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Technical articles and abstracts centered around energy industry knowledge and lessons learned

Technical Abstract GATE Energy Technical Abstract GATE Energy

Machine Learning Methods for Handling Parameter Space Sampling Bias in Unconventional Well Performance Prediction

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.

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Technical Abstract GATE Energy Technical Abstract GATE Energy

Development of the NACE “MR-01-75” and NACE “TM-01-77” Standards: Part II – Accelerated Material Qualification Testing in Sour Environments at Near Atmospheric Pressure

This paper is Part II of a two-part series intended to narrate the history, some of which has been forgotten over time, leading up to the publication of the first Material Requirement (MR-01-75) standard prepared by NACE and its subsequent auxiliary standards.

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