Statistical learning and its application in energy liability management

Develop a statistical model to predict the frequency and severity of contamination on oil and gas sites. Advanced statistical learning techniques will be employed to fully utilize the existing data and the data to be collected. The intern will work closely with colleagues in 360 to integrate domain knowledge into the model. The model will be used to generate cost estimates to remediate the contamination to ensure that oil and gas companies allocate sufficient funds to clean up their sites and reduce the number of Orphan wells across Western Canada. The project will benefit the partner organization 360 by bringing enhanced ability to predict the budget required for the oil and gas companies.

Faculty Supervisor:

Qingrun Zhang

Student:

Partner:

360 ELM

Discipline:

Mathematics

Sector:

Mining

University:

University of Calgary

Program: