Surface Deformation, Inverse Methods, and Machine Learning to Estimate the Distribution of Volumetric Changes for an Assembly of Caverns in a Salt Dome: Implications for Monitoring H<sub>2</sub> Storage.

Masterlark, Tim

Surface Deformation, Inverse Methods, and Machine Learning to Estimate the Distribution of Volumetric Changes for an Assembly of Caverns in a Salt Dome: Implications for Monitoring H₂ Storage.

Tim Masterlark¹, Scyller J. Borglum², Sophie Minas³, Nils Skaug³ and Sui Tung⁴, (1)South Dakota School of Mines and Technology, Rapid City, SD, United States, (2)WSP USA, Rapid City, United States, (3)WSP USA, Houston, United States, (4)University of Wisconsin-Madison, Madison, United States

Surface Deformation, Inverse Methods, and Machine Learning to Estimate the Distribution of Volumetric Changes for an Assembly of Caverns in a Salt Dome: Implications for Monitoring H2 Storage.

Surface Deformation, Inverse Methods, and Machine Learning to Estimate the Distribution of Volumetric Changes for an Assembly of Caverns in a Salt Dome: Implications for Monitoring H₂ Storage.