Drilling automation

Future Workforce Education Through Big-Data Analysis for Drilling Optimization

An operator partnered with the drilling-automation research group at The University of Texas at Austin to develop a work flow for big-data analysis and visualization. The objectives were to maximize the value derived from data, establish an analysis toolkit, and train students on data analytics.

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Fig. 1—Key components in delivering value from big data.

An operator partnered with the drilling-automation research group at The University of Texas at Austin to develop a work flow for big-data analysis and visualization. The objectives were to maximize the value derived from data, establish an analysis toolkit, and train students on data analytics. The operator provided data sets, business and technical objectives, and guidance for the project, while a multidisciplinary group of undergraduate and graduate students piloted an analysis work flow.

Objectives

The project stakeholders agreed on three main objectives. The foremost objective was to maximize the value from the tens of gigabytes of data gathered during drilling operations.

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