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Open-source gravity reduction workflows for geothermal resource assessment

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Abstract

Potential-field geophysical data such as gravity can enhance understanding of geothermal resources at all stages of the resource life cycle, including assessment, exploration, development, and monitoring, and at multiple scales, from the reservoir scale to regional scale.  However, to make gravity data useful for geothermal resource characterization, several processing steps are required to isolate the effects of density variations in the Earth’s crust to enable the identification of structural features associated with geothermal resources.  Although this process is well-established, standard computational implementations for processing gravity data that are FAIR (Findable, Accessible, Interoperable, and Reproduceable) are still lacking.  This paper details ongoing efforts at the U.S. Geological Survey (USGS) to develop a standard set of open-source Python tools for gravity data reduction that align with the FAIR principles.  This workflow makes use of existing open-source tools for geophysical data processing with the goal of maximizing opportunities for rapid improvements, interoperability, and adaptability to other types of geophysical data. 

Suggested Citation

Cronkite-Ratcliff, C., 2026, Open-source gravity reduction workflows for geothermal resource assessment, 51st Stanford Geothermal Workshop, Stanford, CA, February 9-11, 2026, 6 p.

Publication type Conference Paper
Publication Subtype Conference Paper
Title Open-source gravity reduction workflows for geothermal resource assessment
Publication Date March 01, 2026
Year Published 2026
Language English
Publisher Stanford University
Contributing office(s) Geology, Minerals, Energy, and Geophysics Science Center
Description 6 p.
Conference Title 51st Stanford Geothermal Workshop
Conference Location Stanford, CA
Conference Date February 9-11, 2026
Additional publication details