Chilisa Shorten, PhD

Dr. Chilisa Shorten's research is focused on applying data science and machine learning algorithms to the USGS energy assessment process to improve constraints on assessment units, quantify and reduce uncertainty, and automate components of the process.


Dr. Shorten is a Mendenhall Postdoctoral Fellow and Research Geologist with the Central Energy Resources Science Center of the U.S. Geological Survey in Denver, CO. She holds a B.S. in geology from the University of Pittsburgh and a Ph.D. in earth sciences from Syracuse University. Her research background is in thermochronology, basin analysis and thermal history reconstruction applied to constraining the burial and exhumation history of the Appalachian Basin, including important continuous oil and gas resources. During her postdoctoral research at the USGS, she has determined statistically significant, key variables and scaling relationships in continuous resources using well and production data from plays across the US. Further research will improve the determination of assessment units through quantifying and reducing uncertainty of their boundaries. It is important to accurately constrain uncertainty of assessment units because the calculation estimated ultimate recovery values relies on the defined area. Her research integrates geologic understanding, data science and machine learning algorithms to inform USGS energy assessments, which are relied on to understand the future availability of energy resources.