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Drilling Data Cleaning and Preparation for Data Analytics Application

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Course Credit: 0.15 CEU, 1.5 PDH

Throughout the history of oil well drilling, service providers have been continuously striving to improve performance and reduce total drilling costs to operating companies. Despite constant improvement in tools, products and processes, data science cannot be applied straightaway due to data quality issues. But when achieved, the implementation of data science in the energy sector brings significant value in operational efficiency and drilling optimization. The challenge is how to efficiently process the massive amounts of data produced by the multitude of internet of thing (IOT) sensors at the rig. Once cleaned, the data can be fed into data analytics platforms and machine learning models to efficiently analyze trends and plan future well more efficiently. This roadmap can serve as a basis for drilling optimization. The objective of this presentation is to detail the various steps needed to prepare field drilling data for business analysis, as well discuss about data analytics and machine learning application in drilling operations. All content contained within this webinar is copyrighted by Daniel Braga and its use and/or reproduction outside the portal requires express permission from Daniel Braga.

OnePetro Papers:

Accuracy and Correction of Hook Load Measurements During Drilling Operations

Rapid Development of Real-Time Drilling Analytics System

Systematic Management for Drilling Process Improvement

 

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 1 chapter

Course Chapters

  • 1Drilling Data Cleaning and Preparation for Data Analytics Application - Chapter 1
    Media Type: Video

Credits

Earn credits by completing this course0.15 CEU credit1.5 PDH credits

Speakers

Daniel Braga