Prediction accuracy for extended-reach laterals and high-intensity completions is improved by applying a Gaussian Process Regression (GPR) model with a Matérn kernel that accounts for parameter space sampling bias. The method adjusts predictions based on local data density and provides uncertainty quantification, increasing reliability in underrepresented regions of the design space. Applied to wells from the Bakken Formation, the model outperforms traditional approaches and supports confident forecasting for non-standard development designs.

Through recognizing our clients’ needs, our engineering expertise, and our proprietary in-house GATE Prho™ software engine, we provide customizable, cost-effective, easy-to use software tools to deliver better client outcomes quicker.

Corrosion modeling can be performed very early in project development to estimate the feasibility of carbon steel use. It can also augment many different aspects of the design and operations of sweet flowlines. To achieve this, data used for corrosion modeling must be sourced and attributed to the task in question.

CO2 corrosion modeling is a common practice to evaluate carbon steel flowlines and piping, both with and without inhibition, to ensure they achieve their intended design life. Modeling is also used to help determine if a corrosion resistant alloy should be used and can also be utilized to determine corrosion allowance and inhibition requirements.