Project Info

*Quantifying methane emissions from oil and gas

Dorit Hammerling
hammerling@mines.edu
Methane emissions are greenhouse gases and main contributors to climate change. With stricter regulations on the horizon, quantifying emissions from oil and gas operations, and creating mechanisms to alert the operators so they can address the cause of the emissions quickly, are critical. The project uses timely and cutting-edge sensor and satellite data and involves interesting statistical and machine learning approaches including data fusion and uncertainty quantification.

More Information:

Grand Challenge: Not applicable
This commentary provides a high-level overview and shows initial results: https://payneinstitute.mines.edu/wp-content/uploads/sites/149/2021/01/Payne-Institute-Commentary-Initial-Findings-from-Continuous-Monitoring-1.pdf

Primary Contacts:

Prof. Hammerling

Student Preparation

Qualifications

Some programming skills and willingness to learn more. Interest in working with large data and basic knowledge of statistical and machine learning methods. Inquisitive attitude and interest in team work.

TIME COMMITMENT (HRS/WK)

4

SKILLS/TECHNIQUES GAINED

Programming skills Statistical and Machine Learning modeling skills Skills working with large sensor and satellite data Basic knowledge of atmospheric science Team work and collaboration skills

MENTORING PLAN

I will have a fixed weekly meeting with the student, and I will be available to them via email for additional meetings. The student will also get a chance to interact with two graduate students working on the project.

PREFERRED STUDENT STATUS

Sophomore
Junior
Senior
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