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Data Sources & Citations
Hydrogen Prospectivity Model & Input Layers
Gelman, S.E., Hearon, J.S., and Ellis, G.S., 2025, Prospectivity mapping for geologic hydrogen (ver. 1.2, January 22, 2025): U.S. Geological Survey Professional Paper 1900, 43 p., https://doi.org/10.3133/pp1900.
Hearon, J.S., Gelman, S.E., Ellis, G.S., Kinney, S.A., Miller, R.F., Tikku, A.A., Skinner, C.C., O’Halloran, M.M., and Zhang, M., 2025, Data Release for Prospectivity Mapping for Geologic Hydrogen: U.S. Geological Survey data release, https://doi.org/10.5066/P13WCG5U.
Magnetic Anomaly Grids
McCafferty, A.E., San Juan, C.A., Lawley, C.J.M., Graham, G.E., Gadd, M.G., Huston, D.L., Kelley, K.D., Paradis, S., Peter, J.M., and Czarnota, K., 2023, National-scale geophysical, geologic, and mineral resource data and grids for the United States, Canada, and Australia—Data in support of the tri-national Critical Minerals Mapping Initiative (ver. 1.1, March 2025): U.S. Geological Survey data release, https://doi.org/10.5066/P970GDD5.
Natural Gas Well Compositions (Training Data)
Brennan, S.T., Rivera, J.L., Creitz, R.H., Varela, B., and Park, A.J., 2021, Natural Gas Compositional Analyses Dataset of Gases from United States Wells: U.S. Geological Survey data release, https://doi.org/10.5066/P9TR93E3.
This interactive viewer was developed using publicly available USGS datasets. The supervised machine learning models (Random Forest, XGBoost, Weights of Evidence) were trained on H₂ mol% measurements from the Brennan and others (2021) well dataset against the prospectivity input layers from Hearon and others (2025) and magnetic anomaly derivatives from McCafferty and others (2023). Basemap tiles by CARTO (OpenStreetMap contributors).