improvement Estimator (UBD PIE), which uses a Bayesian algorithm together with Palisade’s @RISK probability distributions and Monte Carlo simulation. By using Palisade, UBD PIE became a robust forecasting tool that quantifies expected productivity improvements, supports better reservoir characterization, and helps clients make cost-saving drilling decisions.

Blade Energy

Shaikh Rahman

Blade Energy