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Data Science and Analytics Applications in Petroleum Engineering – A Kick Start in Python

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Course Credit: 0.15 CEU, 1.5 PDH

Over the past decades, it has been obvious that engineers with coding and scripting skills outstand well above in their daily jobs.

Applying data analytics technologies to solve challenges in various petroleum engineering areas including production data wrangling, predictive modeling and visualization are key to find opportunities for improving oilfield asset economic value (e.g. optimize well locations, optimize reservoir management, optimize production and injection targets, maximize recovery factor, etc.)

This talk is a basic overview on the motivations to use Python to automate the PE daily tasks, as an alternative to Excel and some traditional engineering analytic applications. Few case examples are presented to introduce Python scripting realm. In the end, there is an outline on how the petroleum engineer of the future would be using data analytics and workflow automation to be more efficient.

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 1 chapter
  1 downloadable resource

Course Chapters

  • 1Data Science and Analytics Applications in Petroleum Engineering – A Kick Start in Python - Chapter 1
    Media Type: Video

Credits

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

Speakers

Dr. Luigi Saputelli