October 1, 2020
Denver, Colorado USA

All openings for this course have been filled, but a waiting list is available.

If you'd like to be notified if an opening becomes available, you can place your name on the waiting list. Course openings will be filled from the waiting list in the order in which names have been placed on the list. Please click/tap the button below to add your name to the waiting list.

All openings for February session of this course have been filled, but registration is open for the May session.

About this course...

Practical Python for Earth Scientists is a hands-on course intended to introduce basic concepts and give working examples of python code that can be used in daily geoscience workflows. No prior knowledge of python or other programming languages is necessary to attend this course.

The course is being offered in conjunction with the Rocky Mountain Association of Geologists (RMAG). Website: https://rmag.org

Who should attend?

This course is tailored for geologists, geophysicists, petrophysicists, petroleum engineers, production engineers, landmen, and anyone else that would like to gain skills in practical python programming, data mining, and machine learning. While this course will use examples from the petroleum industry, any earth scientist will benefit from learning about geospatial and subsurface data analysis.

Course goals

  • Introduce the python programing language for the geoscientist.
  • Introduce python libraries that allow integration into other software programs through reading, manipulating, and writing LAS well logs and shapefiles.
  • Provide hands on examples of the application of Data Mining, Machine Learning, and Data Analytics to solve problems faced by a petroleum geologist.
  • By the end of the course students should be able to adapt the provided examples for use with their own data.

Topics covered

  • Basic python syntax
  • Loops and functions
  • Sorting and plotting data (pandas and matplotlib)
  • Geospatial data (e.g., shapefiles)
  • Well logs (las files)
  • Data scraping
  • Multivariate regression and residuals
  • Machine-learning (unsupervised and supervised methods)

The course starts at 8:00 AM MST and ends at 4:00 PM.

Course requirements

Bring your own laptop with administrator rights - you will need admin rights to install python. No experience required in python or other programming language.

Course instructors

Matt Bauer • 2M Energy

Thomas Martin • Colorado School of Mines

Zane Jobe • Colorado School of Mines

Continuing education credits

Colorado School of Mines will award 1.0 Continuing Education Credit (CEU) to participants who complete this course.

Registration

Registration for this course is open now. Enrollment is limited; therefore, applications will be accepted in the order received. Full information about fees, options, and payment methods is available. Learn more...

Location and parking

This course will be taught at Catalyst HTI, located in the RiNo neighborhood of Denver, Colorado. Learn more...

Further technical information

For more information about the course content, please contact:

Matt Bauer
2M Energy
matthew.w.bauer.pg@gmail.com

Zane Jobe
Research Professor, Colorado School of Mines
Director, Chevron Center of Research Excellence
core.mines.edu
zanejobe@mines.edu

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