Holistic Machine-Learning Approach Recognizes Trouble Stages

Journal of Petroleum Technology 

The complete paper explores a holistic approach to characterizing trouble stages by applying automated event recognition of abnormal pressure increases and associating those events with formation and operational causes. This analysis of pressure increases provides insight into the potential causes of operational difficulties, and the related diagnostics can suggest improvements to future pump schedules. Improving how stages are pumped is profitable in both the short and the long term. Quantifying how design decisions ultimately affect operations can help decrease the frequency of operational problems and help realize these gains. The Cretaceous Eagle Ford Shale is the source rock for the Woodbine, Buda, and Austin Chalk.

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