Jeff Pepin, PhD
Jeff Pepin is a Hydrologist at the USGS Central Energy Resources Science Center.
Jeff’s research focuses on geothermal resource characterization and resource assessment methodology development. His research often utilizes hydrothermal modeling, geostatistics, electromagnetic geophysics, and machine learning. He is also experienced collecting thermal and hydrogeologic data in the field to support these research efforts. Jeff currently leads the national thermal energy storage assessment program as part of the USGS Geothermal Resources Investigations Project (GRIP). He began his career with the USGS in 2016.
Professional Experience
2024 to present: Hydrologist, U.S. Geological Survey, Central Energy Resources Science Center, Denver, Colorado
2022 to 2024: Hydrologist, U.S. Geological Survey, Colorado Water Science Center, Denver, Colorado
2019 to 2022: Hydrologist, U.S. Geological Survey, New Mexico Water Science Center, Albuquerque, New Mexico
2016 to 2019: Student Trainee Hydrology, U.S. Geological Survey, New Mexico Water Science Center, Albuquerque, New Mexico
2012 to 2019: Research & Teaching Assistant, New Mexico Institute of Mining & Technology, Socorro, New Mexico
2012 to 2012: Well-Logging Specialist, New Mexico Bureau of Geology and Mineral Resources, Socorro, New Mexico
Education and Certifications
Ph.D. in Earth & Environmental Science with specialization in Hydrology, New Mexico Institute of Mining & Technology, 2019
M.S. in Hydrology, New Mexico Institute of Mining & Technology, 2015
B.S. in Geology, California State Polytechnic University Pomona, 2011
Science and Products
Salinity contributions from geothermal waters to the Rio Grande and shallow aquifer system in the transboundary Mesilla (United States)/Conejos-Médanos (Mexico) Basin Salinity contributions from geothermal waters to the Rio Grande and shallow aquifer system in the transboundary Mesilla (United States)/Conejos-Médanos (Mexico) Basin
Machine learning to identify geologic factors associated with production in geothermal fields: A case-study using 3D geologic data, Brady geothermal field, Nevada Machine learning to identify geologic factors associated with production in geothermal fields: A case-study using 3D geologic data, Brady geothermal field, Nevada
3-D geologic controls of hydrothermal fluid flow at Brady geothermal field, Nevada, USA 3-D geologic controls of hydrothermal fluid flow at Brady geothermal field, Nevada, USA
National-scale reservoir thermal energy storage pre-assessment for the United States National-scale reservoir thermal energy storage pre-assessment for the United States
Optimization assessment of a groundwater-level observation network in the Middle Rio Grande Basin, New Mexico Optimization assessment of a groundwater-level observation network in the Middle Rio Grande Basin, New Mexico
Non-USGS Publications**
**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.
Science and Products
Salinity contributions from geothermal waters to the Rio Grande and shallow aquifer system in the transboundary Mesilla (United States)/Conejos-Médanos (Mexico) Basin Salinity contributions from geothermal waters to the Rio Grande and shallow aquifer system in the transboundary Mesilla (United States)/Conejos-Médanos (Mexico) Basin
Machine learning to identify geologic factors associated with production in geothermal fields: A case-study using 3D geologic data, Brady geothermal field, Nevada Machine learning to identify geologic factors associated with production in geothermal fields: A case-study using 3D geologic data, Brady geothermal field, Nevada
3-D geologic controls of hydrothermal fluid flow at Brady geothermal field, Nevada, USA 3-D geologic controls of hydrothermal fluid flow at Brady geothermal field, Nevada, USA
National-scale reservoir thermal energy storage pre-assessment for the United States National-scale reservoir thermal energy storage pre-assessment for the United States
Optimization assessment of a groundwater-level observation network in the Middle Rio Grande Basin, New Mexico Optimization assessment of a groundwater-level observation network in the Middle Rio Grande Basin, New Mexico
Non-USGS Publications**
**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.